Soft Mixer Assignment in a Hierarchical Generative Model of Natural Scene Statistics

PubMed Central

Schwartz, Odelia; Sejnowski, Terrence J.; Dayan, Peter

2010-01-01

Gaussian scale mixture models offer a top-down description of signal generation that captures key bottom-up statistical characteristics of filter responses to images. However, the pattern of dependence among the filters for this class of models is prespecified. We propose a novel extension to the gaussian scale mixture model that learns the pattern of dependence from observed inputs and thereby induces a hierarchical representation of these inputs. Specifically, we propose that inputs are generated by gaussian variables (modeling local filter structure), multiplied by a mixer variable that is assigned probabilistically to each input from a set of possible mixers. We demonstrate inference of both components of the generative model, for synthesized data and for different classes of natural images, such as a generic ensemble and faces. For natural images, the mixer variable assignments show invariances resembling those of complex cells in visual cortex; the statistics of the gaussian components of the model are in accord with the outputs of divisive normalization models. We also show how our model helps interrelate a wide range of models of image statistics and cortical processing. PMID:16999575

Face recognition via edge-based Gabor feature representation for plastic surgery-altered images

NASA Astrophysics Data System (ADS)

Chude-Olisah, Chollette C.; Sulong, Ghazali; Chude-Okonkwo, Uche A. K.; Hashim, Siti Z. M.

2014-12-01

Plastic surgery procedures on the face introduce skin texture variations between images of the same person (intra-subject), thereby making the task of face recognition more difficult than in normal scenario. Usually, in contemporary face recognition systems, the original gray-level face image is used as input to the Gabor descriptor, which translates to encoding some texture properties of the face image. The texture-encoding process significantly degrades the performance of such systems in the case of plastic surgery due to the presence of surgically induced intra-subject variations. Based on the proposition that the shape of significant facial components such as eyes, nose, eyebrow, and mouth remains unchanged after plastic surgery, this paper employs an edge-based Gabor feature representation approach for the recognition of surgically altered face images. We use the edge information, which is dependent on the shapes of the significant facial components, to address the plastic surgery-induced texture variation problems. To ensure that the significant facial components represent useful edge information with little or no false edges, a simple illumination normalization technique is proposed for preprocessing. Gabor wavelet is applied to the edge image to accentuate on the uniqueness of the significant facial components for discriminating among different subjects. The performance of the proposed method is evaluated on the Georgia Tech (GT) and the Labeled Faces in the Wild (LFW) databases with illumination and expression problems, and the plastic surgery database with texture changes. Results show that the proposed edge-based Gabor feature representation approach is robust against plastic surgery-induced face variations amidst expression and illumination problems and outperforms the existing plastic surgery face recognition methods reported in the literature.

Multi-texture local ternary pattern for face recognition

NASA Astrophysics Data System (ADS)

Essa, Almabrok; Asari, Vijayan

2017-05-01

In imagery and pattern analysis domain a variety of descriptors have been proposed and employed for different computer vision applications like face detection and recognition. Many of them are affected under different conditions during the image acquisition process such as variations in illumination and presence of noise, because they totally rely on the image intensity values to encode the image information. To overcome these problems, a novel technique named Multi-Texture Local Ternary Pattern (MTLTP) is proposed in this paper. MTLTP combines the edges and corners based on the local ternary pattern strategy to extract the local texture features of the input image. Then returns a spatial histogram feature vector which is the descriptor for each image that we use to recognize a human being. Experimental results using a k-nearest neighbors classifier (k-NN) on two publicly available datasets justify our algorithm for efficient face recognition in the presence of extreme variations of illumination/lighting environments and slight variation of pose conditions.

Modeling first impressions from highly variable facial images.

PubMed

Vernon, Richard J W; Sutherland, Clare A M; Young, Andrew W; Hartley, Tom

2014-08-12

First impressions of social traits, such as trustworthiness or dominance, are reliably perceived in faces, and despite their questionable validity they can have considerable real-world consequences. We sought to uncover the information driving such judgments, using an attribute-based approach. Attributes (physical facial features) were objectively measured from feature positions and colors in a database of highly variable "ambient" face photographs, and then used as input for a neural network to model factor dimensions (approachability, youthful-attractiveness, and dominance) thought to underlie social attributions. A linear model based on this approach was able to account for 58% of the variance in raters' impressions of previously unseen faces, and factor-attribute correlations could be used to rank attributes by their importance to each factor. Reversing this process, neural networks were then used to predict facial attributes and corresponding image properties from specific combinations of factor scores. In this way, the factors driving social trait impressions could be visualized as a series of computer-generated cartoon face-like images, depicting how attributes change along each dimension. This study shows that despite enormous variation in ambient images of faces, a substantial proportion of the variance in first impressions can be accounted for through linear changes in objectively defined features.

Sparse Feature Extraction for Pose-Tolerant Face Recognition.

PubMed

Abiantun, Ramzi; Prabhu, Utsav; Savvides, Marios

2014-10-01

Automatic face recognition performance has been steadily improving over years of research, however it remains significantly affected by a number of factors such as illumination, pose, expression, resolution and other factors that can impact matching scores. The focus of this paper is the pose problem which remains largely overlooked in most real-world applications. Specifically, we focus on one-to-one matching scenarios where a query face image of a random pose is matched against a set of gallery images. We propose a method that relies on two fundamental components: (a) A 3D modeling step to geometrically correct the viewpoint of the face. For this purpose, we extend a recent technique for efficient synthesis of 3D face models called 3D Generic Elastic Model. (b) A sparse feature extraction step using subspace modeling and ℓ1-minimization to induce pose-tolerance in coefficient space. This in return enables the synthesis of an equivalent frontal-looking face, which can be used towards recognition. We show significant performance improvements in verification rates compared to commercial matchers, and also demonstrate the resilience of the proposed method with respect to degrading input quality. We find that the proposed technique is able to match non-frontal images to other non-frontal images of varying angles.

Development of facial aging simulation system combined with three-dimensional shape prediction from facial photographs

NASA Astrophysics Data System (ADS)

Nagata, Takeshi; Matsuzaki, Kazutoshi; Taniguchi, Kei; Ogawa, Yoshinori; Imaizumi, Kazuhiko

2017-03-01

3D Facial aging changes in more than 10 years of identical persons are being measured at National Research Institute of Police Science. We performed machine learning using such measured data as teacher data and have developed the system which convert input 2D face image into 3D face model and simulate aging. Here, we report about processing and accuracy of our system.

Seeing Jesus in toast: neural and behavioral correlates of face pareidolia.

PubMed

Liu, Jiangang; Li, Jun; Feng, Lu; Li, Ling; Tian, Jie; Lee, Kang

2014-04-01

Face pareidolia is the illusory perception of non-existent faces. The present study, for the first time, contrasted behavioral and neural responses of face pareidolia with those of letter pareidolia to explore face-specific behavioral and neural responses during illusory face processing. Participants were shown pure-noise images but were led to believe that 50% of them contained either faces or letters; they reported seeing faces or letters illusorily 34% and 38% of the time, respectively. The right fusiform face area (rFFA) showed a specific response when participants "saw" faces as opposed to letters in the pure-noise images. Behavioral responses during face pareidolia produced a classification image (CI) that resembled a face, whereas those during letter pareidolia produced a CI that was letter-like. Further, the extent to which such behavioral CIs resembled faces was directly related to the level of face-specific activations in the rFFA. This finding suggests that the rFFA plays a specific role not only in processing of real faces but also in illusory face perception, perhaps serving to facilitate the interaction between bottom-up information from the primary visual cortex and top-down signals from the prefrontal cortex (PFC). Whole brain analyses revealed a network specialized in face pareidolia, including both the frontal and occipitotemporal regions. Our findings suggest that human face processing has a strong top-down component whereby sensory input with even the slightest suggestion of a face can result in the interpretation of a face. Copyright © 2014 Elsevier Ltd. All rights reserved.

Applied learning-based color tone mapping for face recognition in video surveillance system

NASA Astrophysics Data System (ADS)

Yew, Chuu Tian; Suandi, Shahrel Azmin

2012-04-01

In this paper, we present an applied learning-based color tone mapping technique for video surveillance system. This technique can be applied onto both color and grayscale surveillance images. The basic idea is to learn the color or intensity statistics from a training dataset of photorealistic images of the candidates appeared in the surveillance images, and remap the color or intensity of the input image so that the color or intensity statistics match those in the training dataset. It is well known that the difference in commercial surveillance cameras models, and signal processing chipsets used by different manufacturers will cause the color and intensity of the images to differ from one another, thus creating additional challenges for face recognition in video surveillance system. Using Multi-Class Support Vector Machines as the classifier on a publicly available video surveillance camera database, namely SCface database, this approach is validated and compared to the results of using holistic approach on grayscale images. The results show that this technique is suitable to improve the color or intensity quality of video surveillance system for face recognition.

Face recognition by applying wavelet subband representation and kernel associative memory.

PubMed

Zhang, Bai-Ling; Zhang, Haihong; Ge, Shuzhi Sam

2004-01-01

In this paper, we propose an efficient face recognition scheme which has two features: 1) representation of face images by two-dimensional (2-D) wavelet subband coefficients and 2) recognition by a modular, personalised classification method based on kernel associative memory models. Compared to PCA projections and low resolution "thumb-nail" image representations, wavelet subband coefficients can efficiently capture substantial facial features while keeping computational complexity low. As there are usually very limited samples, we constructed an associative memory (AM) model for each person and proposed to improve the performance of AM models by kernel methods. Specifically, we first applied kernel transforms to each possible training pair of faces sample and then mapped the high-dimensional feature space back to input space. Our scheme using modular autoassociative memory for face recognition is inspired by the same motivation as using autoencoders for optical character recognition (OCR), for which the advantages has been proven. By associative memory, all the prototypical faces of one particular person are used to reconstruct themselves and the reconstruction error for a probe face image is used to decide if the probe face is from the corresponding person. We carried out extensive experiments on three standard face recognition datasets, the FERET data, the XM2VTS data, and the ORL data. Detailed comparisons with earlier published results are provided and our proposed scheme offers better recognition accuracy on all of the face datasets.

Deep Convolutional Neural Networks for Classifying Body Constitution Based on Face Image.

PubMed

Huan, Er-Yang; Wen, Gui-Hua; Zhang, Shi-Jun; Li, Dan-Yang; Hu, Yang; Chang, Tian-Yuan; Wang, Qing; Huang, Bing-Lin

2017-01-01

Body constitution classification is the basis and core content of traditional Chinese medicine constitution research. It is to extract the relevant laws from the complex constitution phenomenon and finally build the constitution classification system. Traditional identification methods have the disadvantages of inefficiency and low accuracy, for instance, questionnaires. This paper proposed a body constitution recognition algorithm based on deep convolutional neural network, which can classify individual constitution types according to face images. The proposed model first uses the convolutional neural network to extract the features of face image and then combines the extracted features with the color features. Finally, the fusion features are input to the Softmax classifier to get the classification result. Different comparison experiments show that the algorithm proposed in this paper can achieve the accuracy of 65.29% about the constitution classification. And its performance was accepted by Chinese medicine practitioners.

Novel face-detection method under various environments

NASA Astrophysics Data System (ADS)

Jing, Min-Quan; Chen, Ling-Hwei

2009-06-01

We propose a method to detect a face with different poses under various environments. On the basis of skin color information, skin regions are first extracted from an input image. Next, the shoulder part is cut out by using shape information and the head part is then identified as a face candidate. For a face candidate, a set of geometric features is applied to determine if it is a profile face. If not, then a set of eyelike rectangles extracted from the face candidate and the lighting distribution are used to determine if the face candidate is a nonprofile face. Experimental results show that the proposed method is robust under a wide range of lighting conditions, different poses, and races. The detection rate for the HHI face database is 93.68%. For the Champion face database, the detection rate is 95.15%.

A Two-Stage Framework for 3D Face Reconstruction from RGBD Images.

PubMed

Wang, Kangkan; Wang, Xianwang; Pan, Zhigeng; Liu, Kai

2014-08-01

This paper proposes a new approach for 3D face reconstruction with RGBD images from an inexpensive commodity sensor. The challenges we face are: 1) substantial random noise and corruption are present in low-resolution depth maps; and 2) there is high degree of variability in pose and face expression. We develop a novel two-stage algorithm that effectively maps low-quality depth maps to realistic face models. Each stage is targeted toward a certain type of noise. The first stage extracts sparse errors from depth patches through the data-driven local sparse coding, while the second stage smooths noise on the boundaries between patches and reconstructs the global shape by combining local shapes using our template-based surface refinement. Our approach does not require any markers or user interaction. We perform quantitative and qualitative evaluations on both synthetic and real test sets. Experimental results show that the proposed approach is able to produce high-resolution 3D face models with high accuracy, even if inputs are of low quality, and have large variations in viewpoint and face expression.

Familiarity Detection is an Intrinsic Property of Cortical Microcircuits with Bidirectional Synaptic Plasticity.

PubMed

Zhang, Xiaoyu; Ju, Han; Penney, Trevor B; VanDongen, Antonius M J

2017-01-01

Humans instantly recognize a previously seen face as "familiar." To deepen our understanding of familiarity-novelty detection, we simulated biologically plausible neural network models of generic cortical microcircuits consisting of spiking neurons with random recurrent synaptic connections. NMDA receptor (NMDAR)-dependent synaptic plasticity was implemented to allow for unsupervised learning and bidirectional modifications. Network spiking activity evoked by sensory inputs consisting of face images altered synaptic efficacy, which resulted in the network responding more strongly to a previously seen face than a novel face. Network size determined how many faces could be accurately recognized as familiar. When the simulated model became sufficiently complex in structure, multiple familiarity traces could be retained in the same network by forming partially-overlapping subnetworks that differ slightly from each other, thereby resulting in a high storage capacity. Fisher's discriminant analysis was applied to identify critical neurons whose spiking activity predicted familiar input patterns. Intriguingly, as sensory exposure was prolonged, the selected critical neurons tended to appear at deeper layers of the network model, suggesting recruitment of additional circuits in the network for incremental information storage. We conclude that generic cortical microcircuits with bidirectional synaptic plasticity have an intrinsic ability to detect familiar inputs. This ability does not require a specialized wiring diagram or supervision and can therefore be expected to emerge naturally in developing cortical circuits.

Familiarity Detection is an Intrinsic Property of Cortical Microcircuits with Bidirectional Synaptic Plasticity

PubMed Central

2017-01-01

Abstract Humans instantly recognize a previously seen face as “familiar.” To deepen our understanding of familiarity-novelty detection, we simulated biologically plausible neural network models of generic cortical microcircuits consisting of spiking neurons with random recurrent synaptic connections. NMDA receptor (NMDAR)-dependent synaptic plasticity was implemented to allow for unsupervised learning and bidirectional modifications. Network spiking activity evoked by sensory inputs consisting of face images altered synaptic efficacy, which resulted in the network responding more strongly to a previously seen face than a novel face. Network size determined how many faces could be accurately recognized as familiar. When the simulated model became sufficiently complex in structure, multiple familiarity traces could be retained in the same network by forming partially-overlapping subnetworks that differ slightly from each other, thereby resulting in a high storage capacity. Fisher’s discriminant analysis was applied to identify critical neurons whose spiking activity predicted familiar input patterns. Intriguingly, as sensory exposure was prolonged, the selected critical neurons tended to appear at deeper layers of the network model, suggesting recruitment of additional circuits in the network for incremental information storage. We conclude that generic cortical microcircuits with bidirectional synaptic plasticity have an intrinsic ability to detect familiar inputs. This ability does not require a specialized wiring diagram or supervision and can therefore be expected to emerge naturally in developing cortical circuits. PMID:28534043

Modeling first impressions from highly variable facial images

PubMed Central

Vernon, Richard J. W.; Sutherland, Clare A. M.; Young, Andrew W.; Hartley, Tom

2014-01-01

First impressions of social traits, such as trustworthiness or dominance, are reliably perceived in faces, and despite their questionable validity they can have considerable real-world consequences. We sought to uncover the information driving such judgments, using an attribute-based approach. Attributes (physical facial features) were objectively measured from feature positions and colors in a database of highly variable “ambient” face photographs, and then used as input for a neural network to model factor dimensions (approachability, youthful-attractiveness, and dominance) thought to underlie social attributions. A linear model based on this approach was able to account for 58% of the variance in raters’ impressions of previously unseen faces, and factor-attribute correlations could be used to rank attributes by their importance to each factor. Reversing this process, neural networks were then used to predict facial attributes and corresponding image properties from specific combinations of factor scores. In this way, the factors driving social trait impressions could be visualized as a series of computer-generated cartoon face-like images, depicting how attributes change along each dimension. This study shows that despite enormous variation in ambient images of faces, a substantial proportion of the variance in first impressions can be accounted for through linear changes in objectively defined features. PMID:25071197

Two-Stream Transformer Networks for Video-based Face Alignment.

PubMed

Liu, Hao; Lu, Jiwen; Feng, Jianjiang; Zhou, Jie

2017-08-01

In this paper, we propose a two-stream transformer networks (TSTN) approach for video-based face alignment. Unlike conventional image-based face alignment approaches which cannot explicitly model the temporal dependency in videos and motivated by the fact that consistent movements of facial landmarks usually occur across consecutive frames, our TSTN aims to capture the complementary information of both the spatial appearance on still frames and the temporal consistency information across frames. To achieve this, we develop a two-stream architecture, which decomposes the video-based face alignment into spatial and temporal streams accordingly. Specifically, the spatial stream aims to transform the facial image to the landmark positions by preserving the holistic facial shape structure. Accordingly, the temporal stream encodes the video input as active appearance codes, where the temporal consistency information across frames is captured to help shape refinements. Experimental results on the benchmarking video-based face alignment datasets show very competitive performance of our method in comparisons to the state-of-the-arts.

Coupled Dictionary Learning for the Detail-Enhanced Synthesis of 3-D Facial Expressions.

PubMed

Liang, Haoran; Liang, Ronghua; Song, Mingli; He, Xiaofei

2016-04-01

The desire to reconstruct 3-D face models with expressions from 2-D face images fosters increasing interest in addressing the problem of face modeling. This task is important and challenging in the field of computer animation. Facial contours and wrinkles are essential to generate a face with a certain expression; however, these details are generally ignored or are not seriously considered in previous studies on face model reconstruction. Thus, we employ coupled radius basis function networks to derive an intermediate 3-D face model from a single 2-D face image. To optimize the 3-D face model further through landmarks, a coupled dictionary that is related to 3-D face models and their corresponding 3-D landmarks is learned from the given training set through local coordinate coding. Another coupled dictionary is then constructed to bridge the 2-D and 3-D landmarks for the transfer of vertices on the face model. As a result, the final 3-D face can be generated with the appropriate expression. In the testing phase, the 2-D input faces are converted into 3-D models that display different expressions. Experimental results indicate that the proposed approach to facial expression synthesis can obtain model details more effectively than previous methods can.

Image-Based 3D Face Modeling System

NASA Astrophysics Data System (ADS)

Park, In Kyu; Zhang, Hui; Vezhnevets, Vladimir

2005-12-01

This paper describes an automatic system for 3D face modeling using frontal and profile images taken by an ordinary digital camera. The system consists of four subsystems including frontal feature detection, profile feature detection, shape deformation, and texture generation modules. The frontal and profile feature detection modules automatically extract the facial parts such as the eye, nose, mouth, and ear. The shape deformation module utilizes the detected features to deform the generic head mesh model such that the deformed model coincides with the detected features. A texture is created by combining the facial textures augmented from the input images and the synthesized texture and mapped onto the deformed generic head model. This paper provides a practical system for 3D face modeling, which is highly automated by aggregating, customizing, and optimizing a bunch of individual computer vision algorithms. The experimental results show a highly automated process of modeling, which is sufficiently robust to various imaging conditions. The whole model creation including all the optional manual corrections takes only 2[InlineEquation not available: see fulltext.]3 minutes.

Unconstrained face detection and recognition based on RGB-D camera for the visually impaired

NASA Astrophysics Data System (ADS)

Zhao, Xiangdong; Wang, Kaiwei; Yang, Kailun; Hu, Weijian

2017-02-01

It is highly important for visually impaired people (VIP) to be aware of human beings around themselves, so correctly recognizing people in VIP assisting apparatus provide great convenience. However, in classical face recognition technology, faces used in training and prediction procedures are usually frontal, and the procedures of acquiring face images require subjects to get close to the camera so that frontal face and illumination guaranteed. Meanwhile, labels of faces are defined manually rather than automatically. Most of the time, labels belonging to different classes need to be input one by one. It prevents assisting application for VIP with these constraints in practice. In this article, a face recognition system under unconstrained environment is proposed. Specifically, it doesn't require frontal pose or uniform illumination as required by previous algorithms. The attributes of this work lie in three aspects. First, a real time frontal-face synthesizing enhancement is implemented, and frontal faces help to increase recognition rate, which is proved with experiment results. Secondly, RGB-D camera plays a significant role in our system, from which both color and depth information are utilized to achieve real time face tracking which not only raises the detection rate but also gives an access to label faces automatically. Finally, we propose to use neural networks to train a face recognition system, and Principal Component Analysis (PCA) is applied to pre-refine the input data. This system is expected to provide convenient help for VIP to get familiar with others, and make an access for them to recognize people when the system is trained enough.

Alternative Packaging for Back-Illuminated Imagers

NASA Technical Reports Server (NTRS)

Pain, Bedabrata

2009-01-01

An alternative scheme has been conceived for packaging of silicon-based back-illuminated, back-side-thinned complementary metal oxide/semiconductor (CMOS) and charge-coupled-device image-detector integrated circuits, including an associated fabrication process. This scheme and process are complementary to those described in "Making a Back-Illuminated Imager With Back-Side Connections" (NPO-42839), NASA Tech Briefs, Vol. 32, No. 7 (July 2008), page 38. To avoid misunderstanding, it should be noted that in the terminology of imaging integrated circuits, "front side" or "back side" does not necessarily refer to the side that, during operation, faces toward or away from a source of light or other object to be imaged. Instead, "front side" signifies that side of a semiconductor substrate upon which the pixel pattern and the associated semiconductor devices and metal conductor lines are initially formed during fabrication, and "back side" signifies the opposite side. If the imager is of the type called "back-illuminated," then the back side is the one that faces an object to be imaged. Initially, a back-illuminated, back-side-thinned image-detector is fabricated with its back side bonded to a silicon handle wafer. At a subsequent stage of fabrication, the front side is bonded to a glass wafer (for mechanical support) and the silicon handle wafer is etched away to expose the back side. The frontside integrated circuitry includes metal input/output contact pads, which are rendered inaccessible by the bonding of the front side to the glass wafer. Hence, one of the main problems is to make the input/output contact pads accessible from the back side, which is ultimately to be the side accessible to the external world. The present combination of an alternative packaging scheme and associated fabrication process constitute a solution of the problem.

Individual differences in face-looking behavior generalize from the lab to the world.

PubMed

Peterson, Matthew F; Lin, Jing; Zaun, Ian; Kanwisher, Nancy

2016-05-01

Recent laboratory studies have found large, stable individual differences in the location people first fixate when identifying faces, ranging from the brows to the mouth. Importantly, this variation is strongly associated with differences in fixation-specific identification performance such that individuals' recognition ability is maximized when looking at their preferred location (Mehoudar, Arizpe, Baker, & Yovel, 2014; Peterson & Eckstein, 2013). This finding suggests that face representations are retinotopic and individuals enact gaze strategies that optimize identification, yet the extent to which this behavior reflects real-world gaze behavior is unknown. Here, we used mobile eye trackers to test whether individual differences in face gaze generalize from lab to real-world vision. In-lab fixations were measured with a speeded face identification task, while real-world behavior was measured as subjects freely walked around the Massachusetts Institute of Technology campus. We found a strong correlation between the patterns of individual differences in face gaze in the lab and real-world settings. Our findings support the hypothesis that individuals optimize real-world face identification by consistently fixating the same location and thus strongly constraining the space of retinotopic input. The methods developed for this study entailed collecting a large set of high-definition, wide field-of-view natural videos from head-mounted cameras and the viewer's fixation position, allowing us to characterize subjects' actually experienced real-world retinotopic images. These images enable us to ask how vision is optimized not just for the statistics of the "natural images" found in web databases, but of the truly natural, retinotopic images that have landed on actual human retinae during real-world experience.

Neural network-based system for pattern recognition through a fiber optic bundle

NASA Astrophysics Data System (ADS)

Gamo-Aranda, Javier; Rodriguez-Horche, Paloma; Merchan-Palacios, Miguel; Rosales-Herrera, Pablo; Rodriguez, M.

2001-04-01

A neural network based system to identify images transmitted through a Coherent Fiber-optic Bundle (CFB) is presented. Patterns are generated in a computer, displayed on a Spatial Light Modulator, imaged onto the input face of the CFB, and recovered optically by a CCD sensor array for further processing. Input and output optical subsystems were designed and used to that end. The recognition step of the transmitted patterns is made by a powerful, widely-used, neural network simulator running on the control PC. A complete PC-based interface was developed to control the different tasks involved in the system. An optical analysis of the system capabilities was carried out prior to performing the recognition step. Several neural network topologies were tested, and the corresponding numerical results are also presented and discussed.

Face recognition: a convolutional neural-network approach.

PubMed

Lawrence, S; Giles, C L; Tsoi, A C; Back, A D

1997-01-01

We present a hybrid neural-network for human face recognition which compares favourably with other methods. The system combines local image sampling, a self-organizing map (SOM) neural network, and a convolutional neural network. The SOM provides a quantization of the image samples into a topological space where inputs that are nearby in the original space are also nearby in the output space, thereby providing dimensionality reduction and invariance to minor changes in the image sample, and the convolutional neural network provides partial invariance to translation, rotation, scale, and deformation. The convolutional network extracts successively larger features in a hierarchical set of layers. We present results using the Karhunen-Loeve transform in place of the SOM, and a multilayer perceptron (MLP) in place of the convolutional network for comparison. We use a database of 400 images of 40 individuals which contains quite a high degree of variability in expression, pose, and facial details. We analyze the computational complexity and discuss how new classes could be added to the trained recognizer.

New nonlinear features for inspection, robotics, and face recognition

NASA Astrophysics Data System (ADS)

Casasent, David P.; Talukder, Ashit

1999-10-01

Classification of real-time X-ray images of randomly oriented touching pistachio nuts is discussed. The ultimate objective is the development of a system for automated non- invasive detection of defective product items on a conveyor belt. We discuss the extraction of new features that allow better discrimination between damaged and clean items (pistachio nuts). This feature extraction and classification stage is the new aspect of this paper; our new maximum representation and discriminating feature (MRDF) extraction method computes nonlinear features that are used as inputs to a new modified k nearest neighbor classifier. In this work, the MRDF is applied to standard features (rather than iconic data). The MRDF is robust to various probability distributions of the input class and is shown to provide good classification and new ROC (receiver operating characteristic) data. Other applications of these new feature spaces in robotics and face recognition are also noted.

Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor

PubMed Central

Nguyen, Dat Tien; Baek, Na Rae; Pham, Tuyen Danh; Park, Kang Ryoung

2018-01-01

Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD) method for an iris recognition system (iPAD) using a near infrared light (NIR) camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED). Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM). Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies. PMID:29695113

Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor.

PubMed

Nguyen, Dat Tien; Baek, Na Rae; Pham, Tuyen Danh; Park, Kang Ryoung

2018-04-24

Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD) method for an iris recognition system (iPAD) using a near infrared light (NIR) camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED). Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM). Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies.

A mixture of sparse coding models explaining properties of face neurons related to holistic and parts-based processing

PubMed Central

2017-01-01

Experimental studies have revealed evidence of both parts-based and holistic representations of objects and faces in the primate visual system. However, it is still a mystery how such seemingly contradictory types of processing can coexist within a single system. Here, we propose a novel theory called mixture of sparse coding models, inspired by the formation of category-specific subregions in the inferotemporal (IT) cortex. We developed a hierarchical network that constructed a mixture of two sparse coding submodels on top of a simple Gabor analysis. The submodels were each trained with face or non-face object images, which resulted in separate representations of facial parts and object parts. Importantly, evoked neural activities were modeled by Bayesian inference, which had a top-down explaining-away effect that enabled recognition of an individual part to depend strongly on the category of the whole input. We show that this explaining-away effect was indeed crucial for the units in the face submodel to exhibit significant selectivity to face images over object images in a similar way to actual face-selective neurons in the macaque IT cortex. Furthermore, the model explained, qualitatively and quantitatively, several tuning properties to facial features found in the middle patch of face processing in IT as documented by Freiwald, Tsao, and Livingstone (2009). These included, in particular, tuning to only a small number of facial features that were often related to geometrically large parts like face outline and hair, preference and anti-preference of extreme facial features (e.g., very large/small inter-eye distance), and reduction of the gain of feature tuning for partial face stimuli compared to whole face stimuli. Thus, we hypothesize that the coding principle of facial features in the middle patch of face processing in the macaque IT cortex may be closely related to mixture of sparse coding models. PMID:28742816

A mixture of sparse coding models explaining properties of face neurons related to holistic and parts-based processing.

PubMed

Hosoya, Haruo; Hyvärinen, Aapo

2017-07-01

Experimental studies have revealed evidence of both parts-based and holistic representations of objects and faces in the primate visual system. However, it is still a mystery how such seemingly contradictory types of processing can coexist within a single system. Here, we propose a novel theory called mixture of sparse coding models, inspired by the formation of category-specific subregions in the inferotemporal (IT) cortex. We developed a hierarchical network that constructed a mixture of two sparse coding submodels on top of a simple Gabor analysis. The submodels were each trained with face or non-face object images, which resulted in separate representations of facial parts and object parts. Importantly, evoked neural activities were modeled by Bayesian inference, which had a top-down explaining-away effect that enabled recognition of an individual part to depend strongly on the category of the whole input. We show that this explaining-away effect was indeed crucial for the units in the face submodel to exhibit significant selectivity to face images over object images in a similar way to actual face-selective neurons in the macaque IT cortex. Furthermore, the model explained, qualitatively and quantitatively, several tuning properties to facial features found in the middle patch of face processing in IT as documented by Freiwald, Tsao, and Livingstone (2009). These included, in particular, tuning to only a small number of facial features that were often related to geometrically large parts like face outline and hair, preference and anti-preference of extreme facial features (e.g., very large/small inter-eye distance), and reduction of the gain of feature tuning for partial face stimuli compared to whole face stimuli. Thus, we hypothesize that the coding principle of facial features in the middle patch of face processing in the macaque IT cortex may be closely related to mixture of sparse coding models.

Real-time observation of X-ray diffraction patterns with the Lixiscope

NASA Technical Reports Server (NTRS)

Chung, D. Y.; Tsang, T.; Yin, L. I.; Anderson, J. R.

1981-01-01

The feasibility of the Lixiscope (Low Intensity X-ray Imaging Scope) is demonstrated for real-time observation of transmission Laue patterns. Making use of the high-gain capability of microchannel plate (MCP) visible-light image intensifier tubes, X-ray images are converted to visible-light images by a scintillator. Pb discs are taped to the center of the Lixiscope input face, and crystal samples are held on a goniometer stage with modeling clay. With a compact size to facilitate off axis viewing, and real-time viewing to allow instantaneous response, the Lixiscope may prove useful in dynamic studies of the effects of plastic flows, stresses, high pressures, and low temperatures.

Cloud Offload in Hostile Environments

DTIC Science & Technology

2011-12-01

of recognized objects in an input image. FACE: Windows XP C++ application based on the OpenCV library [45]. It returns the coordinates and identities...SOLDIER. Energy-Efficient Technolo- gies for the Dismounted Soldier”. National Research Council, 1997. [16] COMMITTEE ON SOLDIER POWER/ENERGY SYSTEMS...vol. 4658 of Lecture Notes in Computer Science. Springer Berlin / Heidelberg, 2007. [45] OPENCV . OpenCV Wiki. http://opencv.willowgarage.com/wiki/. [46

LocalMove: computing on-lattice fits for biopolymers

PubMed Central

Ponty, Y.; Istrate, R.; Porcelli, E.; Clote, P.

2008-01-01

Given an input Protein Data Bank file (PDB) for a protein or RNA molecule, LocalMove is a web server that determines an on-lattice representation for the input biomolecule. The web server implements a Markov Chain Monte-Carlo algorithm with simulated annealing to compute an approximate fit for either the coarse-grain model or backbone model on either the cubic or face-centered cubic lattice. LocalMove returns a PDB file as output, as well as dynamic movie of 3D images of intermediate conformations during the computation. The LocalMove server is publicly available at http://bioinformatics.bc.edu/clotelab/localmove/. PMID:18556754

Face recognition via Gabor and convolutional neural network

NASA Astrophysics Data System (ADS)

Lu, Tongwei; Wu, Menglu; Lu, Tao

2018-04-01

In recent years, the powerful feature learning and classification ability of convolutional neural network have attracted widely attention. Compared with the deep learning, the traditional machine learning algorithm has a good explanatory which deep learning does not have. Thus, In this paper, we propose a method to extract the feature of the traditional algorithm as the input of convolution neural network. In order to reduce the complexity of the network, the kernel function of Gabor wavelet is used to extract the feature from different position, frequency and direction of target image. It is sensitive to edge of image which can provide good direction and scale selection. The extraction of the image from eight directions on a scale are as the input of network that we proposed. The network have the advantage of weight sharing and local connection and texture feature of the input image can reduce the influence of facial expression, gesture and illumination. At the same time, we introduced a layer which combined the results of the pooling and convolution can extract deeper features. The training network used the open source caffe framework which is beneficial to feature extraction. The experiment results of the proposed method proved that the network structure effectively overcame the barrier of illumination and had a good robustness as well as more accurate and rapid than the traditional algorithm.

Color preservation for tone reproduction and image enhancement

NASA Astrophysics Data System (ADS)

Hsin, Chengho; Lee, Zong Wei; Lee, Zheng Zhan; Shin, Shaw-Jyh

2014-01-01

Applications based on luminance processing often face the problem of recovering the original chrominance in the output color image. A common approach to reconstruct a color image from the luminance output is by preserving the original hue and saturation. However, this approach often produces a highly colorful image which is undesirable. We develop a color preservation method that not only retains the ratios of the input tri-chromatic values but also adjusts the output chroma in an appropriate way. Linearizing the output luminance is the key idea to realize this method. In addition, a lightness difference metric together with a colorfulness difference metric are proposed to evaluate the performance of the color preservation methods. It shows that the proposed method performs consistently better than the existing approaches.

Recognizing Action Units for Facial Expression Analysis

PubMed Central

Tian, Ying-li; Kanade, Takeo; Cohn, Jeffrey F.

2010-01-01

Most automatic expression analysis systems attempt to recognize a small set of prototypic expressions, such as happiness, anger, surprise, and fear. Such prototypic expressions, however, occur rather infrequently. Human emotions and intentions are more often communicated by changes in one or a few discrete facial features. In this paper, we develop an Automatic Face Analysis (AFA) system to analyze facial expressions based on both permanent facial features (brows, eyes, mouth) and transient facial features (deepening of facial furrows) in a nearly frontal-view face image sequence. The AFA system recognizes fine-grained changes in facial expression into action units (AUs) of the Facial Action Coding System (FACS), instead of a few prototypic expressions. Multistate face and facial component models are proposed for tracking and modeling the various facial features, including lips, eyes, brows, cheeks, and furrows. During tracking, detailed parametric descriptions of the facial features are extracted. With these parameters as the inputs, a group of action units (neutral expression, six upper face AUs and 10 lower face AUs) are recognized whether they occur alone or in combinations. The system has achieved average recognition rates of 96.4 percent (95.4 percent if neutral expressions are excluded) for upper face AUs and 96.7 percent (95.6 percent with neutral expressions excluded) for lower face AUs. The generalizability of the system has been tested by using independent image databases collected and FACS-coded for ground-truth by different research teams. PMID:25210210

Robust 3D face landmark localization based on local coordinate coding.

PubMed

Song, Mingli; Tao, Dacheng; Sun, Shengpeng; Chen, Chun; Maybank, Stephen J

2014-12-01

In the 3D facial animation and synthesis community, input faces are usually required to be labeled by a set of landmarks for parameterization. Because of the variations in pose, expression and resolution, automatic 3D face landmark localization remains a challenge. In this paper, a novel landmark localization approach is presented. The approach is based on local coordinate coding (LCC) and consists of two stages. In the first stage, we perform nose detection, relying on the fact that the nose shape is usually invariant under the variations in the pose, expression, and resolution. Then, we use the iterative closest points algorithm to find a 3D affine transformation that aligns the input face to a reference face. In the second stage, we perform resampling to build correspondences between the input 3D face and the training faces. Then, an LCC-based localization algorithm is proposed to obtain the positions of the landmarks in the input face. Experimental results show that the proposed method is comparable to state of the art methods in terms of its robustness, flexibility, and accuracy.

Visual attention: low-level and high-level viewpoints

NASA Astrophysics Data System (ADS)

Stentiford, Fred W. M.

2012-06-01

This paper provides a brief outline of the approaches to modeling human visual attention. Bottom-up and top-down mechanisms are described together with some of the problems that they face. It has been suggested in brain science that memory functions by trading measurement precision for associative power; sensory inputs from the environment are never identical on separate occasions, but the associations with memory compensate for the differences. A graphical representation for image similarity is described that relies on the size of maximally associative structures (cliques) that are found to reflect between pairs of images. This is applied to the recognition of movie posters, the location and recognition of characters, and the recognition of faces. The similarity mechanism is shown to model popout effects when constraints are placed on the physical separation of pixels that correspond to nodes in the maximal cliques. The effect extends to modeling human visual behaviour on the Poggendorff illusion.

Neuronal responses to face-like stimuli in the monkey pulvinar.

PubMed

Nguyen, Minh Nui; Hori, Etsuro; Matsumoto, Jumpei; Tran, Anh Hai; Ono, Taketoshi; Nishijo, Hisao

2013-01-01

The pulvinar nuclei appear to function as the subcortical visual pathway that bypasses the striate cortex, rapidly processing coarse facial information. We investigated responses from monkey pulvinar neurons during a delayed non-matching-to-sample task, in which monkeys were required to discriminate five categories of visual stimuli [photos of faces with different gaze directions, line drawings of faces, face-like patterns (three dark blobs on a bright oval), eye-like patterns and simple geometric patterns]. Of 401 neurons recorded, 165 neurons responded differentially to the visual stimuli. These visual responses were suppressed by scrambling the images. Although these neurons exhibited a broad response latency distribution, face-like patterns elicited responses with the shortest latencies (approximately 50 ms). Multidimensional scaling analysis indicated that the pulvinar neurons could specifically encode face-like patterns during the first 50-ms period after stimulus onset and classify the stimuli into one of the five different categories during the next 50-ms period. The amount of stimulus information conveyed by the pulvinar neurons and the number of stimulus-differentiating neurons were consistently higher during the second 50-ms period than during the first 50-ms period. These results suggest that responsiveness to face-like patterns during the first 50-ms period might be attributed to ascending inputs from the superior colliculus or the retina, while responsiveness to the five different stimulus categories during the second 50-ms period might be mediated by descending inputs from cortical regions. These findings provide neurophysiological evidence for pulvinar involvement in social cognition and, specifically, rapid coarse facial information processing. © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

VASIR: An Open-Source Research Platform for Advanced Iris Recognition Technologies.

PubMed

Lee, Yooyoung; Micheals, Ross J; Filliben, James J; Phillips, P Jonathon

2013-01-01

The performance of iris recognition systems is frequently affected by input image quality, which in turn is vulnerable to less-than-optimal conditions due to illuminations, environments, and subject characteristics (e.g., distance, movement, face/body visibility, blinking, etc.). VASIR (Video-based Automatic System for Iris Recognition) is a state-of-the-art NIST-developed iris recognition software platform designed to systematically address these vulnerabilities. We developed VASIR as a research tool that will not only provide a reference (to assess the relative performance of alternative algorithms) for the biometrics community, but will also advance (via this new emerging iris recognition paradigm) NIST's measurement mission. VASIR is designed to accommodate both ideal (e.g., classical still images) and less-than-ideal images (e.g., face-visible videos). VASIR has three primary modules: 1) Image Acquisition 2) Video Processing, and 3) Iris Recognition. Each module consists of several sub-components that have been optimized by use of rigorous orthogonal experiment design and analysis techniques. We evaluated VASIR performance using the MBGC (Multiple Biometric Grand Challenge) NIR (Near-Infrared) face-visible video dataset and the ICE (Iris Challenge Evaluation) 2005 still-based dataset. The results showed that even though VASIR was primarily developed and optimized for the less-constrained video case, it still achieved high verification rates for the traditional still-image case. For this reason, VASIR may be used as an effective baseline for the biometrics community to evaluate their algorithm performance, and thus serves as a valuable research platform.

VASIR: An Open-Source Research Platform for Advanced Iris Recognition Technologies

PubMed Central

Lee, Yooyoung; Micheals, Ross J; Filliben, James J; Phillips, P Jonathon

2013-01-01

The performance of iris recognition systems is frequently affected by input image quality, which in turn is vulnerable to less-than-optimal conditions due to illuminations, environments, and subject characteristics (e.g., distance, movement, face/body visibility, blinking, etc.). VASIR (Video-based Automatic System for Iris Recognition) is a state-of-the-art NIST-developed iris recognition software platform designed to systematically address these vulnerabilities. We developed VASIR as a research tool that will not only provide a reference (to assess the relative performance of alternative algorithms) for the biometrics community, but will also advance (via this new emerging iris recognition paradigm) NIST’s measurement mission. VASIR is designed to accommodate both ideal (e.g., classical still images) and less-than-ideal images (e.g., face-visible videos). VASIR has three primary modules: 1) Image Acquisition 2) Video Processing, and 3) Iris Recognition. Each module consists of several sub-components that have been optimized by use of rigorous orthogonal experiment design and analysis techniques. We evaluated VASIR performance using the MBGC (Multiple Biometric Grand Challenge) NIR (Near-Infrared) face-visible video dataset and the ICE (Iris Challenge Evaluation) 2005 still-based dataset. The results showed that even though VASIR was primarily developed and optimized for the less-constrained video case, it still achieved high verification rates for the traditional still-image case. For this reason, VASIR may be used as an effective baseline for the biometrics community to evaluate their algorithm performance, and thus serves as a valuable research platform. PMID:26401431

Multimodal ophthalmic imaging using handheld spectrally encoded coherence tomography and reflectometry (SECTR)

NASA Astrophysics Data System (ADS)

Leeburg, Kelsey C.; El-Haddad, Mohamed T.; Malone, Joseph D.; Terrones, Benjamin D.; Tao, Yuankai K.

2018-02-01

Scanning laser ophthalmoscopy (SLO) provides high-speed, noninvasive en face imaging of the retinal fundus. Optical coherence tomography (OCT) is the current "gold-standard" for ophthalmic diagnostic imaging and enables depth-resolved visualization of ophthalmic structures and image-based surrogate biomarkers of disease. We present a compact optical and mechanical design for handheld spectrally encoded coherence tomography and reflectometry (SECTR) for multimodality en face spectrally encoded reflectometry (SER) and cross-sectional OCT imaging. We custom-designed a double-pass telecentric scan lens, which halves the size of 4-f optical relays and allowed us to reduce the footprint of our SECTR scan-head by a factor of >2.7x (volume) over our previous design. The double-pass scan lens was optimized for diffraction-limited performance over a +/-10° scan field. SECTR optics and optomechanics were combined in a compact rapid-prototyped enclosure with dimensions 87 x 141.8 x 137 mm (w x h x d). SECTR was implemented using a custom-built 400 kHz 1050 nm swept-source. OCT and SER were simultaneously digitized on dual input channels of a 4 GS/s digitizer at 1.4 GS/s per channel. In vivo human en face SER and cross-sectional OCT images were acquired at 350 fps. OCT volumes of 1000 B-scans were acquired in 2.86 s. We believe clinical translation of our compact handheld design will benefit point-of-care ophthalmic diagnostics in patients who are unable to be imaged on conventional slit-lamp based systems, such as infants and the bedridden. When combined with multi-volumetric registration methods, handheld SECTR will have advantages in motion-artifact free imaging over existing handheld technologies.

Optimized face recognition algorithm using radial basis function neural networks and its practical applications.

PubMed

Yoo, Sung-Hoon; Oh, Sung-Kwun; Pedrycz, Witold

2015-09-01

In this study, we propose a hybrid method of face recognition by using face region information extracted from the detected face region. In the preprocessing part, we develop a hybrid approach based on the Active Shape Model (ASM) and the Principal Component Analysis (PCA) algorithm. At this step, we use a CCD (Charge Coupled Device) camera to acquire a facial image by using AdaBoost and then Histogram Equalization (HE) is employed to improve the quality of the image. ASM extracts the face contour and image shape to produce a personal profile. Then we use a PCA method to reduce dimensionality of face images. In the recognition part, we consider the improved Radial Basis Function Neural Networks (RBF NNs) to identify a unique pattern associated with each person. The proposed RBF NN architecture consists of three functional modules realizing the condition phase, the conclusion phase, and the inference phase completed with the help of fuzzy rules coming in the standard 'if-then' format. In the formation of the condition part of the fuzzy rules, the input space is partitioned with the use of Fuzzy C-Means (FCM) clustering. In the conclusion part of the fuzzy rules, the connections (weights) of the RBF NNs are represented by four kinds of polynomials such as constant, linear, quadratic, and reduced quadratic. The values of the coefficients are determined by running a gradient descent method. The output of the RBF NNs model is obtained by running a fuzzy inference method. The essential design parameters of the network (including learning rate, momentum coefficient and fuzzification coefficient used by the FCM) are optimized by means of Differential Evolution (DE). The proposed P-RBF NNs (Polynomial based RBF NNs) are applied to facial recognition and its performance is quantified from the viewpoint of the output performance and recognition rate. Copyright © 2015 Elsevier Ltd. All rights reserved.

Face processing pattern under top-down perception: a functional MRI study

NASA Astrophysics Data System (ADS)

Li, Jun; Liang, Jimin; Tian, Jie; Liu, Jiangang; Zhao, Jizheng; Zhang, Hui; Shi, Guangming

2009-02-01

Although top-down perceptual process plays an important role in face processing, its neural substrate is still puzzling because the top-down stream is extracted difficultly from the activation pattern associated with contamination caused by bottom-up face perception input. In the present study, a novel paradigm of instructing participants to detect faces from pure noise images is employed, which could efficiently eliminate the interference of bottom-up face perception in topdown face processing. Analyzing the map of functional connectivity with right FFA analyzed by conventional Pearson's correlation, a possible face processing pattern induced by top-down perception can be obtained. Apart from the brain areas of bilateral fusiform gyrus (FG), left inferior occipital gyrus (IOG) and left superior temporal sulcus (STS), which are consistent with a core system in the distributed cortical network for face perception, activation induced by top-down face processing is also found in these regions that include the anterior cingulate gyrus (ACC), right oribitofrontal cortex (OFC), left precuneus, right parahippocampal cortex, left dorsolateral prefrontal cortex (DLPFC), right frontal pole, bilateral premotor cortex, left inferior parietal cortex and bilateral thalamus. The results indicate that making-decision, attention, episodic memory retrieving and contextual associative processing network cooperate with general face processing regions to process face information under top-down perception.

Edge smoothing for real-time simulation of a polygon face object system as viewed by a moving observer

NASA Technical Reports Server (NTRS)

Lotz, Robert W. (Inventor); Westerman, David J. (Inventor)

1980-01-01

The visual system within an aircraft flight simulation system receives flight data and terrain data which is formated into a buffer memory. The image data is forwarded to an image processor which translates the image data into face vertex vectors Vf, defining the position relationship between the vertices of each terrain object and the aircraft. The image processor then rotates, clips, and projects the image data into two-dimensional display vectors (Vd). A display generator receives the Vd faces, and other image data to provide analog inputs to CRT devices which provide the window displays for the simulated aircraft. The video signal to the CRT devices passes through an edge smoothing device which prolongs the rise time (and fall time) of the video data inversely as the slope of the edge being smoothed. An operational amplifier within the edge smoothing device has a plurality of independently selectable feedback capacitors each having a different value. The values of the capacitors form a series which doubles as a power of two. Each feedback capacitor has a fast switch responsive to the corresponding bit of a digital binary control word for selecting (1) or not selecting (0) that capacitor. The control word is determined by the slope of each edge. The resulting actual feedback capacitance for each edge is the sum of all the selected capacitors and is directly proportional to the value of the binary control word. The output rise time (or fall time) is a function of the feedback capacitance, and is controlled by the slope through the binary control word.

Real-time camera-based face detection using a modified LAMSTAR neural network system

NASA Astrophysics Data System (ADS)

Girado, Javier I.; Sandin, Daniel J.; DeFanti, Thomas A.; Wolf, Laura K.

2003-03-01

This paper describes a cost-effective, real-time (640x480 at 30Hz) upright frontal face detector as part of an ongoing project to develop a video-based, tetherless 3D head position and orientation tracking system. The work is specifically targeted for auto-stereoscopic displays and projection-based virtual reality systems. The proposed face detector is based on a modified LAMSTAR neural network system. At the input stage, after achieving image normalization and equalization, a sub-window analyzes facial features using a neural network. The sub-window is segmented, and each part is fed to a neural network layer consisting of a Kohonen Self-Organizing Map (SOM). The output of the SOM neural networks are interconnected and related by correlation-links, and can hence determine the presence of a face with enough redundancy to provide a high detection rate. To avoid tracking multiple faces simultaneously, the system is initially trained to track only the face centered in a box superimposed on the display. The system is also rotationally and size invariant to a certain degree.

Depth of treatment sensitive noise resistant dynamic artificial neural networks model of recall in people with prosopagnosia.

PubMed

Morissette, Laurence; Chartier, Sylvain; Vandermeulen, Robyn; Watier, Nicholas

2012-08-01

The Fusiform Face Area (FFA) is the brain region considered to be responsible for face recognition. Prosopagnosia is a brain disorder causing the inability to a recognise faces that is said to mainly affect the FFA. We put forward a model that simulates the capacity to retrieve label associated with faces and objects depending on the depth of treatment of the information. Akin to prosopagnosia, various localised "lesions" were inserted into the network in order to evaluate the degradation of performance. The network is first composed of a Feature Extracting Bidirectional Associative Memory (FEBAM-SOM) to represent the topological maps allowing the categorisation of all faces. The second component of the network is a Bidirectional Heteroassociative Memory (BHM) that links those representations to their semantic label. For the latter, specific semantic labels were used as well as more general ones. The inputs were images representing faces and various objects. Just like in the visual perceptual system, the images were pre-processed using a low-pass filter. Results showed that the network is able to associate the extracted map with the correct label information. The network is able to generalise and is robust to noise. Moreover, results showed that the recall performance of names associated with faces decrease with the size of lesion without affecting the performance of the objects. Finally, results obtained with the network are also consistent with human ones in that higher level, more general labels are more robust to lesion compared to low level, specific labels. Copyright © 2012 Elsevier Ltd. All rights reserved.

Image super-resolution via sparse representation.

PubMed

Yang, Jianchao; Wright, John; Huang, Thomas S; Ma, Yi

2010-11-01

This paper presents a new approach to single-image super-resolution, based on sparse signal representation. Research on image statistics suggests that image patches can be well-represented as a sparse linear combination of elements from an appropriately chosen over-complete dictionary. Inspired by this observation, we seek a sparse representation for each patch of the low-resolution input, and then use the coefficients of this representation to generate the high-resolution output. Theoretical results from compressed sensing suggest that under mild conditions, the sparse representation can be correctly recovered from the downsampled signals. By jointly training two dictionaries for the low- and high-resolution image patches, we can enforce the similarity of sparse representations between the low resolution and high resolution image patch pair with respect to their own dictionaries. Therefore, the sparse representation of a low resolution image patch can be applied with the high resolution image patch dictionary to generate a high resolution image patch. The learned dictionary pair is a more compact representation of the patch pairs, compared to previous approaches, which simply sample a large amount of image patch pairs, reducing the computational cost substantially. The effectiveness of such a sparsity prior is demonstrated for both general image super-resolution and the special case of face hallucination. In both cases, our algorithm generates high-resolution images that are competitive or even superior in quality to images produced by other similar SR methods. In addition, the local sparse modeling of our approach is naturally robust to noise, and therefore the proposed algorithm can handle super-resolution with noisy inputs in a more unified framework.

Visual processing in anorexia nervosa and body dysmorphic disorder: similarities, differences, and future research directions

PubMed Central

Madsen, Sarah K.; Bohon, Cara; Feusner, Jamie D.

2013-01-01

Anorexia nervosa (AN) and body dysmorphic disorder (BDD) are psychiatric disorders that involve distortion of the experience of one’s physical appearance. In AN, individuals believe that they are overweight, perceive their body as “fat,” and are preoccupied with maintaining a low body weight. In BDD, individuals are preoccupied with misperceived defects in physical appearance, most often of the face. Distorted visual perception may contribute to these cardinal symptoms, and may be a common underlying phenotype. This review surveys the current literature on visual processing in AN and BDD, addressing lower- to higher-order stages of visual information processing and perception. We focus on peer-reviewed studies of AN and BDD that address ophthalmologic abnormalities, basic neural processing of visual input, integration of visual input with other systems, neuropsychological tests of visual processing, and representations of whole percepts (such as images of faces, bodies, and other objects). The literature suggests a pattern in both groups of over-attention to detail, reduced processing of global features, and a tendency to focus on symptom-specific details in their own images (body parts in AN, facial features in BDD), with cognitive strategy at least partially mediating the abnormalities. Visuospatial abnormalities were also evident when viewing images of others and for non-appearance related stimuli. Unfortunately no study has directly compared AN and BDD, and most studies were not designed to disentangle disease-related emotional responses from lower-order visual processing. We make recommendations for future studies to improve the understanding of visual processing abnormalities in AN and BDD. PMID:23810196

Neurocomputational bases of object and face recognition.

PubMed Central

Biederman, I; Kalocsai, P

1997-01-01

A number of behavioural phenomena distinguish the recognition of faces and objects, even when members of a set of objects are highly similar. Because faces have the same parts in approximately the same relations, individuation of faces typically requires specification of the metric variation in a holistic and integral representation of the facial surface. The direct mapping of a hypercolumn-like pattern of activation onto a representation layer that preserves relative spatial filter values in a two-dimensional (2D) coordinate space, as proposed by C. von der Malsburg and his associates, may account for many of the phenomena associated with face recognition. An additional refinement, in which each column of filters (termed a 'jet') is centred on a particular facial feature (or fiducial point), allows selectivity of the input into the holistic representation to avoid incorporation of occluding or nearby surfaces. The initial hypercolumn representation also characterizes the first stage of object perception, but the image variation for objects at a given location in a 2D coordinate space may be too great to yield sufficient predictability directly from the output of spatial kernels. Consequently, objects can be represented by a structural description specifying qualitative (typically, non-accidental) characterizations of an object's parts, the attributes of the parts, and the relations among the parts, largely based on orientation and depth discontinuities (as shown by Hummel & Biederman). A series of experiments on the name priming or physical matching of complementary images (in the Fourier domain) of objects and faces documents that whereas face recognition is strongly dependent on the original spatial filter values, evidence from object recognition indicates strong invariance to these values, even when distinguishing among objects that are as similar as faces. PMID:9304687

Evidence for Working Memory Storage Operations in Perceptual Cortex

PubMed Central

Sreenivasan, Kartik K.; Gratton, Caterina; Vytlacil, Jason; D’Esposito, Mark

2014-01-01

Isolating the short-term storage component of working memory (WM) from the myriad of associated executive processes has been an enduring challenge. Recent efforts have identified patterns of activity in visual regions that contain information about items being held in WM. However, it remains unclear (i) whether these representations withstand intervening sensory input and (ii) how communication between multimodal association cortex and unimodal perceptual regions supporting WM representations is involved in WM storage. We present evidence that the features of a face held in WM are stored within face processing regions, that these representations persist across subsequent sensory input, and that information about the match between sensory input and memory representation is relayed forward from perceptual to prefrontal regions. Participants were presented with a series of probe faces and indicated whether each probe matched a Target face held in WM. We parametrically varied the feature similarity between probe and Target faces. Activity within face processing regions scaled linearly with the degree of feature similarity between the probe face and the features of the Target face, suggesting that the features of the Target face were stored in these regions. Furthermore, directed connectivity measures revealed that the direction of information flow that was optimal for performance was from sensory regions that stored the features of the Target face to dorsal prefrontal regions, supporting the notion that sensory input is compared to representations stored within perceptual regions and relayed forward. Together, these findings indicate that WM storage operations are carried out within perceptual cortex. PMID:24436009

Constructing a safety and security system by medical applications of a fast face recognition optical parallel correlator

NASA Astrophysics Data System (ADS)

Watanabe, Eriko; Ishikawa, Mami; Ohta, Maiko; Murakami, Yasuo; Kodate, Kashiko

2006-01-01

Medical errors and patient safety have always received a great deal of attention, as they can be critically life-threatening and significant matters. Hospitals and medical personnel are trying their utmost to avoid these errors. Currently in the medical field, patients' record is identified through their PIN numbers and ID cards. However, for patients who cannot speak or move, or who suffer from memory disturbances, alternative methods would be more desirable, and necessary in some cases. The authors previously proposed and fabricated a specially-designed correlator called FARCO (Fast Face Recognition Optical Correlator) based on the Vanderlugt Correlator1, which operates at the speed of 1000 faces/s 2,3,4. Combined with high-speed display devices, the four-channel processing could achieve such high operational speed as 4000 faces/s. Running trial experiments on a 1-to-N identification basis using the optical parallel correlator, we succeeded in acquiring low error rates of 1 % FMR and 2.3 % FNMR. In this paper, we propose a robust face recognition system using the FARCO for focusing on the safety and security of the medical field. We apply our face recognition system to registration of inpatients, in particular children and infants, before and after medical treatments or operations. The proposed system has recorded a higher recognition rate by multiplexing both input and database facial images from moving images. The system was also tested and evaluated for further practical use, leaving excellent results. Hence, our face recognition system could function effectively as an integral part of medical system, meeting these essential requirements of safety, security and privacy.

The Face-Processing Network Is Resilient to Focal Resection of Human Visual Cortex

PubMed Central

Jonas, Jacques; Gomez, Jesse; Maillard, Louis; Brissart, Hélène; Hossu, Gabriela; Jacques, Corentin; Loftus, David; Colnat-Coulbois, Sophie; Stigliani, Anthony; Barnett, Michael A.; Grill-Spector, Kalanit; Rossion, Bruno

2016-01-01

Human face perception requires a network of brain regions distributed throughout the occipital and temporal lobes with a right hemisphere advantage. Present theories consider this network as either a processing hierarchy beginning with the inferior occipital gyrus (occipital face area; IOG-faces/OFA) or a multiple-route network with nonhierarchical components. The former predicts that removing IOG-faces/OFA will detrimentally affect downstream stages, whereas the latter does not. We tested this prediction in a human patient (Patient S.P.) requiring removal of the right inferior occipital cortex, including IOG-faces/OFA. We acquired multiple fMRI measurements in Patient S.P. before and after a preplanned surgery and multiple measurements in typical controls, enabling both within-subject/across-session comparisons (Patient S.P. before resection vs Patient S.P. after resection) and between-subject/across-session comparisons (Patient S.P. vs controls). We found that the spatial topology and selectivity of downstream ipsilateral face-selective regions were stable 1 and 8 month(s) after surgery. Additionally, the reliability of distributed patterns of face selectivity in Patient S.P. before versus after resection was not different from across-session reliability in controls. Nevertheless, postoperatively, representations of visual space were typical in dorsal face-selective regions but atypical in ventral face-selective regions and V1 of the resected hemisphere. Diffusion weighted imaging in Patient S.P. and controls identifies white matter tracts connecting retinotopic areas to downstream face-selective regions, which may contribute to the stable and plastic features of the face network in Patient S.P. after surgery. Together, our results support a multiple-route network of face processing with nonhierarchical components and shed light on stable and plastic features of high-level visual cortex following focal brain damage. SIGNIFICANCE STATEMENT Brain networks consist of interconnected functional regions commonly organized in processing hierarchies. Prevailing theories predict that damage to the input of the hierarchy will detrimentally affect later stages. We tested this prediction with multiple brain measurements in a rare human patient requiring surgical removal of the putative input to a network processing faces. Surprisingly, the spatial topology and selectivity of downstream face-selective regions are stable after surgery. Nevertheless, representations of visual space were typical in dorsal face-selective regions but atypical in ventral face-selective regions and V1. White matter connections from outside the face network may support these stable and plastic features. As processing hierarchies are ubiquitous in biological and nonbiological systems, our results have pervasive implications for understanding the construction of resilient networks. PMID:27511014

Qualitatively similar processing for own- and other-race faces: Evidence from efficiency and equivalent input noise.

PubMed

Shafai, Fakhri; Oruc, Ipek

2018-02-01

The other-race effect is the finding of diminished performance in recognition of other-race faces compared to those of own-race. It has been suggested that the other-race effect stems from specialized expert processes being tuned exclusively to own-race faces. In the present study, we measured recognition contrast thresholds for own- and other-race faces as well as houses for Caucasian observers. We have factored face recognition performance into two invariant aspects of visual function: efficiency, which is related to neural computations and processing demanded by the task, and equivalent input noise, related to signal degradation within the visual system. We hypothesized that if expert processes are available only to own-race faces, this should translate into substantially greater recognition efficiencies for own-race compared to other-race faces. Instead, we found similar recognition efficiencies for both own- and other-race faces. The other-race effect manifested as increased equivalent input noise. These results argue against qualitatively distinct perceptual processes. Instead they suggest that for Caucasian observers, similar neural computations underlie recognition of own- and other-race faces. Copyright © 2018 Elsevier Ltd. All rights reserved.

Motion video compression system with neural network having winner-take-all function

NASA Technical Reports Server (NTRS)

Fang, Wai-Chi (Inventor); Sheu, Bing J. (Inventor)

1997-01-01

A motion video data system includes a compression system, including an image compressor, an image decompressor correlative to the image compressor having an input connected to an output of the image compressor, a feedback summing node having one input connected to an output of the image decompressor, a picture memory having an input connected to an output of the feedback summing node, apparatus for comparing an image stored in the picture memory with a received input image and deducing therefrom pixels having differences between the stored image and the received image and for retrieving from the picture memory a partial image including the pixels only and applying the partial image to another input of the feedback summing node, whereby to produce at the output of the feedback summing node an updated decompressed image, a subtraction node having one input connected to received the received image and another input connected to receive the partial image so as to generate a difference image, the image compressor having an input connected to receive the difference image whereby to produce a compressed difference image at the output of the image compressor.

Permutation coding technique for image recognition systems.

PubMed

Kussul, Ernst M; Baidyk, Tatiana N; Wunsch, Donald C; Makeyev, Oleksandr; Martín, Anabel

2006-11-01

A feature extractor and neural classifier for image recognition systems are proposed. The proposed feature extractor is based on the concept of random local descriptors (RLDs). It is followed by the encoder that is based on the permutation coding technique that allows to take into account not only detected features but also the position of each feature on the image and to make the recognition process invariant to small displacements. The combination of RLDs and permutation coding permits us to obtain a sufficiently general description of the image to be recognized. The code generated by the encoder is used as an input data for the neural classifier. Different types of images were used to test the proposed image recognition system. It was tested in the handwritten digit recognition problem, the face recognition problem, and the microobject shape recognition problem. The results of testing are very promising. The error rate for the Modified National Institute of Standards and Technology (MNIST) database is 0.44% and for the Olivetti Research Laboratory (ORL) database it is 0.1%.

Pattern-Recognition Processor Using Holographic Photopolymer

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Cammack, Kevin

2006-01-01

proposed joint-transform optical correlator (JTOC) would be capable of operating as a real-time pattern-recognition processor. The key correlation-filter reading/writing medium of this JTOC would be an updateable holographic photopolymer. The high-resolution, high-speed characteristics of this photopolymer would enable pattern-recognition processing to occur at a speed three orders of magnitude greater than that of state-of-the-art digital pattern-recognition processors. There are many potential applications in biometric personal identification (e.g., using images of fingerprints and faces) and nondestructive industrial inspection. In order to appreciate the advantages of the proposed JTOC, it is necessary to understand the principle of operation of a conventional JTOC. In a conventional JTOC (shown in the upper part of the figure), a collimated laser beam passes through two side-by-side spatial light modulators (SLMs). One SLM displays a real-time input image to be recognized. The other SLM displays a reference image from a digital memory. A Fourier-transform lens is placed at its focal distance from the SLM plane, and a charge-coupled device (CCD) image detector is placed at the back focal plane of the lens for use as a square-law recorder. Processing takes place in two stages. In the first stage, the CCD records the interference pattern between the Fourier transforms of the input and reference images, and the pattern is then digitized and saved in a buffer memory. In the second stage, the reference SLM is turned off and the interference pattern is fed back to the input SLM. The interference pattern thus becomes Fourier-transformed, yielding at the CCD an image representing the joint-transform correlation between the input and reference images. This image contains a sharp correlation peak when the input and reference images are matched. The drawbacks of a conventional JTOC are the following: The CCD has low spatial resolution and is not an ideal square-law detector for the purpose of holographic recording of interference fringes. A typical state-of-the-art CCD has a pixel-pitch limited resolution of about 100 lines/mm. In contrast, the holographic photopolymer to be used in the proposed JTOC offers a resolution > 2,000 lines/mm. In addition to being disadvantageous in itself, the low resolution of the CCD causes overlap of a DC term and the desired correlation term in the output image. This overlap severely limits the correlation signal-to-noise ratio. The two-stage nature of the process limits the achievable throughput rate. A further limit is imposed by the low frame rate (typical video rates) of low- and medium-cost commercial CCDs.

Simulation of talking faces in the human brain improves auditory speech recognition

PubMed Central

von Kriegstein, Katharina; Dogan, Özgür; Grüter, Martina; Giraud, Anne-Lise; Kell, Christian A.; Grüter, Thomas; Kleinschmidt, Andreas; Kiebel, Stefan J.

2008-01-01

Human face-to-face communication is essentially audiovisual. Typically, people talk to us face-to-face, providing concurrent auditory and visual input. Understanding someone is easier when there is visual input, because visual cues like mouth and tongue movements provide complementary information about speech content. Here, we hypothesized that, even in the absence of visual input, the brain optimizes both auditory-only speech and speaker recognition by harvesting speaker-specific predictions and constraints from distinct visual face-processing areas. To test this hypothesis, we performed behavioral and neuroimaging experiments in two groups: subjects with a face recognition deficit (prosopagnosia) and matched controls. The results show that observing a specific person talking for 2 min improves subsequent auditory-only speech and speaker recognition for this person. In both prosopagnosics and controls, behavioral improvement in auditory-only speech recognition was based on an area typically involved in face-movement processing. Improvement in speaker recognition was only present in controls and was based on an area involved in face-identity processing. These findings challenge current unisensory models of speech processing, because they show that, in auditory-only speech, the brain exploits previously encoded audiovisual correlations to optimize communication. We suggest that this optimization is based on speaker-specific audiovisual internal models, which are used to simulate a talking face. PMID:18436648

Optical device with conical input and output prism faces

DOEpatents

Brunsden, Barry S.

1981-01-01

A device for radially translating radiation in which a right circular cylinder is provided at each end thereof with conical prism faces. The faces are oppositely extending and the device may be severed in the middle and separated to allow access to the central part of the beam. Radiation entering the input end of the device is radially translated such that radiation entering the input end at the perimeter is concentrated toward the output central axis and radiation at the input central axis is dispersed toward the output perimeter. Devices are disclosed for compressing beam energy to enhance drilling techniques, for beam manipulation of optical spatial frequencies in the Fourier plane and for simplification of dark field and color contrast microscopy. Both refracting and reflecting devices are disclosed.

Neural correlates of own- and other-race face perception: spatial and temporal response differences.

PubMed

Natu, Vaidehi; Raboy, David; O'Toole, Alice J

2011-02-01

Humans show an "other-race effect" for face recognition, with more accurate recognition of own- versus other-race faces. We compared the neural representations of own- and other-race faces using functional magnetic resonance imaging (fMRI) data in combination with a multi-voxel pattern classifier. Neural activity was recorded while Asians and Caucasians viewed Asian and Caucasian faces. A pattern classifier, applied to voxels across a broad range of ventral temporal areas, discriminated the brain activity maps elicited in response to Asian versus Caucasian faces in the brains of both Asians and Caucasians. Classification was most accurate in the first few time points of the block and required the use of own-race faces in the localizer scan to select voxels for classifier input. Next, we examined differences in the time-course of neural responses to own- and other-race faces and found evidence for a temporal "other-race effect." Own-race faces elicited a larger neural response initially that attenuated rapidly. The response to other-race faces was weaker at first, but increased over time, ultimately surpassing the magnitude of the own-race response in the fusiform "face" area (FFA). A similar temporal response pattern held across a broad range of ventral temporal areas. The pattern-classification results indicate the early availability of categorical information about own- versus other-race face status in the spatial pattern of neural activity. The slower, more sustained, brain response to other-race faces may indicate the need to recruit additional neural resources to process other-race faces for identification. Copyright © 2010 Elsevier Inc. All rights reserved.

Multimodal swept-source spectrally encoded scanning laser ophthalmoscopy and optical coherence tomography at 400 kHz

NASA Astrophysics Data System (ADS)

El-Haddad, Mohamed T.; Joos, Karen M.; Patel, Shriji N.; Tao, Yuankai K.

2017-02-01

Multimodal imaging systems that combine scanning laser ophthalmoscopy (SLO) and optical coherence tomography (OCT) have demonstrated the utility of concurrent en face and volumetric imaging for aiming, eye tracking, bulk motion compensation, mosaicking, and contrast enhancement. However, this additional functionality trades off with increased system complexity and cost because both SLO and OCT generally require dedicated light sources, galvanometer scanners, relay and imaging optics, detectors, and control and digitization electronics. We previously demonstrated multimodal ophthalmic imaging using swept-source spectrally encoded SLO and OCT (SS-SESLO-OCT). Here, we present system enhancements and a new optical design that increase our SS-SESLO-OCT data throughput by >7x and field-of-view (FOV) by >4x. A 200 kHz 1060 nm Axsun swept-source was optically buffered to 400 kHz sweep-rate, and SESLO and OCT were simultaneously digitized on dual input channels of a 4 GS/s digitizer at 1.2 GS/s per channel using a custom k-clock. We show in vivo human imaging of the anterior segment out to the limbus and retinal fundus over a >40° FOV. In addition, nine overlapping volumetric SS-SESLO-OCT volumes were acquired under video-rate SESLO preview and guidance. In post-processing, all nine SESLO images and en face projections of the corresponding OCT volumes were mosaicked to show widefield multimodal fundus imaging with a >80° FOV. Concurrent multimodal SS-SESLO-OCT may have applications in clinical diagnostic imaging by enabling aiming, image registration, and multi-field mosaicking and benefit intraoperative imaging by allowing for real-time surgical feedback, instrument tracking, and overlays of computationally extracted image-based surrogate biomarkers of disease.

Children with autism spectrum disorder (ASD) attend typically to faces and objects presented within their picture communication systems.

PubMed

Gillespie-Smith, K; Riby, D M; Hancock, P J B; Doherty-Sneddon, G

2014-05-01

Children with autism spectrum disorder (ASD) may require interventions for communication difficulties. One type of intervention is picture communication symbols which are proposed to improve comprehension of linguistic input for children with ASD. However, atypical attention to faces and objects is widely reported across the autism spectrum for several types of stimuli. In this study we used eye-tracking methodology to explore fixation duration and time taken to fixate on the object and face areas within picture communication symbols. Twenty-one children with ASD were compared with typically developing matched groups. Children with ASD were shown to have similar fixation patterns on face and object areas compared with typically developing matched groups. It is proposed that children with ASD attend to the images in a manner that does not differentiate them from typically developing individuals. Therefore children with and without autism have the same opportunity to encode the available information. We discuss what this may imply for interventions using picture symbols. © 2013 The Authors. Journal of Intellectual Disability Research © 2013 John Wiley & Sons Ltd, MENCAP & IASSIDD.

BrainIACS: a system for web-based medical image processing

NASA Astrophysics Data System (ADS)

Kishore, Bhaskar; Bazin, Pierre-Louis; Pham, Dzung L.

2009-02-01

We describe BrainIACS, a web-based medical image processing system that permits and facilitates algorithm developers to quickly create extensible user interfaces for their algorithms. Designed to address the challenges faced by algorithm developers in providing user-friendly graphical interfaces, BrainIACS is completely implemented using freely available, open-source software. The system, which is based on a client-server architecture, utilizes an AJAX front-end written using the Google Web Toolkit (GWT) and Java Servlets running on Apache Tomcat as its back-end. To enable developers to quickly and simply create user interfaces for configuring their algorithms, the interfaces are described using XML and are parsed by our system to create the corresponding user interface elements. Most of the commonly found elements such as check boxes, drop down lists, input boxes, radio buttons, tab panels and group boxes are supported. Some elements such as the input box support input validation. Changes to the user interface such as addition and deletion of elements are performed by editing the XML file or by using the system's user interface creator. In addition to user interface generation, the system also provides its own interfaces for data transfer, previewing of input and output files, and algorithm queuing. As the system is programmed using Java (and finally Java-script after compilation of the front-end code), it is platform independent with the only requirements being that a Servlet implementation be available and that the processing algorithms can execute on the server platform.

Differential amygdala response during facial recognition in patients with schizophrenia: an fMRI study.

PubMed

Kosaka, H; Omori, M; Murata, T; Iidaka, T; Yamada, H; Okada, T; Takahashi, T; Sadato, N; Itoh, H; Yonekura, Y; Wada, Y

2002-09-01

Human lesion or neuroimaging studies suggest that amygdala is involved in facial emotion recognition. Although impairments in recognition of facial and/or emotional expression have been reported in schizophrenia, there are few neuroimaging studies that have examined differential brain activation during facial recognition between patients with schizophrenia and normal controls. To investigate amygdala responses during facial recognition in schizophrenia, we conducted a functional magnetic resonance imaging (fMRI) study with 12 right-handed medicated patients with schizophrenia and 12 age- and sex-matched healthy controls. The experiment task was a type of emotional intensity judgment task. During the task period, subjects were asked to view happy (or angry/disgusting/sad) and neutral faces simultaneously presented every 3 s and to judge which face was more emotional (positive or negative face discrimination). Imaging data were investigated in voxel-by-voxel basis for single-group analysis and for between-group analysis according to the random effect model using Statistical Parametric Mapping (SPM). No significant difference in task accuracy was found between the schizophrenic and control groups. Positive face discrimination activated the bilateral amygdalae of both controls and schizophrenics, with more prominent activation of the right amygdala shown in the schizophrenic group. Negative face discrimination activated the bilateral amygdalae in the schizophrenic group whereas the right amygdala alone in the control group, although no significant group difference was found. Exaggerated amygdala activation during emotional intensity judgment found in the schizophrenic patients may reflect impaired gating of sensory input containing emotion. Copyright 2002 Elsevier Science B.V.

Methods and systems for determining angular orientation of a drill string

DOEpatents

Cobern, Martin E.

2010-03-23

Preferred methods and systems generate a control input based on a periodically-varying characteristic associated with the rotation of a drill string. The periodically varying characteristic can be correlated with the magnetic tool face and gravity tool face of a rotating component of the drill string, so that the control input can be used to initiate a response in the rotating component as a function of gravity tool face.

Image enhancement by non-linear extrapolation in frequency space

NASA Technical Reports Server (NTRS)

Anderson, Charles H. (Inventor); Greenspan, Hayit K. (Inventor)

1998-01-01

An input image is enhanced to include spatial frequency components having frequencies higher than those in an input image. To this end, an edge map is generated from the input image using a high band pass filtering technique. An enhancing map is subsequently generated from the edge map, with the enhanced map having spatial frequencies exceeding an initial maximum spatial frequency of the input image. The enhanced map is generated by applying a non-linear operator to the edge map in a manner which preserves the phase transitions of the edges of the input image. The enhanced map is added to the input image to achieve a resulting image having spatial frequencies greater than those in the input image. Simplicity of computations and ease of implementation allow for image sharpening after enlargement and for real-time applications such as videophones, advanced definition television, zooming, and restoration of old motion pictures.

Limited receptive area neural classifier for recognition of swallowing sounds using continuous wavelet transform.

PubMed

Makeyev, Oleksandr; Sazonov, Edward; Schuckers, Stephanie; Lopez-Meyer, Paulo; Melanson, Ed; Neuman, Michael

2007-01-01

In this paper we propose a sound recognition technique based on the limited receptive area (LIRA) neural classifier and continuous wavelet transform (CWT). LIRA neural classifier was developed as a multipurpose image recognition system. Previous tests of LIRA demonstrated good results in different image recognition tasks including: handwritten digit recognition, face recognition, metal surface texture recognition, and micro work piece shape recognition. We propose a sound recognition technique where scalograms of sound instances serve as inputs of the LIRA neural classifier. The methodology was tested in recognition of swallowing sounds. Swallowing sound recognition may be employed in systems for automated swallowing assessment and diagnosis of swallowing disorders. The experimental results suggest high efficiency and reliability of the proposed approach.

Visual cryptography for face privacy

NASA Astrophysics Data System (ADS)

Ross, Arun; Othman, Asem A.

2010-04-01

We discuss the problem of preserving the privacy of a digital face image stored in a central database. In the proposed scheme, a private face image is dithered into two host face images such that it can be revealed only when both host images are simultaneously available; at the same time, the individual host images do not reveal the identity of the original image. In order to accomplish this, we appeal to the field of Visual Cryptography. Experimental results confirm the following: (a) the possibility of hiding a private face image in two unrelated host face images; (b) the successful matching of face images that are reconstructed by superimposing the host images; and (c) the inability of the host images, known as sheets, to reveal the identity of the secret face image.

The Face-Processing Network Is Resilient to Focal Resection of Human Visual Cortex.

PubMed

Weiner, Kevin S; Jonas, Jacques; Gomez, Jesse; Maillard, Louis; Brissart, Hélène; Hossu, Gabriela; Jacques, Corentin; Loftus, David; Colnat-Coulbois, Sophie; Stigliani, Anthony; Barnett, Michael A; Grill-Spector, Kalanit; Rossion, Bruno

2016-08-10

Human face perception requires a network of brain regions distributed throughout the occipital and temporal lobes with a right hemisphere advantage. Present theories consider this network as either a processing hierarchy beginning with the inferior occipital gyrus (occipital face area; IOG-faces/OFA) or a multiple-route network with nonhierarchical components. The former predicts that removing IOG-faces/OFA will detrimentally affect downstream stages, whereas the latter does not. We tested this prediction in a human patient (Patient S.P.) requiring removal of the right inferior occipital cortex, including IOG-faces/OFA. We acquired multiple fMRI measurements in Patient S.P. before and after a preplanned surgery and multiple measurements in typical controls, enabling both within-subject/across-session comparisons (Patient S.P. before resection vs Patient S.P. after resection) and between-subject/across-session comparisons (Patient S.P. vs controls). We found that the spatial topology and selectivity of downstream ipsilateral face-selective regions were stable 1 and 8 month(s) after surgery. Additionally, the reliability of distributed patterns of face selectivity in Patient S.P. before versus after resection was not different from across-session reliability in controls. Nevertheless, postoperatively, representations of visual space were typical in dorsal face-selective regions but atypical in ventral face-selective regions and V1 of the resected hemisphere. Diffusion weighted imaging in Patient S.P. and controls identifies white matter tracts connecting retinotopic areas to downstream face-selective regions, which may contribute to the stable and plastic features of the face network in Patient S.P. after surgery. Together, our results support a multiple-route network of face processing with nonhierarchical components and shed light on stable and plastic features of high-level visual cortex following focal brain damage. Brain networks consist of interconnected functional regions commonly organized in processing hierarchies. Prevailing theories predict that damage to the input of the hierarchy will detrimentally affect later stages. We tested this prediction with multiple brain measurements in a rare human patient requiring surgical removal of the putative input to a network processing faces. Surprisingly, the spatial topology and selectivity of downstream face-selective regions are stable after surgery. Nevertheless, representations of visual space were typical in dorsal face-selective regions but atypical in ventral face-selective regions and V1. White matter connections from outside the face network may support these stable and plastic features. As processing hierarchies are ubiquitous in biological and nonbiological systems, our results have pervasive implications for understanding the construction of resilient networks. Copyright © 2016 the authors 0270-6474/16/368426-16$15.00/0.

Automated Rock Identification for Future Mars Exploration Missions

NASA Technical Reports Server (NTRS)

Gulick, V. C.; Morris, R. L.; Gazis, P.; Bishop, J. L.; Alena, R.; Hart, S. D.; Horton, A.

2003-01-01

A key task for human or robotic explorers on the surface of Mars is choosing which particular rock or mineral samples should be selected for more intensive study. The usual challenges of such a task are compounded by the lack of sensory input available to a suited astronaut or the limited downlink bandwidth available to a rover. Additional challenges facing a human mission include limited surface time and the similarities in appearance of important minerals (e.g. carbonates, silicates, salts). Yet the choice of which sample to collect is critical. To address this challenge we are developing science analysis algorithms to interface with a Geologist's Field Assistant (GFA) device that will allow robotic or human remote explorers to better sense and explore their surroundings during limited surface excursions. We aim for our algorithms to interpret spectral and imaging data obtained by various sensors. The algorithms, for example, will identify key minerals, rocks, and sediments from mid-IR, Raman, and visible/near-IR spectra as well as from high resolution and microscopic images to help interpret data and to provide high-level advice to the remote explorer. A top-level system will consider multiple inputs from raw sensor data output by imagers and spectrometers (visible/near-IR, mid-IR, and Raman) as well as human opinion to identify rock and mineral samples.

Age-related increase of image-invariance in the fusiform face area.

PubMed

Nordt, Marisa; Semmelmann, Kilian; Genç, Erhan; Weigelt, Sarah

2018-06-01

Face recognition undergoes prolonged development from childhood to adulthood, thereby raising the question which neural underpinnings are driving this development. Here, we address the development of the neural foundation of the ability to recognize a face across naturally varying images. Fourteen children (ages, 7-10) and 14 adults (ages, 20-23) watched images of either the same or different faces in a functional magnetic resonance imaging adaptation paradigm. The same face was either presented in exact image repetitions or in varying images. Additionally, a subset of participants completed a behavioral task, in which they decided if the face in consecutively presented images belonged to the same person. Results revealed age-related increases in neural sensitivity to face identity in the fusiform face area. Importantly, ventral temporal face-selective regions exhibited more image-invariance - as indicated by stronger adaptation for different images of the same person - in adults compared to children. Crucially, the amount of adaptation to face identity across varying images was correlated with the ability to recognize individual faces in different images. These results suggest that the increase of image-invariance in face-selective regions might be related to the development of face recognition skills. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Not All Faces Are Processed Equally: Evidence for Featural Rather than Holistic Processing of One's Own Face in a Face-Imaging Task

ERIC Educational Resources Information Center

Greenberg, Seth N.; Goshen-Gottstein, Yonatan

2009-01-01

The present work considers the mental imaging of faces, with a focus in own-face imaging. Experiments 1 and 3 demonstrated an own-face disadvantage, with slower generation of mental images of one's own face than of other familiar faces. In contrast, Experiment 2 demonstrated that mental images of facial parts are generated more quickly for one's…

Arrangement for multiplexing and intensity splitting light beams for interface into fiber optic cables

DOEpatents

Johnson, Steve A.

1990-01-01

An arrangement especially suitable for use in a laser apparatus for converting a plurality of different input light beams, for example copper vapor laser beams, into a plurality of substantially identical light beams is disclosed herein. This arrangement utilizes an optical mixing bar which is preferably integrally formed as a single unit and which includes a main body for mixing light therein, a flat input surface on one end of the main body, and a multi-faceted output face on the opposite end of the main body. This arrangement also includes means for directing the plurality of different input light beams onto the input face of the mixing base, whereby to cause the different beams to mix within the main body of the mixing bar and exit the latter from its multi-faceted output face as the desired plurality of substantially identical output beams.

System for face recognition under expression variations of neutral-sampled individuals using recognized expression warping and a virtual expression-face database

NASA Astrophysics Data System (ADS)

Petpairote, Chayanut; Madarasmi, Suthep; Chamnongthai, Kosin

2018-01-01

The practical identification of individuals using facial recognition techniques requires the matching of faces with specific expressions to faces from a neutral face database. A method for facial recognition under varied expressions against neutral face samples of individuals via recognition of expression warping and the use of a virtual expression-face database is proposed. In this method, facial expressions are recognized and the input expression faces are classified into facial expression groups. To aid facial recognition, the virtual expression-face database is sorted into average facial-expression shapes and by coarse- and fine-featured facial textures. Wrinkle information is also employed in classification by using a process of masking to adjust input faces to match the expression-face database. We evaluate the performance of the proposed method using the CMU multi-PIE, Cohn-Kanade, and AR expression-face databases, and we find that it provides significantly improved results in terms of face recognition accuracy compared to conventional methods and is acceptable for facial recognition under expression variation.

Optical image encryption system using nonlinear approach based on biometric authentication

NASA Astrophysics Data System (ADS)

Verma, Gaurav; Sinha, Aloka

2017-07-01

A nonlinear image encryption scheme using phase-truncated Fourier transform (PTFT) and natural logarithms is proposed in this paper. With the help of the PTFT, the input image is truncated into phase and amplitude parts at the Fourier plane. The phase-only information is kept as the secret key for the decryption, and the amplitude distribution is modulated by adding an undercover amplitude random mask in the encryption process. Furthermore, the encrypted data is kept hidden inside the face biometric-based phase mask key using the base changing rule of logarithms for secure transmission. This phase mask is generated through principal component analysis. Numerical experiments show the feasibility and the validity of the proposed nonlinear scheme. The performance of the proposed scheme has been studied against the brute force attacks and the amplitude-phase retrieval attack. Simulation results are presented to illustrate the enhanced system performance with desired advantages in comparison to the linear cryptosystem.

Enhancing the performance of cooperative face detector by NFGS

NASA Astrophysics Data System (ADS)

Yesugade, Snehal; Dave, Palak; Srivastava, Srinkhala; Das, Apurba

2015-07-01

Computerized human face detection is an important task of deformable pattern recognition in today's world. Especially in cooperative authentication scenarios like ATM fraud detection, attendance recording, video tracking and video surveillance, the accuracy of the face detection engine in terms of accuracy, memory utilization and speed have been active areas of research for the last decade. The Haar based face detection or SIFT and EBGM based face recognition systems are fairly reliable in this regard. But, there the features are extracted in terms of gray textures. When the input is a high resolution online video with a fairly large viewing area, Haar needs to search for face everywhere (say 352×250 pixels) and every time (e.g., 30 FPS capture all the time). In the current paper we have proposed to address both the aforementioned scenarios by a neuro-visually inspired method of figure-ground segregation (NFGS) [5] to result in a two-dimensional binary array from gray face image. The NFGS would identify the reference video frame in a low sampling rate and updates the same with significant change of environment like illumination. The proposed algorithm would trigger the face detector only when appearance of a new entity is encountered into the viewing area. To address the detection accuracy, classical face detector would be enabled only in a narrowed down region of interest (RoI) as fed by the NFGS. The act of updating the RoI would be done in each frame online with respect to the moving entity which in turn would improve both FR (False Rejection) and FA (False Acceptance) of the face detection system.

Programmable remapper for image processing

NASA Technical Reports Server (NTRS)

Juday, Richard D. (Inventor); Sampsell, Jeffrey B. (Inventor)

1991-01-01

A video-rate coordinate remapper includes a memory for storing a plurality of transformations on look-up tables for remapping input images from one coordinate system to another. Such transformations are operator selectable. The remapper includes a collective processor by which certain input pixels of an input image are transformed to a portion of the output image in a many-to-one relationship. The remapper includes an interpolative processor by which the remaining input pixels of the input image are transformed to another portion of the output image in a one-to-many relationship. The invention includes certain specific transforms for creating output images useful for certain defects of visually impaired people. The invention also includes means for shifting input pixels and means for scrolling the output matrix.

The Photorefractive Effect and its Application in Optical Computing

NASA Astrophysics Data System (ADS)

Li, Guo

This Ph.D dissertation includes the fanning effect and the temperature dependence of the diffraction efficiency and response time using different addressing configurations, and evaluation of the limitations and capacity of a holographic storage in BaTiO_3 crystals. Also, we designed a digital holographic optical disk and made an associate memory. The beam fanning effect in a BaTiO_3 crystal was investigated in detail. The effect depends on the crystal faces illuminated. In particular, for the +c face of illumination we found that the fanning effect strongly depends on angle of incidence, polarization and wavelength of the incident light, crystal temperature, laser beam profile, but only weakly depends on input laser power. In the case of the -c face and a-face illumination dependence of the ring angle on wavelength and input power was observed. We found that the intensity of the reflected beam in NDFWM, the intensity of self phase conjugate beam and the response time of the fanning effect decrease with temperature exponentially and there being a major change around 60 ^circ-80^circ C. A random bistability and oscillation of the SPPC occur around 80^circC. We also present a theoretical analysis for the dependence of the photorefractive effect on temperature. We experimentally evaluate the capacity and limitation of optical storage in BaTiO_3 crystals using self-pumped phase conjugation (SPPC) and two-wave mixing. The storage capacity is different with different face of illumination, polarization, beam profile and input power. We demonstrate that using two wave mixing, three dimensional volume holograms can be stored. The information -bearing beam diameter for storage and recall can be about 0.25mm or less. By these techniques we demonstrate that at least 10^5 holograms can be stored in a 3.5 inch photorefractive disk. We evaluate an optimal optical architecture for exploiting the photorefractive effect for digital holographic disk storage. An image with many pixels was used for this experimental evaluation. By using a raytracing program, we traced a beam with a Gaussian profile through our optical system. We also estimated the Seidel aberration of our optical system in order to determine the quality of the stored digital data.

Using false colors to protect visual privacy of sensitive content

NASA Astrophysics Data System (ADS)

Ćiftçi, Serdar; Korshunov, Pavel; Akyüz, Ahmet O.; Ebrahimi, Touradj

2015-03-01

Many privacy protection tools have been proposed for preserving privacy. Tools for protection of visual privacy available today lack either all or some of the important properties that are expected from such tools. Therefore, in this paper, we propose a simple yet effective method for privacy protection based on false color visualization, which maps color palette of an image into a different color palette, possibly after a compressive point transformation of the original pixel data, distorting the details of the original image. This method does not require any prior face detection or other sensitive regions detection and, hence, unlike typical privacy protection methods, it is less sensitive to inaccurate computer vision algorithms. It is also secure as the look-up tables can be encrypted, reversible as table look-ups can be inverted, flexible as it is independent of format or encoding, adjustable as the final result can be computed by interpolating the false color image with the original using different degrees of interpolation, less distracting as it does not create visually unpleasant artifacts, and selective as it preserves better semantic structure of the input. Four different color scales and four different compression functions, one which the proposed method relies, are evaluated via objective (three face recognition algorithms) and subjective (50 human subjects in an online-based study) assessments using faces from FERET public dataset. The evaluations demonstrate that DEF and RBS color scales lead to the strongest privacy protection, while compression functions add little to the strength of privacy protection. Statistical analysis also shows that recognition algorithms and human subjects perceive the proposed protection similarly

Online decoding of object-based attention using real-time fMRI.

PubMed

Niazi, Adnan M; van den Broek, Philip L C; Klanke, Stefan; Barth, Markus; Poel, Mannes; Desain, Peter; van Gerven, Marcel A J

2014-01-01

Visual attention is used to selectively filter relevant information depending on current task demands and goals. Visual attention is called object-based attention when it is directed to coherent forms or objects in the visual field. This study used real-time functional magnetic resonance imaging for moment-to-moment decoding of attention to spatially overlapped objects belonging to two different object categories. First, a whole-brain classifier was trained on pictures of faces and places. Subjects then saw transparently overlapped pictures of a face and a place, and attended to only one of them while ignoring the other. The category of the attended object, face or place, was decoded on a scan-by-scan basis using the previously trained decoder. The decoder performed at 77.6% accuracy indicating that despite competing bottom-up sensory input, object-based visual attention biased neural patterns towards that of the attended object. Furthermore, a comparison between different classification approaches indicated that the representation of faces and places is distributed rather than focal. This implies that real-time decoding of object-based attention requires a multivariate decoding approach that can detect these distributed patterns of cortical activity. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Fast and accurate face recognition based on image compression

NASA Astrophysics Data System (ADS)

Zheng, Yufeng; Blasch, Erik

2017-05-01

Image compression is desired for many image-related applications especially for network-based applications with bandwidth and storage constraints. The face recognition community typical reports concentrate on the maximal compression rate that would not decrease the recognition accuracy. In general, the wavelet-based face recognition methods such as EBGM (elastic bunch graph matching) and FPB (face pattern byte) are of high performance but run slowly due to their high computation demands. The PCA (Principal Component Analysis) and LDA (Linear Discriminant Analysis) algorithms run fast but perform poorly in face recognition. In this paper, we propose a novel face recognition method based on standard image compression algorithm, which is termed as compression-based (CPB) face recognition. First, all gallery images are compressed by the selected compression algorithm. Second, a mixed image is formed with the probe and gallery images and then compressed. Third, a composite compression ratio (CCR) is computed with three compression ratios calculated from: probe, gallery and mixed images. Finally, the CCR values are compared and the largest CCR corresponds to the matched face. The time cost of each face matching is about the time of compressing the mixed face image. We tested the proposed CPB method on the "ASUMSS face database" (visible and thermal images) from 105 subjects. The face recognition accuracy with visible images is 94.76% when using JPEG compression. On the same face dataset, the accuracy of FPB algorithm was reported as 91.43%. The JPEG-compressionbased (JPEG-CPB) face recognition is standard and fast, which may be integrated into a real-time imaging device.

Mapping attractor fields in face space: the atypicality bias in face recognition.

PubMed

Tanaka, J; Giles, M; Kremen, S; Simon, V

1998-09-01

A familiar face can be recognized across many changes in the stimulus input. In this research, the many-to-one mapping of face stimuli to a single face memory is referred to as a face memory's 'attractor field'. According to the attractor field approach, a face memory will be activated by any stimuli falling within the boundaries of its attractor field. It was predicted that by virtue of its location in a multi-dimensional face space, the attractor field of an atypical face will be larger than the attractor field of a typical face. To test this prediction, subjects make likeness judgments to morphed faces that contained a 50/50 contribution from an atypical and a typical parent face. The main result of four experiments was that the morph face was judged to bear a stronger resemblance to the atypical face parent than the typical face parent. The computational basis of the atypicality bias was demonstrated in a neural network simulation where morph inputs of atypical and typical representations elicited stronger activation of atypical output units than of typical output units. Together, the behavioral and simulation evidence supports the view that the attractor fields of atypical faces span over a broader region of face space that the attractor fields of typical faces.

Image scale measurement with correlation filters in a volume holographic optical correlator

NASA Astrophysics Data System (ADS)

Zheng, Tianxiang; Cao, Liangcai; He, Qingsheng; Jin, Guofan

2013-08-01

A search engine containing various target images or different part of a large scene area is of great use for many applications, including object detection, biometric recognition, and image registration. The input image captured in realtime is compared with all the template images in the search engine. A volume holographic correlator is one type of these search engines. It performs thousands of comparisons among the images at a super high speed, with the correlation task accomplishing mainly in optics. However, the inputted target image always contains scale variation to the filtering template images. At the time, the correlation values cannot properly reflect the similarity of the images. It is essential to estimate and eliminate the scale variation of the inputted target image. There are three domains for performing the scale measurement, as spatial, spectral and time domains. Most methods dealing with the scale factor are based on the spatial or the spectral domains. In this paper, a method with the time domain is proposed to measure the scale factor of the input image. It is called a time-sequential scaled method. The method utilizes the relationship between the scale variation and the correlation value of two images. It sends a few artificially scaled input images to compare with the template images. The correlation value increases and decreases with the increasing of the scale factor at the intervals of 0.8~1 and 1~1.2, respectively. The original scale of the input image can be measured by estimating the largest correlation value through correlating the artificially scaled input image with the template images. The measurement range for the scale can be 0.8~4.8. Scale factor beyond 1.2 is measured by scaling the input image at the factor of 1/2, 1/3 and 1/4, correlating the artificially scaled input image with the template images, and estimating the new corresponding scale factor inside 0.8~1.2.

InterFace: A software package for face image warping, averaging, and principal components analysis.

PubMed

Kramer, Robin S S; Jenkins, Rob; Burton, A Mike

2017-12-01

We describe InterFace, a software package for research in face recognition. The package supports image warping, reshaping, averaging of multiple face images, and morphing between faces. It also supports principal components analysis (PCA) of face images, along with tools for exploring the "face space" produced by PCA. The package uses a simple graphical user interface, allowing users to perform these sophisticated image manipulations without any need for programming knowledge. The program is available for download in the form of an app, which requires that users also have access to the (freely available) MATLAB Runtime environment.

Torque Splitting by a Concentric Face Gear Transmission

NASA Technical Reports Server (NTRS)

Filler, Robert R.; Heath, Gregory F.; Slaughter, Stephen C.; Lewicki, David G.

2002-01-01

Tests of a 167 Kilowatt (224 Horsepower) split torque face gearbox were performed by the Boeing Company in Mesa, Arizona, while working under a Defense Advanced Research Projects Agency (DARPA) Technology Reinvestment Program (TRP). This paper provides a summary of these cooperative tests, which were jointly funded by Boeing and DARPA. Design, manufacture and testing of the scaled-power TRP proof-of-concept (POC) split torque gearbox followed preliminary evaluations of the concept performed early in the program. The split torque tests were run using 200 N-m (1767 in-lbs) torque input to each side of the transmission. During tests, two input pinions were slow rolled while in mesh with the two face gears. Two idler gears were also used in the configuration to recombine torque near the output. Resistance was applied at the output face gear to create the required loading conditions in the gear teeth. A system of weights, pulleys and cables were used in the test rig to provide both the input and output loading. Strain gages applied in the tooth root fillets provided strain indication used to determine torque splitting conditions at the input pinions. The final two pinion-two idler tests indicated 52% to 48% average torque split capabilities for the two pinions. During the same tests, a 57% to 43% average distribution of the torque being recombined to the upper face gear from the lower face gear was measured between the two idlers. The POC split torque tests demonstrated that face gears can be applied effectively in split torque rotorcraft transmissions, yielding good potential for significant weight, cost and reliability improvements over existing equipment using spiral bevel gearing.

Rhomboid prism pair for rotating the plane of parallel light beams

NASA Technical Reports Server (NTRS)

Orloff, K. L. (Inventor); Yanagita, H.

1982-01-01

An optical system is described for rotating the plane defined by a pair of parallel light beams. In one embodiment a single pair of rhomboid prisms have their respective input faces disposed to receive the respective input beams. Each prism is rotated about an axis of revolution coaxial with each of the respective input beams by means of a suitable motor and gear arrangement to cause the plane of the parallel output beams to be rotated relative to the plane of the input beams. In a second embodiment, two pairs of rhomboid prisms are provided. In a first angular orientation of the output beams, the prisms merely decrease the lateral displacement of the output beams in order to keep in the same plane as the input beams. In a second angular orientation of the prisms, the input faces of the second pair of prisms are brought into coincidence with the input beams for rotating the plane of the output beams by a substantial angle such as 90 deg.

Purification of Training Samples Based on Spectral Feature and Superpixel Segmentation

NASA Astrophysics Data System (ADS)

Guan, X.; Qi, W.; He, J.; Wen, Q.; Chen, T.; Wang, Z.

2018-04-01

Remote sensing image classification is an effective way to extract information from large volumes of high-spatial resolution remote sensing images. Generally, supervised image classification relies on abundant and high-precision training data, which is often manually interpreted by human experts to provide ground truth for training and evaluating the performance of the classifier. Remote sensing enterprises accumulated lots of manually interpreted products from early lower-spatial resolution remote sensing images by executing their routine research and business programs. However, these manually interpreted products may not match the very high resolution (VHR) image properly because of different dates or spatial resolution of both data, thus, hindering suitability of manually interpreted products in training classification models, or small coverage area of these manually interpreted products. We also face similar problems in our laboratory in 21st Century Aerospace Technology Co. Ltd (short for 21AT). In this work, we propose a method to purify the interpreted product to match newly available VHRI data and provide the best training data for supervised image classifiers in VHR image classification. And results indicate that our proposed method can efficiently purify the input data for future machine learning use.

Cross-modal face recognition using multi-matcher face scores

NASA Astrophysics Data System (ADS)

Zheng, Yufeng; Blasch, Erik

2015-05-01

The performance of face recognition can be improved using information fusion of multimodal images and/or multiple algorithms. When multimodal face images are available, cross-modal recognition is meaningful for security and surveillance applications. For example, a probe face is a thermal image (especially at nighttime), while only visible face images are available in the gallery database. Matching a thermal probe face onto the visible gallery faces requires crossmodal matching approaches. A few such studies were implemented in facial feature space with medium recognition performance. In this paper, we propose a cross-modal recognition approach, where multimodal faces are cross-matched in feature space and the recognition performance is enhanced with stereo fusion at image, feature and/or score level. In the proposed scenario, there are two cameras for stereo imaging, two face imagers (visible and thermal images) in each camera, and three recognition algorithms (circular Gaussian filter, face pattern byte, linear discriminant analysis). A score vector is formed with three cross-matched face scores from the aforementioned three algorithms. A classifier (e.g., k-nearest neighbor, support vector machine, binomial logical regression [BLR]) is trained then tested with the score vectors by using 10-fold cross validations. The proposed approach was validated with a multispectral stereo face dataset from 105 subjects. Our experiments show very promising results: ACR (accuracy rate) = 97.84%, FAR (false accept rate) = 0.84% when cross-matching the fused thermal faces onto the fused visible faces by using three face scores and the BLR classifier.

Anatomical connections of the functionally-defined “face patches” in the macaque monkey

PubMed Central

Saleem, Kadharbatcha S.

2017-01-01

The neural circuits underlying face recognition provide a model for understanding visual object representation, social cognition, and hierarchical information processing. A fundamental piece of information lacking to date is the detailed anatomical connections of the face patches. Here, we injected retrograde tracers into four different face patches (PL, ML, AL, AM) to characterize their anatomical connectivity. We found that the patches are strongly and specifically connected to each other, and individual patches receive inputs from extrastriate cortex, the medial temporal lobe, and three subcortical structures (the pulvinar, claustrum, and amygdala). Inputs from prefrontal cortex were surprisingly weak. Patches were densely interconnected to one another in both feedforward and feedback directions, inconsistent with a serial hierarchy. These results provide the first direct anatomical evidence that the face patches constitute a highly specialized system, and suggest that subcortical regions may play a vital role in routing face-related information to subsequent processing stages. PMID:27263973

Face familiarity promotes stable identity recognition: exploring face perception using serial dependence

PubMed Central

Kok, Rebecca; Van der Burg, Erik; Rhodes, Gillian; Alais, David

2017-01-01

Studies suggest that familiar faces are processed in a manner distinct from unfamiliar faces and that familiarity with a face confers an advantage in identity recognition. Our visual system seems to capitalize on experience to build stable face representations that are impervious to variation in retinal input that may occur due to changes in lighting, viewpoint, viewing distance, eye movements, etc. Emerging evidence also suggests that our visual system maintains a continuous perception of a face's identity from one moment to the next despite the retinal input variations through serial dependence. This study investigates whether interactions occur between face familiarity and serial dependence. In two experiments, participants used a continuous scale to rate attractiveness of unfamiliar and familiar faces (either experimentally learned or famous) presented in rapid sequences. Both experiments revealed robust inter-trial effects in which attractiveness ratings for a given face depended on the preceding face's attractiveness. This inter-trial attractiveness effect was most pronounced for unfamiliar faces. Indeed, when participants were familiar with a given face, attractiveness ratings showed significantly less serial dependence. These results represent the first evidence that familiar faces can resist the temporal integration seen in sequential dependencies and highlight the importance of familiarity to visual cognition. PMID:28405355

Common path endoscopic probes for optical coherence tomography (Conference Presentation)

NASA Astrophysics Data System (ADS)

Singh, Kanwarpal; Gardecki, Joseph A.; Tearney, Guillermo J.

2017-02-01

Background: Dispersion imbalance and polarization mismatch between the reference and sample arm signals can lead to image quality degradation in optical coherence tomography (OCT). One approach to reduce these image artifacts is to employ a common-path geometry in fiber-based probes. In this work, we report an 800 um diameter all-fiber common-path monolithic probe for coronary artery imaging where the reference signal is generated using an inline fiber partial reflector. Methods: Our common-path probe was designed for swept-source based Fourier domain OCT at 1310 nm wavelength. A face of a coreless fiber was coated with gold and spliced to a standard SMF-28 single mode fiber creating an inline partial reflector, which acted as a reference surface. The other face of the coreless fiber was shaped into a ball lens for focusing. The optical elements were assembled within a 560 µm diameter drive shaft, which was attached to a rotary junction. The drive shaft was placed inside a transparent sheath having an outer diameter of 800 µm. Results: With a source input power of 30mW, the inline common-path probe achieved a sensitivity of 104 dB. Images of human finger skin showed the characteristic layers of skin as well as features such as sweat ducts. Images of coronary arteries ex vivo obtained with this probe enabled visualization of the characteristic architectural morphology of the normal artery wall and known features of atherosclerotic plaque. Conclusion: In this work, we have demonstrated a common path OCT probe for cardiovascular imaging. The probe is easy to fabricate, will reduce system complexity and overall cost. We believe that this design will be helpful in endoscopic applications that require high resolution and a compact form factor.

The role of external features in face recognition with central vision loss: A pilot study

PubMed Central

Bernard, Jean-Baptiste; Chung, Susana T.L.

2016-01-01

Purpose We evaluated how the performance for recognizing familiar face images depends on the internal (eyebrows, eyes, nose, mouth) and external face features (chin, outline of face, hairline) in individuals with central vision loss. Methods In Experiment 1, we measured eye movements for four observers with central vision loss to determine whether they fixated more often on the internal or the external features of face images while attempting to recognize the images. We then measured the accuracy for recognizing face images that contained only the internal, only the external, or both internal and external features (Experiment 2), and for hybrid images where the internal and external features came from two different source images (Experiment 3), for five observers with central vision loss and four age-matched control observers. Results When recognizing familiar face images, approximately 40% of the fixations of observers with central vision loss were centered on the external features of faces. The recognition accuracy was higher for images containing only external features (66.8±3.3% correct) than for images containing only internal features (35.8±15.0%), a finding contradicting that of control observers. For hybrid face images, observers with central vision loss responded more accurately to the external features (50.4±17.8%) than to the internal features (9.3±4.9%), while control observers did not show the same bias toward responding to the external features. Conclusions Contrary to people with normal vision who rely more on the internal features of face images for recognizing familiar faces, individuals with central vision loss show a higher dependence on using external features of face images. PMID:26829260

The Role of External Features in Face Recognition with Central Vision Loss.

PubMed

Bernard, Jean-Baptiste; Chung, Susana T L

2016-05-01

We evaluated how the performance of recognizing familiar face images depends on the internal (eyebrows, eyes, nose, mouth) and external face features (chin, outline of face, hairline) in individuals with central vision loss. In experiment 1, we measured eye movements for four observers with central vision loss to determine whether they fixated more often on the internal or the external features of face images while attempting to recognize the images. We then measured the accuracy for recognizing face images that contained only the internal, only the external, or both internal and external features (experiment 2) and for hybrid images where the internal and external features came from two different source images (experiment 3) for five observers with central vision loss and four age-matched control observers. When recognizing familiar face images, approximately 40% of the fixations of observers with central vision loss was centered on the external features of faces. The recognition accuracy was higher for images containing only external features (66.8 ± 3.3% correct) than for images containing only internal features (35.8 ± 15.0%), a finding contradicting that of control observers. For hybrid face images, observers with central vision loss responded more accurately to the external features (50.4 ± 17.8%) than to the internal features (9.3 ± 4.9%), whereas control observers did not show the same bias toward responding to the external features. Contrary to people with normal vision who rely more on the internal features of face images for recognizing familiar faces, individuals with central vision loss show a higher dependence on using external features of face images.

32 CFR Appendix B to Part 68 - Addendum for Education Services Between [Name of Educational Institution] and the U.S. Air Force

Code of Federal Regulations, 2014 CFR

2014-07-01

... contractor for training in the use of the Academic Institution Portal (AI Portal) regarding input of... incompletion of a course. Face-to-face counseling is not required. (5) Register and use the AI Portal to input... with the USAF. (6) Submit one consolidated invoice per term via the AI Portal for each class in which...

Social Cognition in Williams Syndrome: Face Tuning

PubMed Central

Pavlova, Marina A.; Heiz, Julie; Sokolov, Alexander N.; Barisnikov, Koviljka

2016-01-01

Many neurological, neurodevelopmental, neuropsychiatric, and psychosomatic disorders are characterized by impairments in visual social cognition, body language reading, and facial assessment of a social counterpart. Yet a wealth of research indicates that individuals with Williams syndrome exhibit remarkable concern for social stimuli and face fascination. Here individuals with Williams syndrome were presented with a set of Face-n-Food images composed of food ingredients and in different degree resembling a face (slightly bordering on the Giuseppe Arcimboldo style). The primary advantage of these images is that single components do not explicitly trigger face-specific processing, whereas in face images commonly used for investigating face perception (such as photographs or depictions), the mere occurrence of typical cues already implicates face presence. In a spontaneous recognition task, participants were shown a set of images in a predetermined order from the least to most resembling a face. Strikingly, individuals with Williams syndrome exhibited profound deficits in recognition of the Face-n-Food images as a face: they did not report seeing a face on the images, which typically developing controls effortlessly recognized as a face, and gave overall fewer face responses. This suggests atypical face tuning in Williams syndrome. The outcome is discussed in the light of a general pattern of social cognition in Williams syndrome and brain mechanisms underpinning face processing. PMID:27531986

Social Cognition in Williams Syndrome: Face Tuning.

PubMed

Pavlova, Marina A; Heiz, Julie; Sokolov, Alexander N; Barisnikov, Koviljka

2016-01-01

Many neurological, neurodevelopmental, neuropsychiatric, and psychosomatic disorders are characterized by impairments in visual social cognition, body language reading, and facial assessment of a social counterpart. Yet a wealth of research indicates that individuals with Williams syndrome exhibit remarkable concern for social stimuli and face fascination. Here individuals with Williams syndrome were presented with a set of Face-n-Food images composed of food ingredients and in different degree resembling a face (slightly bordering on the Giuseppe Arcimboldo style). The primary advantage of these images is that single components do not explicitly trigger face-specific processing, whereas in face images commonly used for investigating face perception (such as photographs or depictions), the mere occurrence of typical cues already implicates face presence. In a spontaneous recognition task, participants were shown a set of images in a predetermined order from the least to most resembling a face. Strikingly, individuals with Williams syndrome exhibited profound deficits in recognition of the Face-n-Food images as a face: they did not report seeing a face on the images, which typically developing controls effortlessly recognized as a face, and gave overall fewer face responses. This suggests atypical face tuning in Williams syndrome. The outcome is discussed in the light of a general pattern of social cognition in Williams syndrome and brain mechanisms underpinning face processing.

Recognition Using Hybrid Classifiers.

PubMed

Osadchy, Margarita; Keren, Daniel; Raviv, Dolev

2016-04-01

A canonical problem in computer vision is category recognition (e.g., find all instances of human faces, cars etc., in an image). Typically, the input for training a binary classifier is a relatively small sample of positive examples, and a huge sample of negative examples, which can be very diverse, consisting of images from a large number of categories. The difficulty of the problem sharply increases with the dimension and size of the negative example set. We propose to alleviate this problem by applying a "hybrid" classifier, which replaces the negative samples by a prior, and then finds a hyperplane which separates the positive samples from this prior. The method is extended to kernel space and to an ensemble-based approach. The resulting binary classifiers achieve an identical or better classification rate than SVM, while requiring far smaller memory and lower computational complexity to train and apply.

Face detection on distorted images using perceptual quality-aware features

NASA Astrophysics Data System (ADS)

Gunasekar, Suriya; Ghosh, Joydeep; Bovik, Alan C.

2014-02-01

We quantify the degradation in performance of a popular and effective face detector when human-perceived image quality is degraded by distortions due to additive white gaussian noise, gaussian blur or JPEG compression. It is observed that, within a certain range of perceived image quality, a modest increase in image quality can drastically improve face detection performance. These results can be used to guide resource or bandwidth allocation in a communication/delivery system that is associated with face detection tasks. A new face detector based on QualHOG features is also proposed that augments face-indicative HOG features with perceptual quality-aware spatial Natural Scene Statistics (NSS) features, yielding improved tolerance against image distortions. The new detector provides statistically significant improvements over a strong baseline on a large database of face images representing a wide range of distortions. To facilitate this study, we created a new Distorted Face Database, containing face and non-face patches from images impaired by a variety of common distortion types and levels. This new dataset is available for download and further experimentation at www.ideal.ece.utexas.edu/˜suriya/DFD/.

Locality constrained joint dynamic sparse representation for local matching based face recognition.

PubMed

Wang, Jianzhong; Yi, Yugen; Zhou, Wei; Shi, Yanjiao; Qi, Miao; Zhang, Ming; Zhang, Baoxue; Kong, Jun

2014-01-01

Recently, Sparse Representation-based Classification (SRC) has attracted a lot of attention for its applications to various tasks, especially in biometric techniques such as face recognition. However, factors such as lighting, expression, pose and disguise variations in face images will decrease the performances of SRC and most other face recognition techniques. In order to overcome these limitations, we propose a robust face recognition method named Locality Constrained Joint Dynamic Sparse Representation-based Classification (LCJDSRC) in this paper. In our method, a face image is first partitioned into several smaller sub-images. Then, these sub-images are sparsely represented using the proposed locality constrained joint dynamic sparse representation algorithm. Finally, the representation results for all sub-images are aggregated to obtain the final recognition result. Compared with other algorithms which process each sub-image of a face image independently, the proposed algorithm regards the local matching-based face recognition as a multi-task learning problem. Thus, the latent relationships among the sub-images from the same face image are taken into account. Meanwhile, the locality information of the data is also considered in our algorithm. We evaluate our algorithm by comparing it with other state-of-the-art approaches. Extensive experiments on four benchmark face databases (ORL, Extended YaleB, AR and LFW) demonstrate the effectiveness of LCJDSRC.

Sub-pattern based multi-manifold discriminant analysis for face recognition

NASA Astrophysics Data System (ADS)

Dai, Jiangyan; Guo, Changlu; Zhou, Wei; Shi, Yanjiao; Cong, Lin; Yi, Yugen

2018-04-01

In this paper, we present a Sub-pattern based Multi-manifold Discriminant Analysis (SpMMDA) algorithm for face recognition. Unlike existing Multi-manifold Discriminant Analysis (MMDA) approach which is based on holistic information of face image for recognition, SpMMDA operates on sub-images partitioned from the original face image and then extracts the discriminative local feature from the sub-images separately. Moreover, the structure information of different sub-images from the same face image is considered in the proposed method with the aim of further improve the recognition performance. Extensive experiments on three standard face databases (Extended YaleB, CMU PIE and AR) demonstrate that the proposed method is effective and outperforms some other sub-pattern based face recognition methods.

Illumination robust face recognition using spatial adaptive shadow compensation based on face intensity prior

NASA Astrophysics Data System (ADS)

Hsieh, Cheng-Ta; Huang, Kae-Horng; Lee, Chang-Hsing; Han, Chin-Chuan; Fan, Kuo-Chin

2017-12-01

Robust face recognition under illumination variations is an important and challenging task in a face recognition system, particularly for face recognition in the wild. In this paper, a face image preprocessing approach, called spatial adaptive shadow compensation (SASC), is proposed to eliminate shadows in the face image due to different lighting directions. First, spatial adaptive histogram equalization (SAHE), which uses face intensity prior model, is proposed to enhance the contrast of each local face region without generating visible noises in smooth face areas. Adaptive shadow compensation (ASC), which performs shadow compensation in each local image block, is then used to produce a wellcompensated face image appropriate for face feature extraction and recognition. Finally, null-space linear discriminant analysis (NLDA) is employed to extract discriminant features from SASC compensated images. Experiments performed on the Yale B, Yale B extended, and CMU PIE face databases have shown that the proposed SASC always yields the best face recognition accuracy. That is, SASC is more robust to face recognition under illumination variations than other shadow compensation approaches.

Precedence of the eye region in neural processing of faces

PubMed Central

Issa, Elias; DiCarlo, James

2012-01-01

SUMMARY Functional magnetic resonance imaging (fMRI) has revealed multiple subregions in monkey inferior temporal cortex (IT) that are selective for images of faces over other objects. The earliest of these subregions, the posterior lateral face patch (PL), has not been studied previously at the neurophysiological level. Perhaps not surprisingly, we found that PL contains a high concentration of ‘face selective’ cells when tested with standard image sets comparable to those used previously to define the region at the level of fMRI. However, we here report that several different image sets and analytical approaches converge to show that nearly all face selective PL cells are driven by the presence of a single eye in the context of a face outline. Most strikingly, images containing only an eye, even when incorrectly positioned in an outline, drove neurons nearly as well as full face images, and face images lacking only this feature led to longer latency responses. Thus, bottom-up face processing is relatively local and linearly integrates features -- consistent with parts-based models -- grounding investigation of how the presence of a face is first inferred in the IT face processing hierarchy. PMID:23175821

Why the long face? The importance of vertical image structure for biological "barcodes" underlying face recognition.

PubMed

Spence, Morgan L; Storrs, Katherine R; Arnold, Derek H

2014-07-29

Humans are experts at face recognition. The mechanisms underlying this complex capacity are not fully understood. Recently, it has been proposed that face recognition is supported by a coarse-scale analysis of visual information contained in horizontal bands of contrast distributed along the vertical image axis-a biological facial "barcode" (Dakin & Watt, 2009). A critical prediction of the facial barcode hypothesis is that the distribution of image contrast along the vertical axis will be more important for face recognition than image distributions along the horizontal axis. Using a novel paradigm involving dynamic image distortions, a series of experiments are presented examining famous face recognition impairments from selectively disrupting image distributions along the vertical or horizontal image axes. Results show that disrupting the image distribution along the vertical image axis is more disruptive for recognition than matched distortions along the horizontal axis. Consistent with the facial barcode hypothesis, these results suggest that human face recognition relies disproportionately on appropriately scaled distributions of image contrast along the vertical image axis. © 2014 ARVO.

Can we match ultraviolet face images against their visible counterparts?

NASA Astrophysics Data System (ADS)

Narang, Neeru; Bourlai, Thirimachos; Hornak, Lawrence A.

2015-05-01

In law enforcement and security applications, the acquisition of face images is critical in producing key trace evidence for the successful identification of potential threats. However, face recognition (FR) for face images captured using different camera sensors, and under variable illumination conditions, and expressions is very challenging. In this paper, we investigate the advantages and limitations of the heterogeneous problem of matching ultra violet (from 100 nm to 400 nm in wavelength) or UV, face images against their visible (VIS) counterparts, when all face images are captured under controlled conditions. The contributions of our work are three-fold; (i) We used a camera sensor designed with the capability to acquire UV images at short-ranges, and generated a dual-band (VIS and UV) database that is composed of multiple, full frontal, face images of 50 subjects. Two sessions were collected that span over the period of 2 months. (ii) For each dataset, we determined which set of face image pre-processing algorithms are more suitable for face matching, and, finally, (iii) we determined which FR algorithm better matches cross-band face images, resulting in high rank-1 identification rates. Experimental results show that our cross spectral matching (the heterogeneous problem, where gallery and probe sets consist of face images acquired in different spectral bands) algorithms achieve sufficient identification performance. However, we also conclude that the problem under study, is very challenging, and it requires further investigation to address real-world law enforcement or military applications. To the best of our knowledge, this is first time in the open literature the problem of cross-spectral matching of UV against VIS band face images is being investigated.

Implicit multisensory associations influence voice recognition.

PubMed

von Kriegstein, Katharina; Giraud, Anne-Lise

2006-10-01

Natural objects provide partially redundant information to the brain through different sensory modalities. For example, voices and faces both give information about the speech content, age, and gender of a person. Thanks to this redundancy, multimodal recognition is fast, robust, and automatic. In unimodal perception, however, only part of the information about an object is available. Here, we addressed whether, even under conditions of unimodal sensory input, crossmodal neural circuits that have been shaped by previous associative learning become activated and underpin a performance benefit. We measured brain activity with functional magnetic resonance imaging before, while, and after participants learned to associate either sensory redundant stimuli, i.e. voices and faces, or arbitrary multimodal combinations, i.e. voices and written names, ring tones, and cell phones or brand names of these cell phones. After learning, participants were better at recognizing unimodal auditory voices that had been paired with faces than those paired with written names, and association of voices with faces resulted in an increased functional coupling between voice and face areas. No such effects were observed for ring tones that had been paired with cell phones or names. These findings demonstrate that brief exposure to ecologically valid and sensory redundant stimulus pairs, such as voices and faces, induces specific multisensory associations. Consistent with predictive coding theories, associative representations become thereafter available for unimodal perception and facilitate object recognition. These data suggest that for natural objects effective predictive signals can be generated across sensory systems and proceed by optimization of functional connectivity between specialized cortical sensory modules.

Near infrared and visible face recognition based on decision fusion of LBP and DCT features

NASA Astrophysics Data System (ADS)

Xie, Zhihua; Zhang, Shuai; Liu, Guodong; Xiong, Jinquan

2018-03-01

Visible face recognition systems, being vulnerable to illumination, expression, and pose, can not achieve robust performance in unconstrained situations. Meanwhile, near infrared face images, being light- independent, can avoid or limit the drawbacks of face recognition in visible light, but its main challenges are low resolution and signal noise ratio (SNR). Therefore, near infrared and visible fusion face recognition has become an important direction in the field of unconstrained face recognition research. In order to extract the discriminative complementary features between near infrared and visible images, in this paper, we proposed a novel near infrared and visible face fusion recognition algorithm based on DCT and LBP features. Firstly, the effective features in near-infrared face image are extracted by the low frequency part of DCT coefficients and the partition histograms of LBP operator. Secondly, the LBP features of visible-light face image are extracted to compensate for the lacking detail features of the near-infrared face image. Then, the LBP features of visible-light face image, the DCT and LBP features of near-infrared face image are sent to each classifier for labeling. Finally, decision level fusion strategy is used to obtain the final recognition result. The visible and near infrared face recognition is tested on HITSZ Lab2 visible and near infrared face database. The experiment results show that the proposed method extracts the complementary features of near-infrared and visible face images and improves the robustness of unconstrained face recognition. Especially for the circumstance of small training samples, the recognition rate of proposed method can reach 96.13%, which has improved significantly than 92.75 % of the method based on statistical feature fusion.

Design and implementation of face recognition system based on Windows

NASA Astrophysics Data System (ADS)

Zhang, Min; Liu, Ting; Li, Ailan

2015-07-01

In view of the basic Windows login password input way lacking of safety and convenient operation, we will introduce the biometrics technology, face recognition, into the computer to login system. Not only can it encrypt the computer system, also according to the level to identify administrators at all levels. With the enhancement of the system security, user input can neither be a cumbersome nor worry about being stolen password confidential.

The Potential of Using Brain Images for Authentication

PubMed Central

Zhou, Zongtan; Shen, Hui; Hu, Dewen

2014-01-01

Biometric recognition (also known as biometrics) refers to the automated recognition of individuals based on their biological or behavioral traits. Examples of biometric traits include fingerprint, palmprint, iris, and face. The brain is the most important and complex organ in the human body. Can it be used as a biometric trait? In this study, we analyze the uniqueness of the brain and try to use the brain for identity authentication. The proposed brain-based verification system operates in two stages: gray matter extraction and gray matter matching. A modified brain segmentation algorithm is implemented for extracting gray matter from an input brain image. Then, an alignment-based matching algorithm is developed for brain matching. Experimental results on two data sets show that the proposed brain recognition system meets the high accuracy requirement of identity authentication. Though currently the acquisition of the brain is still time consuming and expensive, brain images are highly unique and have the potential possibility for authentication in view of pattern recognition. PMID:25126604

Cardiac imaging modalities with ionizing radiation: the role of informed consent.

PubMed

Paterick, Timothy E; Jan, M Fuad; Paterick, Zachary R; Tajik, A Jamil; Gerber, Thomas C

2012-06-01

Informed consent ideally results in patient autonomy and rational health care decisions. Frequently, patients face complex medical decisions that require a delicate balancing of anticipated benefits and potential risks, which is the concept of informed consent. This balancing process requires an understanding of available medical evidence and alternative medical options, and input from experienced physicians. The informed consent doctrine places a positive obligation on physicians to partner with patients as they try to make the best decision for their specific medical situation. The high prevalence and mortality related to heart disease in our society has led to increased cardiac imaging with modalities that use ionizing radiation. This paper reviews how physicians can meet the ideals of informed consent when considering cardiac imaging with ionizing radiation, given the limited evidence for risks and benefits. The goal is an informed patient making rational choices based on available medical information. Copyright © 2012 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

The potential of using brain images for authentication.

PubMed

Chen, Fanglin; Zhou, Zongtan; Shen, Hui; Hu, Dewen

2014-01-01

Biometric recognition (also known as biometrics) refers to the automated recognition of individuals based on their biological or behavioral traits. Examples of biometric traits include fingerprint, palmprint, iris, and face. The brain is the most important and complex organ in the human body. Can it be used as a biometric trait? In this study, we analyze the uniqueness of the brain and try to use the brain for identity authentication. The proposed brain-based verification system operates in two stages: gray matter extraction and gray matter matching. A modified brain segmentation algorithm is implemented for extracting gray matter from an input brain image. Then, an alignment-based matching algorithm is developed for brain matching. Experimental results on two data sets show that the proposed brain recognition system meets the high accuracy requirement of identity authentication. Though currently the acquisition of the brain is still time consuming and expensive, brain images are highly unique and have the potential possibility for authentication in view of pattern recognition.

Point-Wise Phase Matching for Nonlinear Frequency Generation in Dielectric Resonators

NASA Technical Reports Server (NTRS)

Yu, Nan (Inventor); Strekalov, Dmitry V. (Inventor); Lin, Guoping (Inventor)

2016-01-01

An optical resonator fabricated from a uniaxial birefringent crystal, such as beta barium borate. The crystal is cut with the optical axis not perpendicular to a face of the cut crystal. In some cases the optical axis lies in the plane of the cut crystal face. An incident (input) electromagnetic signal (which can range from the infrared through the visible to the ultraviolet) is applied to the resonator. An output signal is recovered which has a frequency that is an integer multiple of the frequency of the input signal. In some cases a prism is used to evanescently couple the input and the output signals to the resonator.

Energy conservation using face detection

NASA Astrophysics Data System (ADS)

Deotale, Nilesh T.; Kalbande, Dhananjay R.; Mishra, Akassh A.

2011-10-01

Computerized Face Detection, is concerned with the difficult task of converting a video signal of a person to written text. It has several applications like face recognition, simultaneous multiple face processing, biometrics, security, video surveillance, human computer interface, image database management, digital cameras use face detection for autofocus, selecting regions of interest in photo slideshows that use a pan-and-scale and The Present Paper deals with energy conservation using face detection. Automating the process to a computer requires the use of various image processing techniques. There are various methods that can be used for Face Detection such as Contour tracking methods, Template matching, Controlled background, Model based, Motion based and color based. Basically, the video of the subject are converted into images are further selected manually for processing. However, several factors like poor illumination, movement of face, viewpoint-dependent Physical appearance, Acquisition geometry, Imaging conditions, Compression artifacts makes Face detection difficult. This paper reports an algorithm for conservation of energy using face detection for various devices. The present paper suggests Energy Conservation can be done by Detecting the Face and reducing the brightness of complete image and then adjusting the brightness of the particular area of an image where the face is located using histogram equalization.

Amygdala habituation and prefrontal functional connectivity in youth with autism spectrum disorders.

PubMed

Swartz, Johnna R; Wiggins, Jillian Lee; Carrasco, Melisa; Lord, Catherine; Monk, Christopher S

2013-01-01

Amygdala habituation, the rapid decrease in amygdala responsiveness to the repeated presentation of stimuli, is fundamental to the nervous system. Habituation is important for maintaining adaptive levels of arousal to predictable social stimuli and decreased habituation is associated with heightened anxiety. Input from the ventromedial prefrontal cortex (vmPFC) regulates amygdala activity. Although previous research has shown abnormal amygdala function in youth with autism spectrum disorders (ASD), no study has examined amygdala habituation in a young sample or whether habituation is related to amygdala connectivity with the vmPFC. Data were analyzed from 32 children and adolescents with ASD and 56 typically developing controls who underwent functional magnetic resonance imaging while performing a gender identification task for faces that were fearful, happy, sad, or neutral. Habituation was tested by comparing amygdala activation to faces during the first half versus the second half of the session. VmPFC-amygdala connectivity was examined through psychophysiologic interaction analysis. Youth with ASD had decreased amygdala habituation to sad and neutral faces compared with controls. Moreover, decreased amygdala habituation correlated with autism severity as measured by the Social Responsiveness Scale. There was a group difference in vmPFC-amygdala connectivity while viewing sad faces, and connectivity predicted amygdala habituation to sad faces in controls. Sustained amygdala activation to faces suggests that repeated face presentations are processed differently in individuals with ASD, which could contribute to social impairments. Abnormal modulation of the amygdala by the vmPFC may play a role in decreased habituation. Copyright © 2013 American Academy of Child & Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Improving face image extraction by using deep learning technique

NASA Astrophysics Data System (ADS)

Xue, Zhiyun; Antani, Sameer; Long, L. R.; Demner-Fushman, Dina; Thoma, George R.

2016-03-01

The National Library of Medicine (NLM) has made a collection of over a 1.2 million research articles containing 3.2 million figure images searchable using the Open-iSM multimodal (text+image) search engine. Many images are visible light photographs, some of which are images containing faces ("face images"). Some of these face images are acquired in unconstrained settings, while others are studio photos. To extract the face regions in the images, we first applied one of the most widely-used face detectors, a pre-trained Viola-Jones detector implemented in Matlab and OpenCV. The Viola-Jones detector was trained for unconstrained face image detection, but the results for the NLM database included many false positives, which resulted in a very low precision. To improve this performance, we applied a deep learning technique, which reduced the number of false positives and as a result, the detection precision was improved significantly. (For example, the classification accuracy for identifying whether the face regions output by this Viola- Jones detector are true positives or not in a test set is about 96%.) By combining these two techniques (Viola-Jones and deep learning) we were able to increase the system precision considerably, while avoiding the need to manually construct a large training set by manual delineation of the face regions.

A New Experiment on Bengali Character Recognition

NASA Astrophysics Data System (ADS)

Barman, Sumana; Bhattacharyya, Debnath; Jeon, Seung-Whan; Kim, Tai-Hoon; Kim, Haeng-Kon

This paper presents a method to use View based approach in Bangla Optical Character Recognition (OCR) system providing reduced data set to the ANN classification engine rather than the traditional OCR methods. It describes how Bangla characters are processed, trained and then recognized with the use of a Backpropagation Artificial neural network. This is the first published account of using a segmentation-free optical character recognition system for Bangla using a view based approach. The methodology presented here assumes that the OCR pre-processor has presented the input images to the classification engine described here. The size and the font face used to render the characters are also significant in both training and classification. The images are first converted into greyscale and then to binary images; these images are then scaled to a fit a pre-determined area with a fixed but significant number of pixels. The feature vectors are then formed extracting the characteristics points, which in this case is simply a series of 0s and 1s of fixed length. Finally, an artificial neural network is chosen for the training and classification process.

High-Fidelity Microstructural Characterization and Performance Modeling of Aluminized Composite Propellant

DOE PAGES

Kosiba, Graham D.; Wixom, Ryan R.; Oehlschlaeger, Matthew A.

2017-10-27

Image processing and stereological techniques were used to characterize the heterogeneity of composite propellant and inform a predictive burn rate model. Composite propellant samples made up of ammonium perchlorate (AP), hydroxyl-terminated polybutadiene (HTPB), and aluminum (Al) were faced with an ion mill and imaged with a scanning electron microscope (SEM) and x-ray tomography (micro-CT). Properties of both the bulk and individual components of the composite propellant were determined from a variety of image processing tools. An algebraic model, based on the improved Beckstead-Derr-Price model developed by Cohen and Strand, was used to predict the steady-state burning of the aluminized compositemore » propellant. In the presented model the presence of aluminum particles within the propellant was introduced. The thermal effects of aluminum particles are accounted for at the solid-gas propellant surface interface and aluminum combustion is considered in the gas phase using a single global reaction. In conclusion, properties derived from image processing were used directly as model inputs, leading to a sample-specific predictive combustion model.« less

High-Fidelity Microstructural Characterization and Performance Modeling of Aluminized Composite Propellant

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kosiba, Graham D.; Wixom, Ryan R.; Oehlschlaeger, Matthew A.

Image processing and stereological techniques were used to characterize the heterogeneity of composite propellant and inform a predictive burn rate model. Composite propellant samples made up of ammonium perchlorate (AP), hydroxyl-terminated polybutadiene (HTPB), and aluminum (Al) were faced with an ion mill and imaged with a scanning electron microscope (SEM) and x-ray tomography (micro-CT). Properties of both the bulk and individual components of the composite propellant were determined from a variety of image processing tools. An algebraic model, based on the improved Beckstead-Derr-Price model developed by Cohen and Strand, was used to predict the steady-state burning of the aluminized compositemore » propellant. In the presented model the presence of aluminum particles within the propellant was introduced. The thermal effects of aluminum particles are accounted for at the solid-gas propellant surface interface and aluminum combustion is considered in the gas phase using a single global reaction. In conclusion, properties derived from image processing were used directly as model inputs, leading to a sample-specific predictive combustion model.« less

Self- or familiar-face recognition advantage? New insight using ambient images.

PubMed

Bortolon, Catherine; Lorieux, Siméon; Raffard, Stéphane

2018-06-01

Self-face recognition has been widely explored in the past few years. Nevertheless, the current literature relies on the use of standardized photographs which do not represent daily-life face recognition. Therefore, we aim for the first time to evaluate self-face processing in healthy individuals using natural/ambient images which contain variations in the environment and in the face itself. In total, 40 undergraduate and graduate students performed a forced delayed-matching task, including images of one's own face, friend, famous and unknown individuals. For both reaction time and accuracy, results showed that participants were faster and more accurate when matching different images of their own face compared to both famous and unfamiliar faces. Nevertheless, no significant differences were found between self-face and friend-face and between friend-face and famous-face. They were also faster and more accurate when matching friend and famous faces compared to unfamiliar faces. Our results suggest that faster and more accurate responses to self-face might be better explained by a familiarity effect - that is, (1) the result of frequent exposition to one's own image through mirror and photos, (2) a more robust mental representation of one's own face and (3) strong face recognition units as for other familiar faces.

iCATSI: multi-pixel imaging differential spectroradiometer for standoff detection and quantification of chemical threats

NASA Astrophysics Data System (ADS)

Prel, Florent; Moreau, Louis; Lavoie, Hugo; Bouffard, François; Thériault, Jean-Marc; Vallieres, Christian; Roy, Claude; Dubé, Denis

2011-11-01

Homeland security and first responders are often faced with safety situations involving the identification of unknown volatile chemicals. Examples include industrial fires, chemical warfare, industrial leak, etc. The Improved Compact ATmospheric Sounding Interferometer (iCATSI) sensor has been developed to investigate the standoff detection and identification of toxic industrial chemicals (TICs), chemical warfare agents (CWA) and other chemicals. iCATSI is a combination of the CATSI instrument, a standoff differential FTIR optimised for the characterization of chemicals and the MR-i, the hyperspectral imaging spectroradiometer of ABB Bomem based on the proven MR spectroradiometers. The instrument is equipped with a dual-input telescope to perform optical background subtraction. The resulting signal is the difference between the spectral radiance entering each input port. With that method, the signal from the background is automatically removed from the signal of the target of interest. The iCATSI sensor is able to detect, spectrally resolve and identify 5 meters plumes up to 5 km range. The instrument is capable of sensing in the VLWIR (cut-off near 14 μm) to support research related to standoff chemical detection. In one of its configurations, iCATSI produces three 24 × 16 spectral images per second from 5.5 to 14 μm at a spectral resolution of 16 cm-1. In another configuration, iCATSI produces from two to four spectral images per second of 256 × 256 pixels from 8 to 13 μm with the same spectral resolution. Overview of the capabilities of the instrument and results from tests and field trials will be presented.

Tweaked residual convolutional network for face alignment

NASA Astrophysics Data System (ADS)

Du, Wenchao; Li, Ke; Zhao, Qijun; Zhang, Yi; Chen, Hu

2017-08-01

We propose a novel Tweaked Residual Convolutional Network approach for face alignment with two-level convolutional networks architecture. Specifically, the first-level Tweaked Convolutional Network (TCN) module predicts the landmark quickly but accurately enough as a preliminary, by taking low-resolution version of the detected face holistically as the input. The following Residual Convolutional Networks (RCN) module progressively refines the landmark by taking as input the local patch extracted around the predicted landmark, particularly, which allows the Convolutional Neural Network (CNN) to extract local shape-indexed features to fine tune landmark position. Extensive evaluations show that the proposed Tweaked Residual Convolutional Network approach outperforms existing methods.

An analysis of whether a working-age ward-based liaison psychiatry service requires the input of a liaison psychiatrist.

PubMed

Guthrie, Elspeth A; McMeekin, Aaron T; Khan, Sylvia; Makin, Sally; Shaw, Ben; Longson, Damien

2017-06-01

Aims and method This article presents a 12-month case series to determine the fraction of ward referrals of adults of working age who needed a liaison psychiatrist in a busy tertiary referral teaching hospital. Results The service received 344 referrals resulting in 1259 face-to-face contacts. Depression accounted for the most face-to-face contacts. We deemed the involvement of a liaison psychiatrist necessary in 241 (70.1%) referrals, with medication management as the most common reason. Clinical implications A substantial amount of liaison ward work involves the treatment and management of severe and complex mental health problems. Our analysis suggests that in the majority of cases the input of a liaison psychiatrist is required.

Role of development in reorganization of the SI forelimb-stump representation in fetally, neonatally, and adult amputated rats.

PubMed

Pluto, Charles P; Lane, Richard D; Chiaia, Nicolas L; Stojic, Andrey S; Rhoades, Robert W

2003-09-01

Rats that sustain forelimb removal on postnatal day (P) 0 exhibit numerous multi-unit recording sites in the forelimb-stump representation of primary somatosensory cortex (SI) that also respond to hindlimb stimulation when cortical GABAA+B receptors are blocked. Most of these hindlimb inputs originate in the medial SI hindlimb representation. Although many forelimb-stump sites in these animals respond to hindlimb stimulation, very few respond to stimulation of the face (vibrissae or lower jaw), which is represented in SI just lateral to the forelimb. The lateral to medial development of SI may influence the capacity of hindlimb (but not face) inputs to "invade" the forelimb-stump region in neonatal amputees. The SI forelimb-stump was mapped in adult (>60 days) rats that had sustained amputation on embryonic day (E) 16, on P0, or during adulthood. GABA receptors were blocked and subsequent mapping revealed increases in nonstump inputs in E16 and P0 amputees: fetal amputees exhibited forelimb-stump sites responsive to face (34%), hindlimb (10%), and both (22%); neonatal amputees exhibited 10% face, 39% hindlimb, and 5% both; adult amputees exhibited 10% face, 5% hindlimb, and 0% both, with approximately 80% stump-only sites. These results indicate age-dependent differences in receptive-field reorganization of the forelimb-stump representation, which may reflect the spatiotemporal development of SI. Results from cobalt chloride inactivation of the SI vibrissae region and electrolesioning of the dysgranular cortex suggest that normally suppressed vibrissae inputs to the SI forelimb-stump area originate in the SI vibrissae region and synapse in the dysgranular cortex.

Interactive display system having a digital micromirror imaging device

DOEpatents

Veligdan, James T.; DeSanto, Leonard; Kaull, Lisa; Brewster, Calvin

2006-04-11

A display system includes a waveguide optical panel having an inlet face and an opposite outlet face. A projector cooperates with a digital imaging device, e.g. a digital micromirror imaging device, for projecting an image through the panel for display on the outlet face. The imaging device includes an array of mirrors tiltable between opposite display and divert positions. The display positions reflect an image light beam from the projector through the panel for display on the outlet face. The divert positions divert the image light beam away from the panel, and are additionally used for reflecting a probe light beam through the panel toward the outlet face. Covering a spot on the panel, e.g. with a finger, reflects the probe light beam back through the panel toward the inlet face for detection thereat and providing interactive capability.

Fast template matching with polynomials.

PubMed

Omachi, Shinichiro; Omachi, Masako

2007-08-01

Template matching is widely used for many applications in image and signal processing. This paper proposes a novel template matching algorithm, called algebraic template matching. Given a template and an input image, algebraic template matching efficiently calculates similarities between the template and the partial images of the input image, for various widths and heights. The partial image most similar to the template image is detected from the input image for any location, width, and height. In the proposed algorithm, a polynomial that approximates the template image is used to match the input image instead of the template image. The proposed algorithm is effective especially when the width and height of the template image differ from the partial image to be matched. An algorithm using the Legendre polynomial is proposed for efficient approximation of the template image. This algorithm not only reduces computational costs, but also improves the quality of the approximated image. It is shown theoretically and experimentally that the computational cost of the proposed algorithm is much smaller than the existing methods.

Video-based face recognition via convolutional neural networks

NASA Astrophysics Data System (ADS)

Bao, Tianlong; Ding, Chunhui; Karmoshi, Saleem; Zhu, Ming

2017-06-01

Face recognition has been widely studied recently while video-based face recognition still remains a challenging task because of the low quality and large intra-class variation of video captured face images. In this paper, we focus on two scenarios of video-based face recognition: 1)Still-to-Video(S2V) face recognition, i.e., querying a still face image against a gallery of video sequences; 2)Video-to-Still(V2S) face recognition, in contrast to S2V scenario. A novel method was proposed in this paper to transfer still and video face images to an Euclidean space by a carefully designed convolutional neural network, then Euclidean metrics are used to measure the distance between still and video images. Identities of still and video images that group as pairs are used as supervision. In the training stage, a joint loss function that measures the Euclidean distance between the predicted features of training pairs and expanding vectors of still images is optimized to minimize the intra-class variation while the inter-class variation is guaranteed due to the large margin of still images. Transferred features are finally learned via the designed convolutional neural network. Experiments are performed on COX face dataset. Experimental results show that our method achieves reliable performance compared with other state-of-the-art methods.

Performance evaluation of no-reference image quality metrics for face biometric images

NASA Astrophysics Data System (ADS)

Liu, Xinwei; Pedersen, Marius; Charrier, Christophe; Bours, Patrick

2018-03-01

The accuracy of face recognition systems is significantly affected by the quality of face sample images. The recent established standardization proposed several important aspects for the assessment of face sample quality. There are many existing no-reference image quality metrics (IQMs) that are able to assess natural image quality by taking into account similar image-based quality attributes as introduced in the standardization. However, whether such metrics can assess face sample quality is rarely considered. We evaluate the performance of 13 selected no-reference IQMs on face biometrics. The experimental results show that several of them can assess face sample quality according to the system performance. We also analyze the strengths and weaknesses of different IQMs as well as why some of them failed to assess face sample quality. Retraining an original IQM by using face database can improve the performance of such a metric. In addition, the contribution of this paper can be used for the evaluation of IQMs on other biometric modalities; furthermore, it can be used for the development of multimodality biometric IQMs.

A Method for En Face OCT Imaging of Subretinal Fluid in Age-Related Macular Degeneration

PubMed Central

Mohammad, Fatimah; Wanek, Justin; Zelkha, Ruth; Lim, Jennifer I.; Chen, Judy; Shahidi, Mahnaz

2014-01-01

Purpose. The purpose of the study is to report a method for en face imaging of subretinal fluid (SRF) due to age-related macular degeneration (AMD) based on spectral domain optical coherence tomography (SDOCT). Methods. High density SDOCT imaging was performed at two visits in 4 subjects with neovascular AMD and one healthy subject. En face OCT images of a retinal layer anterior to the retinal pigment epithelium were generated. Validity, repeatability, and utility of the method were established. Results. En face OCT images generated by manual and automatic segmentation were nearly indistinguishable and displayed similar regions of SRF. En face OCT images displayed uniform intensities and similar retinal vascular patterns in a healthy subject, while the size and appearance of a hypopigmented fibrotic scar in an AMD subject were similar at 2 visits. In AMD subjects, dark regions on en face OCT images corresponded to reduced or absent light reflectance due to SRF. On en face OCT images, a decrease in SRF areas with treatment was demonstrated and this corresponded with a reduction in the central subfield retinal thickness. Conclusion. En face OCT imaging is a promising tool for visualization and monitoring of SRF area due to disease progression and treatment. PMID:25478209

Kruskal-Wallis-based computationally efficient feature selection for face recognition.

PubMed

Ali Khan, Sajid; Hussain, Ayyaz; Basit, Abdul; Akram, Sheeraz

2014-01-01

Face recognition in today's technological world, and face recognition applications attain much more importance. Most of the existing work used frontal face images to classify face image. However these techniques fail when applied on real world face images. The proposed technique effectively extracts the prominent facial features. Most of the features are redundant and do not contribute to representing face. In order to eliminate those redundant features, computationally efficient algorithm is used to select the more discriminative face features. Extracted features are then passed to classification step. In the classification step, different classifiers are ensemble to enhance the recognition accuracy rate as single classifier is unable to achieve the high accuracy. Experiments are performed on standard face database images and results are compared with existing techniques.

The Effect of Early Visual Deprivation on the Development of Face Detection

ERIC Educational Resources Information Center

Mondloch, Catherine J.; Segalowitz, Sidney J.; Lewis, Terri L.; Dywan, Jane; Le Grand, Richard; Maurer, Daphne

2013-01-01

The expertise of adults in face perception is facilitated by their ability to rapidly detect that a stimulus is a face. In two experiments, we examined the role of early visual input in the development of face detection by testing patients who had been treated as infants for bilateral congenital cataract. Experiment 1 indicated that, at age 9 to…

Holistic Face Categorization in Higher Order Visual Areas of the Normal and Prosopagnosic Brain: Toward a Non-Hierarchical View of Face Perception

PubMed Central

Rossion, Bruno; Dricot, Laurence; Goebel, Rainer; Busigny, Thomas

2011-01-01

How a visual stimulus is initially categorized as a face in a network of human brain areas remains largely unclear. Hierarchical neuro-computational models of face perception assume that the visual stimulus is first decomposed in local parts in lower order visual areas. These parts would then be combined into a global representation in higher order face-sensitive areas of the occipito-temporal cortex. Here we tested this view in fMRI with visual stimuli that are categorized as faces based on their global configuration rather than their local parts (two-tones Mooney figures and Arcimboldo's facelike paintings). Compared to the same inverted visual stimuli that are not categorized as faces, these stimuli activated the right middle fusiform gyrus (“Fusiform face area”) and superior temporal sulcus (pSTS), with no significant activation in the posteriorly located inferior occipital gyrus (i.e., no “occipital face area”). This observation is strengthened by behavioral and neural evidence for normal face categorization of these stimuli in a brain-damaged prosopagnosic patient whose intact right middle fusiform gyrus and superior temporal sulcus are devoid of any potential face-sensitive inputs from the lesioned right inferior occipital cortex. Together, these observations indicate that face-preferential activation may emerge in higher order visual areas of the right hemisphere without any face-preferential inputs from lower order visual areas, supporting a non-hierarchical view of face perception in the visual cortex. PMID:21267432

Fourier power spectrum characteristics of face photographs: attractiveness perception depends on low-level image properties.

PubMed

Menzel, Claudia; Hayn-Leichsenring, Gregor U; Langner, Oliver; Wiese, Holger; Redies, Christoph

2015-01-01

We investigated whether low-level processed image properties that are shared by natural scenes and artworks - but not veridical face photographs - affect the perception of facial attractiveness and age. Specifically, we considered the slope of the radially averaged Fourier power spectrum in a log-log plot. This slope is a measure of the distribution of special frequency power in an image. Images of natural scenes and artworks possess - compared to face images - a relatively shallow slope (i.e., increased high spatial frequency power). Since aesthetic perception might be based on the efficient processing of images with natural scene statistics, we assumed that the perception of facial attractiveness might also be affected by these properties. We calculated Fourier slope and other beauty-associated measurements in face images and correlated them with ratings of attractiveness and age of the depicted persons (Study 1). We found that Fourier slope - in contrast to the other tested image properties - did not predict attractiveness ratings when we controlled for age. In Study 2A, we overlaid face images with random-phase patterns with different statistics. Patterns with a slope similar to those in natural scenes and artworks resulted in lower attractiveness and higher age ratings. In Studies 2B and 2C, we directly manipulated the Fourier slope of face images and found that images with shallower slopes were rated as more attractive. Additionally, attractiveness of unaltered faces was affected by the Fourier slope of a random-phase background (Study 3). Faces in front of backgrounds with statistics similar to natural scenes and faces were rated as more attractive. We conclude that facial attractiveness ratings are affected by specific image properties. An explanation might be the efficient coding hypothesis.

Fourier Power Spectrum Characteristics of Face Photographs: Attractiveness Perception Depends on Low-Level Image Properties

PubMed Central

Langner, Oliver; Wiese, Holger; Redies, Christoph

2015-01-01

We investigated whether low-level processed image properties that are shared by natural scenes and artworks – but not veridical face photographs – affect the perception of facial attractiveness and age. Specifically, we considered the slope of the radially averaged Fourier power spectrum in a log-log plot. This slope is a measure of the distribution of special frequency power in an image. Images of natural scenes and artworks possess – compared to face images – a relatively shallow slope (i.e., increased high spatial frequency power). Since aesthetic perception might be based on the efficient processing of images with natural scene statistics, we assumed that the perception of facial attractiveness might also be affected by these properties. We calculated Fourier slope and other beauty-associated measurements in face images and correlated them with ratings of attractiveness and age of the depicted persons (Study 1). We found that Fourier slope – in contrast to the other tested image properties – did not predict attractiveness ratings when we controlled for age. In Study 2A, we overlaid face images with random-phase patterns with different statistics. Patterns with a slope similar to those in natural scenes and artworks resulted in lower attractiveness and higher age ratings. In Studies 2B and 2C, we directly manipulated the Fourier slope of face images and found that images with shallower slopes were rated as more attractive. Additionally, attractiveness of unaltered faces was affected by the Fourier slope of a random-phase background (Study 3). Faces in front of backgrounds with statistics similar to natural scenes and faces were rated as more attractive. We conclude that facial attractiveness ratings are affected by specific image properties. An explanation might be the efficient coding hypothesis. PMID:25835539

Comparison greenhouse gas (GHG) emissions and global warming potential (GWP) effect of energy use in different wheat agroecosystems in Iran.

PubMed

Yousefi, Mohammad; Mahdavi Damghani, Abdolmajid; Khoramivafa, Mahmud

2016-04-01

The aims of this study were to determine energy requirement and global warming potential (GWP) in low and high input wheat production systems in western of Iran. For this purpose, data were collected from 120 wheat farms applying questionnaires via face-to-face interviews. Results showed that total energy input and output were 60,000 and 180,000 MJ ha(-1) in high input systems and 14,000 and 56,000 MJ ha(-1) in low input wheat production systems, respectively. The highest share of total input energy in high input systems recorded for electricity power, N fertilizer, and diesel fuel with 36, 18, and 13 %, respectively, while the highest share of input energy in low input systems observed for N fertilizer, diesel fuel, and seed with 32, 31, and 27 %. Energy use efficiency in high input systems (3.03) was lower than of low input systems (3.94). Total CO2, N2O, and CH4 emissions in high input systems were 1981.25, 31.18, and 1.87 kg ha(-1), respectively. These amounts were 699.88, 0.02, and 0.96 kg ha(-1) in low input systems. In high input wheat production systems, total GWP was 11686.63 kg CO2eq ha(-1) wheat. This amount was 725.89 kg CO2eq ha(-1) in low input systems. The results show that 1 ha of high input system will produce greenhouse effect 17 times of low input systems. So, high input production systems need to have an efficient and sustainable management for reducing environmental crises such as change climate.

Optical power splitter for splitting high power light

DOEpatents

English, Jr., Ronald E.; Christensen, John J.

1995-01-01

An optical power splitter for the distribution of high-power light energy has a plurality of prisms arranged about a central axis to form a central channel. The input faces of the prisms are in a common plane which is substantially perpendicular to the central axis. A beam of light which is substantially coaxial to the central axis is incident on the prisms and at least partially strikes a surface area of each prism input face. The incident beam also partially passes through the central channel.

Can the usage of human growth hormones affect facial appearance and the accuracy of face recognition systems?

NASA Astrophysics Data System (ADS)

Rose, Jake; Martin, Michael; Bourlai, Thirimachos

2014-06-01

In law enforcement and security applications, the acquisition of face images is critical in producing key trace evidence for the successful identification of potential threats. The goal of the study is to demonstrate that steroid usage significantly affects human facial appearance and hence, the performance of commercial and academic face recognition (FR) algorithms. In this work, we evaluate the performance of state-of-the-art FR algorithms on two unique face image datasets of subjects before (gallery set) and after (probe set) steroid (or human growth hormone) usage. For the purpose of this study, datasets of 73 subjects were created from multiple sources found on the Internet, containing images of men and women before and after steroid usage. Next, we geometrically pre-processed all images of both face datasets. Then, we applied image restoration techniques on the same face datasets, and finally, we applied FR algorithms in order to match the pre-processed face images of our probe datasets against the face images of the gallery set. Experimental results demonstrate that only a specific set of FR algorithms obtain the most accurate results (in terms of the rank-1 identification rate). This is because there are several factors that influence the efficiency of face matchers including (i) the time lapse between the before and after image pre-processing and restoration face photos, (ii) the usage of different drugs (e.g. Dianabol, Winstrol, and Decabolan), (iii) the usage of different cameras to capture face images, and finally, (iv) the variability of standoff distance, illumination and other noise factors (e.g. motion noise). All of the previously mentioned complicated scenarios make clear that cross-scenario matching is a very challenging problem and, thus, further investigation is required.

Two-step superresolution approach for surveillance face image through radial basis function-partial least squares regression and locality-induced sparse representation

NASA Astrophysics Data System (ADS)

Jiang, Junjun; Hu, Ruimin; Han, Zhen; Wang, Zhongyuan; Chen, Jun

2013-10-01

Face superresolution (SR), or face hallucination, refers to the technique of generating a high-resolution (HR) face image from a low-resolution (LR) one with the help of a set of training examples. It aims at transcending the limitations of electronic imaging systems. Applications of face SR include video surveillance, in which the individual of interest is often far from cameras. A two-step method is proposed to infer a high-quality and HR face image from a low-quality and LR observation. First, we establish the nonlinear relationship between LR face images and HR ones, according to radial basis function and partial least squares (RBF-PLS) regression, to transform the LR face into the global face space. Then, a locality-induced sparse representation (LiSR) approach is presented to enhance the local facial details once all the global faces for each LR training face are constructed. A comparison of some state-of-the-art SR methods shows the superiority of the proposed two-step approach, RBF-PLS global face regression followed by LiSR-based local patch reconstruction. Experiments also demonstrate the effectiveness under both simulation conditions and some real conditions.

Age and gender classification in the wild with unsupervised feature learning

NASA Astrophysics Data System (ADS)

Wan, Lihong; Huo, Hong; Fang, Tao

2017-03-01

Inspired by unsupervised feature learning (UFL) within the self-taught learning framework, we propose a method based on UFL, convolution representation, and part-based dimensionality reduction to handle facial age and gender classification, which are two challenging problems under unconstrained circumstances. First, UFL is introduced to learn selective receptive fields (filters) automatically by applying whitening transformation and spherical k-means on random patches collected from unlabeled data. The learning process is fast and has no hyperparameters to tune. Then, the input image is convolved with these filters to obtain filtering responses on which local contrast normalization is applied. Average pooling and feature concatenation are then used to form global face representation. Finally, linear discriminant analysis with part-based strategy is presented to reduce the dimensions of the global representation and to improve classification performances further. Experiments on three challenging databases, namely, Labeled faces in the wild, Gallagher group photos, and Adience, demonstrate the effectiveness of the proposed method relative to that of state-of-the-art approaches.

Processing of Fear and Anger Facial Expressions: The Role of Spatial Frequency

PubMed Central

Comfort, William E.; Wang, Meng; Benton, Christopher P.; Zana, Yossi

2013-01-01

Spatial frequency (SF) components encode a portion of the affective value expressed in face images. The aim of this study was to estimate the relative weight of specific frequency spectrum bandwidth on the discrimination of anger and fear facial expressions. The general paradigm was a classification of the expression of faces morphed at varying proportions between anger and fear images in which SF adaptation and SF subtraction are expected to shift classification of facial emotion. A series of three experiments was conducted. In Experiment 1 subjects classified morphed face images that were unfiltered or filtered to remove either low (<8 cycles/face), middle (12–28 cycles/face), or high (>32 cycles/face) SF components. In Experiment 2 subjects were adapted to unfiltered or filtered prototypical (non-morphed) fear face images and subsequently classified morphed face images. In Experiment 3 subjects were adapted to unfiltered or filtered prototypical fear face images with the phase component randomized before classifying morphed face images. Removing mid frequency components from the target images shifted classification toward fear. The same shift was observed under adaptation condition to unfiltered and low- and middle-range filtered fear images. However, when the phase spectrum of the same adaptation stimuli was randomized, no adaptation effect was observed. These results suggest that medium SF components support the perception of fear more than anger at both low and high level of processing. They also suggest that the effect at high-level processing stage is related more to high-level featural and/or configural information than to the low-level frequency spectrum. PMID:23637687

Engineering the Ideal Gigapixel Image Viewer

NASA Astrophysics Data System (ADS)

Perpeet, D. Wassenberg, J.

2011-09-01

Despite improvements in automatic processing, analysts are still faced with the task of evaluating gigapixel-scale mosaics or images acquired by telescopes such as Pan-STARRS. Displaying such images in ‘ideal’ form is a major challenge even today, and the amount of data will only increase as sensor resolutions improve. In our opinion, the ideal viewer has several key characteristics. Lossless display - down to individual pixels - ensures all information can be extracted from the image. Support for all relevant pixel formats (integer or floating point) allows displaying data from different sensors. Smooth zooming and panning in the high-resolution data enables rapid screening and navigation in the image. High responsiveness to input commands avoids frustrating delays. Instantaneous image enhancement, e.g. contrast adjustment and image channel selection, helps with analysis tasks. Modest system requirements allow viewing on regular workstation computers or even laptops. To the best of our knowledge, no such software product is currently available. Meeting these goals requires addressing certain realities of current computer architectures. GPU hardware accelerates rendering and allows smooth zooming without high CPU load. Programmable GPU shaders enable instant channel selection and contrast adjustment without any perceptible slowdown or changes to the input data. Relatively low disk transfer speeds suggest the use of compression to decrease the amount of data to transfer. Asynchronous I/O allows decompressing while waiting for previous I/O operations to complete. The slow seek times of magnetic disks motivate optimizing the order of the data on disk. Vectorization and parallelization allow significant increases in computational capacity. Limited memory requires streaming and caching of image regions. We develop a viewer that takes the above issues into account. Its awareness of the computer architecture enables previously unattainable features such as smooth zooming and image enhancement within high-resolution data. We describe our implementation, disclosing its novel file format and lossless image codec whose decompression is faster than copying the raw data in memory. Both provide crucial performance boosts compared to conventional approaches. Usability tests demonstrate the suitability of our viewer for rapid analysis of large SAR datasets, multispectral satellite imagery and mosaics.

Temporal Tuning of Word- and Face-selective Cortex.

PubMed

Yeatman, Jason D; Norcia, Anthony M

2016-11-01

Sensitivity to temporal change places fundamental limits on object processing in the visual system. An emerging consensus from the behavioral and neuroimaging literature suggests that temporal resolution differs substantially for stimuli of different complexity and for brain areas at different levels of the cortical hierarchy. Here, we used steady-state visually evoked potentials to directly measure three fundamental parameters that characterize the underlying neural response to text and face images: temporal resolution, peak temporal frequency, and response latency. We presented full-screen images of text or a human face, alternated with a scrambled image, at temporal frequencies between 1 and 12 Hz. These images elicited a robust response at the first harmonic that showed differential tuning, scalp topography, and delay for the text and face images. Face-selective responses were maximal at 4 Hz, but text-selective responses, by contrast, were maximal at 1 Hz. The topography of the text image response was strongly left-lateralized at higher stimulation rates, whereas the response to the face image was slightly right-lateralized but nearly bilateral at all frequencies. Both text and face images elicited steady-state activity at more than one apparent latency; we observed early (141-160 msec) and late (>250 msec) text- and face-selective responses. These differences in temporal tuning profiles are likely to reflect differences in the nature of the computations performed by word- and face-selective cortex. Despite the close proximity of word- and face-selective regions on the cortical surface, our measurements demonstrate substantial differences in the temporal dynamics of word- versus face-selective responses.

A Method of Face Detection with Bayesian Probability

NASA Astrophysics Data System (ADS)

Sarker, Goutam

2010-10-01

The objective of face detection is to identify all images which contain a face, irrespective of its orientation, illumination conditions etc. This is a hard problem, because the faces are highly variable in size, shape lighting conditions etc. Many methods have been designed and developed to detect faces in a single image. The present paper is based on one `Appearance Based Method' which relies on learning the facial and non facial features from image examples. This in its turn is based on statistical analysis of examples and counter examples of facial images and employs Bayesian Conditional Classification Rule to detect the probability of belongingness of a face (or non-face) within an image frame. The detection rate of the present system is very high and thereby the number of false positive and false negative detection is substantially low.

Enhanced Visualization of Subtle Outer Retinal Pathology by En Face Optical Coherence Tomography and Correlation with Multi-Modal Imaging

PubMed Central

Chew, Avenell L.; Lamey, Tina; McLaren, Terri; De Roach, John

2016-01-01

Purpose To present en face optical coherence tomography (OCT) images generated by graph-search theory algorithm-based custom software and examine correlation with other imaging modalities. Methods En face OCT images derived from high density OCT volumetric scans of 3 healthy subjects and 4 patients using a custom algorithm (graph-search theory) and commercial software (Heidelberg Eye Explorer software (Heidelberg Engineering)) were compared and correlated with near infrared reflectance, fundus autofluorescence, adaptive optics flood-illumination ophthalmoscopy (AO-FIO) and microperimetry. Results Commercial software was unable to generate accurate en face OCT images in eyes with retinal pigment epithelium (RPE) pathology due to segmentation error at the level of Bruch’s membrane (BM). Accurate segmentation of the basal RPE and BM was achieved using custom software. The en face OCT images from eyes with isolated interdigitation or ellipsoid zone pathology were of similar quality between custom software and Heidelberg Eye Explorer software in the absence of any other significant outer retinal pathology. En face OCT images demonstrated angioid streaks, lesions of acute macular neuroretinopathy, hydroxychloroquine toxicity and Bietti crystalline deposits that correlated with other imaging modalities. Conclusions Graph-search theory algorithm helps to overcome the limitations of outer retinal segmentation inaccuracies in commercial software. En face OCT images can provide detailed topography of the reflectivity within a specific layer of the retina which correlates with other forms of fundus imaging. Our results highlight the need for standardization of image reflectivity to facilitate quantification of en face OCT images and longitudinal analysis. PMID:27959968

Implicit Multisensory Associations Influence Voice Recognition

PubMed Central

von Kriegstein, Katharina; Giraud, Anne-Lise

2006-01-01

Natural objects provide partially redundant information to the brain through different sensory modalities. For example, voices and faces both give information about the speech content, age, and gender of a person. Thanks to this redundancy, multimodal recognition is fast, robust, and automatic. In unimodal perception, however, only part of the information about an object is available. Here, we addressed whether, even under conditions of unimodal sensory input, crossmodal neural circuits that have been shaped by previous associative learning become activated and underpin a performance benefit. We measured brain activity with functional magnetic resonance imaging before, while, and after participants learned to associate either sensory redundant stimuli, i.e. voices and faces, or arbitrary multimodal combinations, i.e. voices and written names, ring tones, and cell phones or brand names of these cell phones. After learning, participants were better at recognizing unimodal auditory voices that had been paired with faces than those paired with written names, and association of voices with faces resulted in an increased functional coupling between voice and face areas. No such effects were observed for ring tones that had been paired with cell phones or names. These findings demonstrate that brief exposure to ecologically valid and sensory redundant stimulus pairs, such as voices and faces, induces specific multisensory associations. Consistent with predictive coding theories, associative representations become thereafter available for unimodal perception and facilitate object recognition. These data suggest that for natural objects effective predictive signals can be generated across sensory systems and proceed by optimization of functional connectivity between specialized cortical sensory modules. PMID:17002519

A Within-subjects Experimental Protocol to Assess the Effects of Social Input on Infant EEG.

PubMed

St John, Ashley M; Kao, Katie; Chita-Tegmark, Meia; Liederman, Jacqueline; Grieve, Philip G; Tarullo, Amanda R

2017-05-03

Despite the importance of social interactions for infant brain development, little research has assessed functional neural activation while infants socially interact. Electroencephalography (EEG) power is an advantageous technique to assess infant functional neural activation. However, many studies record infant EEG only during one baseline condition. This protocol describes a paradigm that is designed to comprehensively assess infant EEG activity in both social and nonsocial contexts as well as tease apart how different types of social inputs differentially relate to infant EEG. The within-subjects paradigm includes four controlled conditions. In the nonsocial condition, infants view objects on computer screens. The joint attention condition involves an experimenter directing the infant's attention to pictures. The joint attention condition includes three types of social input: language, face-to-face interaction, and the presence of joint attention. Differences in infant EEG between the nonsocial and joint attention conditions could be due to any of these three types of input. Therefore, two additional conditions (one with language input while the experimenter is hidden behind a screen and one with face-to-face interaction) were included to assess the driving contextual factors in patterns of infant neural activation. Representative results demonstrate that infant EEG power varied by condition, both overall and differentially by brain region, supporting the functional nature of infant EEG power. This technique is advantageous in that it includes conditions that are clearly social or nonsocial and allows for examination of how specific types of social input relate to EEG power. This paradigm can be used to assess how individual differences in age, affect, socioeconomic status, and parent-infant interaction quality relate to the development of the social brain. Based on the demonstrated functional nature of infant EEG power, future studies should consider the role of EEG recording context and design conditions that are clearly social or nonsocial.

A multi-camera system for real-time pose estimation

NASA Astrophysics Data System (ADS)

Savakis, Andreas; Erhard, Matthew; Schimmel, James; Hnatow, Justin

2007-04-01

This paper presents a multi-camera system that performs face detection and pose estimation in real-time and may be used for intelligent computing within a visual sensor network for surveillance or human-computer interaction. The system consists of a Scene View Camera (SVC), which operates at a fixed zoom level, and an Object View Camera (OVC), which continuously adjusts its zoom level to match objects of interest. The SVC is set to survey the whole filed of view. Once a region has been identified by the SVC as a potential object of interest, e.g. a face, the OVC zooms in to locate specific features. In this system, face candidate regions are selected based on skin color and face detection is accomplished using a Support Vector Machine classifier. The locations of the eyes and mouth are detected inside the face region using neural network feature detectors. Pose estimation is performed based on a geometrical model, where the head is modeled as a spherical object that rotates upon the vertical axis. The triangle formed by the mouth and eyes defines a vertical plane that intersects the head sphere. By projecting the eyes-mouth triangle onto a two dimensional viewing plane, equations were obtained that describe the change in its angles as the yaw pose angle increases. These equations are then combined and used for efficient pose estimation. The system achieves real-time performance for live video input. Testing results assessing system performance are presented for both still images and video.

Adapting Local Features for Face Detection in Thermal Image.

PubMed

Ma, Chao; Trung, Ngo Thanh; Uchiyama, Hideaki; Nagahara, Hajime; Shimada, Atsushi; Taniguchi, Rin-Ichiro

2017-11-27

A thermal camera captures the temperature distribution of a scene as a thermal image. In thermal images, facial appearances of different people under different lighting conditions are similar. This is because facial temperature distribution is generally constant and not affected by lighting condition. This similarity in face appearances is advantageous for face detection. To detect faces in thermal images, cascade classifiers with Haar-like features are generally used. However, there are few studies exploring the local features for face detection in thermal images. In this paper, we introduce two approaches relying on local features for face detection in thermal images. First, we create new feature types by extending Multi-Block LBP. We consider a margin around the reference and the generally constant distribution of facial temperature. In this way, we make the features more robust to image noise and more effective for face detection in thermal images. Second, we propose an AdaBoost-based training method to get cascade classifiers with multiple types of local features. These feature types have different advantages. In this way we enhance the description power of local features. We did a hold-out validation experiment and a field experiment. In the hold-out validation experiment, we captured a dataset from 20 participants, comprising 14 males and 6 females. For each participant, we captured 420 images with 10 variations in camera distance, 21 poses, and 2 appearances (participant with/without glasses). We compared the performance of cascade classifiers trained by different sets of the features. The experiment results showed that the proposed approaches effectively improve the performance of face detection in thermal images. In the field experiment, we compared the face detection performance in realistic scenes using thermal and RGB images, and gave discussion based on the results.

Image dependency in the recognition of newly learnt faces.

PubMed

Longmore, Christopher A; Santos, Isabel M; Silva, Carlos F; Hall, Abi; Faloyin, Dipo; Little, Emily

2017-05-01

Research investigating the effect of lighting and viewpoint changes on unfamiliar and newly learnt faces has revealed that such recognition is highly image dependent and that changes in either of these leads to poor recognition accuracy. Three experiments are reported to extend these findings by examining the effect of apparent age on the recognition of newly learnt faces. Experiment 1 investigated the ability to generalize to novel ages of a face after learning a single image. It was found that recognition was best for the learnt image with performance falling the greater the dissimilarity between the study and test images. Experiments 2 and 3 examined whether learning two images aids subsequent recognition of a novel image. The results indicated that interpolation between two studied images (Experiment 2) provided some additional benefit over learning a single view, but that this did not extend to extrapolation (Experiment 3). The results from all studies suggest that recognition was driven primarily by pictorial codes and that the recognition of faces learnt from a limited number of sources operates on stored images of faces as opposed to more abstract, structural, representations.

Experimental Optoelectronic Associative Memory

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

1992-01-01

Optoelectronic associative memory responds to input image by displaying one of M remembered images. Which image to display determined by optoelectronic analog computation of resemblance between input image and each remembered image. Does not rely on precomputation and storage of outer-product synapse matrix. Size of memory needed to store and process images reduced.

Neural network face recognition using wavelets

NASA Astrophysics Data System (ADS)

Karunaratne, Passant V.; Jouny, Ismail I.

1997-04-01

The recognition of human faces is a phenomenon that has been mastered by the human visual system and that has been researched extensively in the domain of computer neural networks and image processing. This research is involved in the study of neural networks and wavelet image processing techniques in the application of human face recognition. The objective of the system is to acquire a digitized still image of a human face, carry out pre-processing on the image as required, an then, given a prior database of images of possible individuals, be able to recognize the individual in the image. The pre-processing segment of the system includes several procedures, namely image compression, denoising, and feature extraction. The image processing is carried out using Daubechies wavelets. Once the images have been passed through the wavelet-based image processor they can be efficiently analyzed by means of a neural network. A back- propagation neural network is used for the recognition segment of the system. The main constraints of the system is with regard to the characteristics of the images being processed. The system should be able to carry out effective recognition of the human faces irrespective of the individual's facial-expression, presence of extraneous objects such as head-gear or spectacles, and face/head orientation. A potential application of this face recognition system would be as a secondary verification method in an automated teller machine.

Processing deficits for familiar and novel faces in patients with left posterior fusiform lesions.

PubMed

Roberts, Daniel J; Lambon Ralph, Matthew A; Kim, Esther; Tainturier, Marie-Josephe; Beeson, Pelagie M; Rapcsak, Steven Z; Woollams, Anna M

2015-11-01

Pure alexia (PA) arises from damage to the left posterior fusiform gyrus (pFG) and the striking reading disorder that defines this condition has meant that such patients are often cited as evidence for the specialisation of this region to processing of written words. There is, however, an alternative view that suggests this region is devoted to processing of high acuity foveal input, which is particularly salient for complex visual stimuli like letter strings. Previous reports have highlighted disrupted processing of non-linguistic visual stimuli after damage to the left pFG, both for familiar and unfamiliar objects and also for novel faces. This study explored the nature of face processing deficits in patients with left pFG damage. Identification of famous faces was found to be compromised in both expressive and receptive tasks. Discrimination of novel faces was also impaired, particularly for those that varied in terms of second-order spacing information, and this deficit was most apparent for the patients with the more severe reading deficits. Interestingly, discrimination of faces that varied in terms of feature identity was considerably better in these patients and it was performance in this condition that was related to the size of the length effects shown in reading. This finding complements functional imaging studies showing left pFG activation for faces varying only in spacing and frontal activation for faces varying only on features. These results suggest that the sequential part-based processing strategy that promotes the length effect in the reading of these patients also allows them to discriminate between faces on the basis of feature identity, but processing of second-order configural information is most compromised due to their left pFG lesion. This study supports a view in which the left pFG is specialised for processing of high acuity foveal visual information that supports processing of both words and faces. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Processing deficits for familiar and novel faces in patients with left posterior fusiform lesions

PubMed Central

Roberts, Daniel J.; Lambon Ralph, Matthew A.; Kim, Esther; Tainturier, Marie-Josephe; Beeson, Pelagie M.; Rapcsak, Steven Z.; Woollams, Anna M.

2015-01-01

Pure alexia (PA) arises from damage to the left posterior fusiform gyrus (pFG) and the striking reading disorder that defines this condition has meant that such patients are often cited as evidence for the specialisation of this region to processing of written words. There is, however, an alternative view that suggests this region is devoted to processing of high acuity foveal input, which is particularly salient for complex visual stimuli like letter strings. Previous reports have highlighted disrupted processing of non-linguistic visual stimuli after damage to the left pFG, both for familiar and unfamiliar objects and also for novel faces. This study explored the nature of face processing deficits in patients with left pFG damage. Identification of famous faces was found to be compromised in both expressive and receptive tasks. Discrimination of novel faces was also impaired, particularly for those that varied in terms of second-order spacing information, and this deficit was most apparent for the patients with the more severe reading deficits. Interestingly, discrimination of faces that varied in terms of feature identity was considerably better in these patients and it was performance in this condition that was related to the size of the length effects shown in reading. This finding complements functional imaging studies showing left pFG activation for faces varying only in spacing and frontal activation for faces varying only on features. These results suggest that the sequential part-based processing strategy that promotes the length effect in the reading of these patients also allows them to discriminate between faces on the basis of feature identity, but processing of second-order configural information is most compromised due to their left pFG lesion. This study supports a view in which the left pFG is specialised for processing of high acuity foveal visual information that supports processing of both words and faces. PMID:25837867

Face-n-Food: Gender Differences in Tuning to Faces.

PubMed

Pavlova, Marina A; Scheffler, Klaus; Sokolov, Alexander N

2015-01-01

Faces represent valuable signals for social cognition and non-verbal communication. A wealth of research indicates that women tend to excel in recognition of facial expressions. However, it remains unclear whether females are better tuned to faces. We presented healthy adult females and males with a set of newly created food-plate images resembling faces (slightly bordering on the Giuseppe Arcimboldo style). In a spontaneous recognition task, participants were shown a set of images in a predetermined order from the least to most resembling a face. Females not only more readily recognized the images as a face (they reported resembling a face on images, on which males still did not), but gave on overall more face responses. The findings are discussed in the light of gender differences in deficient face perception. As most neuropsychiatric, neurodevelopmental and psychosomatic disorders characterized by social brain abnormalities are sex specific, the task may serve as a valuable tool for uncovering impairments in visual face processing.

Face-n-Food: Gender Differences in Tuning to Faces

PubMed Central

Pavlova, Marina A.; Scheffler, Klaus; Sokolov, Alexander N.

2015-01-01

Faces represent valuable signals for social cognition and non-verbal communication. A wealth of research indicates that women tend to excel in recognition of facial expressions. However, it remains unclear whether females are better tuned to faces. We presented healthy adult females and males with a set of newly created food-plate images resembling faces (slightly bordering on the Giuseppe Arcimboldo style). In a spontaneous recognition task, participants were shown a set of images in a predetermined order from the least to most resembling a face. Females not only more readily recognized the images as a face (they reported resembling a face on images, on which males still did not), but gave on overall more face responses. The findings are discussed in the light of gender differences in deficient face perception. As most neuropsychiatric, neurodevelopmental and psychosomatic disorders characterized by social brain abnormalities are sex specific, the task may serve as a valuable tool for uncovering impairments in visual face processing. PMID:26154177

Infant Face Preferences after Binocular Visual Deprivation

ERIC Educational Resources Information Center

Mondloch, Catherine J.; Lewis, Terri L.; Levin, Alex V.; Maurer, Daphne

2013-01-01

Early visual deprivation impairs some, but not all, aspects of face perception. We investigated the possible developmental roots of later abnormalities by using a face detection task to test infants treated for bilateral congenital cataract within 1 hour of their first focused visual input. The seven patients were between 5 and 12 weeks old…

Infant perceptual development for faces and spoken words: An integrated approach

PubMed Central

Watson, Tamara L; Robbins, Rachel A; Best, Catherine T

2014-01-01

There are obvious differences between recognizing faces and recognizing spoken words or phonemes that might suggest development of each capability requires different skills. Recognizing faces and perceiving spoken language, however, are in key senses extremely similar endeavors. Both perceptual processes are based on richly variable, yet highly structured input from which the perceiver needs to extract categorically meaningful information. This similarity could be reflected in the perceptual narrowing that occurs within the first year of life in both domains. We take the position that the perceptual and neurocognitive processes by which face and speech recognition develop are based on a set of common principles. One common principle is the importance of systematic variability in the input as a source of information rather than noise. Experience of this variability leads to perceptual tuning to the critical properties that define individual faces or spoken words versus their membership in larger groupings of people and their language communities. We argue that parallels can be drawn directly between the principles responsible for the development of face and spoken language perception. PMID:25132626

Face recognition system using multiple face model of hybrid Fourier feature under uncontrolled illumination variation.

PubMed

Hwang, Wonjun; Wang, Haitao; Kim, Hyunwoo; Kee, Seok-Cheol; Kim, Junmo

2011-04-01

The authors present a robust face recognition system for large-scale data sets taken under uncontrolled illumination variations. The proposed face recognition system consists of a novel illumination-insensitive preprocessing method, a hybrid Fourier-based facial feature extraction, and a score fusion scheme. First, in the preprocessing stage, a face image is transformed into an illumination-insensitive image, called an "integral normalized gradient image," by normalizing and integrating the smoothed gradients of a facial image. Then, for feature extraction of complementary classifiers, multiple face models based upon hybrid Fourier features are applied. The hybrid Fourier features are extracted from different Fourier domains in different frequency bandwidths, and then each feature is individually classified by linear discriminant analysis. In addition, multiple face models are generated by plural normalized face images that have different eye distances. Finally, to combine scores from multiple complementary classifiers, a log likelihood ratio-based score fusion scheme is applied. The proposed system using the face recognition grand challenge (FRGC) experimental protocols is evaluated; FRGC is a large available data set. Experimental results on the FRGC version 2.0 data sets have shown that the proposed method shows an average of 81.49% verification rate on 2-D face images under various environmental variations such as illumination changes, expression changes, and time elapses.

Perceived face size in healthy adults.

PubMed

D'Amour, Sarah; Harris, Laurence R

2017-01-01

Perceptual body size distortions have traditionally been studied using subjective, qualitative measures that assess only one type of body representation-the conscious body image. Previous research on perceived body size has typically focused on measuring distortions of the entire body and has tended to overlook the face. Here, we present a novel psychophysical method for determining perceived body size that taps into implicit body representation. Using a two-alternative forced choice (2AFC), participants were sequentially shown two life-size images of their own face, viewed upright, upside down, or tilted 90°. In one interval, the width or length dimension was varied, while the other interval contained an undistorted image. Participants reported which image most closely matched their own face. An adaptive staircase adjusted the distorted image to hone in on the image that was equally likely to be judged as matching their perceived face as the accurate image. When viewed upright or upside down, face width was overestimated and length underestimated, whereas perception was accurate for the on-side views. These results provide the first psychophysically robust measurements of how accurately healthy participants perceive the size of their face, revealing distortions of the implicit body representation independent of the conscious body image.

TDC-based readout electronics for real-time acquisition of high resolution PET bio-images

NASA Astrophysics Data System (ADS)

Marino, N.; Saponara, S.; Ambrosi, G.; Baronti, F.; Bisogni, M. G.; Cerello, P.,; Ciciriello, F.; Corsi, F.; Fanucci, L.; Ionica, M.; Licciulli, F.; Marzocca, C.; Morrocchi, M.; Pennazio, F.; Roncella, R.; Santoni, C.; Wheadon, R.; Del Guerra, A.

2013-02-01

Positron emission tomography (PET) is a clinical and research tool for in vivo metabolic imaging. The demand for better image quality entails continuous research to improve PET instrumentation. In clinical applications, PET image quality benefits from the time of flight (TOF) feature. Indeed, by measuring the photons arrival time on the detectors with a resolution less than 100 ps, the annihilation point can be estimated with centimeter resolution. This leads to better noise level, contrast and clarity of detail in the images either using analytical or iterative reconstruction algorithms. This work discusses a silicon photomultiplier (SiPM)-based magnetic-field compatible TOF-PET module with depth of interaction (DOI) correction. The detector features a 3D architecture with two tiles of SiPMs coupled to a single LYSO scintillator on both its faces. The real-time front-end electronics is based on a current-mode ASIC where a low input impedance, fast current buffer allows achieving the required time resolution. A pipelined time to digital converter (TDC) measures and digitizes the arrival time and the energy of the events with a timestamp of 100 ps and 400 ps, respectively. An FPGA clusters the data and evaluates the DOI, with a simulated z resolution of the PET image of 1.4 mm FWHM.

A novel thermal face recognition approach using face pattern words

NASA Astrophysics Data System (ADS)

Zheng, Yufeng

2010-04-01

A reliable thermal face recognition system can enhance the national security applications such as prevention against terrorism, surveillance, monitoring and tracking, especially at nighttime. The system can be applied at airports, customs or high-alert facilities (e.g., nuclear power plant) for 24 hours a day. In this paper, we propose a novel face recognition approach utilizing thermal (long wave infrared) face images that can automatically identify a subject at both daytime and nighttime. With a properly acquired thermal image (as a query image) in monitoring zone, the following processes will be employed: normalization and denoising, face detection, face alignment, face masking, Gabor wavelet transform, face pattern words (FPWs) creation, face identification by similarity measure (Hamming distance). If eyeglasses are present on a subject's face, an eyeglasses mask will be automatically extracted from the querying face image, and then masked with all comparing FPWs (no more transforms). A high identification rate (97.44% with Top-1 match) has been achieved upon our preliminary face dataset (of 39 subjects) from the proposed approach regardless operating time and glasses-wearing condition.e

Fast periodic presentation of natural images reveals a robust face-selective electrophysiological response in the human brain.

PubMed

Rossion, Bruno; Torfs, Katrien; Jacques, Corentin; Liu-Shuang, Joan

2015-01-16

We designed a fast periodic visual stimulation approach to identify an objective signature of face categorization incorporating both visual discrimination (from nonface objects) and generalization (across widely variable face exemplars). Scalp electroencephalographic (EEG) data were recorded in 12 human observers viewing natural images of objects at a rapid frequency of 5.88 images/s for 60 s. Natural images of faces were interleaved every five stimuli, i.e., at 1.18 Hz (5.88/5). Face categorization was indexed by a high signal-to-noise ratio response, specifically at an oddball face stimulation frequency of 1.18 Hz and its harmonics. This face-selective periodic EEG response was highly significant for every participant, even for a single 60-s sequence, and was generally localized over the right occipitotemporal cortex. The periodicity constraint and the large selection of stimuli ensured that this selective response to natural face images was free of low-level visual confounds, as confirmed by the absence of any oddball response for phase-scrambled stimuli. Without any subtraction procedure, time-domain analysis revealed a sequence of differential face-selective EEG components between 120 and 400 ms after oddball face image onset, progressing from medial occipital (P1-faces) to occipitotemporal (N1-faces) and anterior temporal (P2-faces) regions. Overall, this fast periodic visual stimulation approach provides a direct signature of natural face categorization and opens an avenue for efficiently measuring categorization responses of complex visual stimuli in the human brain. © 2015 ARVO.

Automatic image equalization and contrast enhancement using Gaussian mixture modeling.

PubMed

Celik, Turgay; Tjahjadi, Tardi

2012-01-01

In this paper, we propose an adaptive image equalization algorithm that automatically enhances the contrast in an input image. The algorithm uses the Gaussian mixture model to model the image gray-level distribution, and the intersection points of the Gaussian components in the model are used to partition the dynamic range of the image into input gray-level intervals. The contrast equalized image is generated by transforming the pixels' gray levels in each input interval to the appropriate output gray-level interval according to the dominant Gaussian component and the cumulative distribution function of the input interval. To take account of the hypothesis that homogeneous regions in the image represent homogeneous silences (or set of Gaussian components) in the image histogram, the Gaussian components with small variances are weighted with smaller values than the Gaussian components with larger variances, and the gray-level distribution is also used to weight the components in the mapping of the input interval to the output interval. Experimental results show that the proposed algorithm produces better or comparable enhanced images than several state-of-the-art algorithms. Unlike the other algorithms, the proposed algorithm is free of parameter setting for a given dynamic range of the enhanced image and can be applied to a wide range of image types.

Image based SAR product simulation for analysis

NASA Technical Reports Server (NTRS)

Domik, G.; Leberl, F.

1987-01-01

SAR product simulation serves to predict SAR image gray values for various flight paths. Input typically consists of a digital elevation model and backscatter curves. A new method is described of product simulation that employs also a real SAR input image for image simulation. This can be denoted as 'image-based simulation'. Different methods to perform this SAR prediction are presented and advantages and disadvantages discussed. Ascending and descending orbit images from NASA's SIR-B experiment were used for verification of the concept: input images from ascending orbits were converted into images from a descending orbit; the results are compared to the available real imagery to verify that the prediction technique produces meaningful image data.

How Category Structure Influences the Perception of Object Similarity: The Atypicality Bias

PubMed Central

Tanaka, James William; Kantner, Justin; Bartlett, Marni

2011-01-01

Why do some faces appear more similar than others? Beyond structural factors, we speculate that similarity is governed by the organization of faces located in a multi-dimensional face space. To test this hypothesis, we morphed a typical face with an atypical face. If similarity judgments are guided purely by their physical properties, the morph should be perceived to be equally similar to its typical parent as its atypical parent. However, contrary to the structural prediction, our results showed that the morph face was perceived to be more similar to the atypical face than the typical face. Our empirical studies show that the atypicality bias is not limited to faces, but extends to other object categories (birds) whose members share common shape properties. We also demonstrate atypicality bias is malleable and can change subject to category learning and experience. Collectively, the empirical evidence indicates that perceptions of face and object similarity are affected by the distribution of stimuli in a face or object space. In this framework, atypical stimuli are located in a sparser region of the space where there is less competition for recognition and therefore, these representations capture a broader range of inputs. In contrast, typical stimuli are located in a denser region of category space where there is increased competition for recognition and hence, these representation draw a more restricted range of face inputs. These results suggest that the perceived likeness of an object is influenced by the organization of surrounding exemplars in the category space. PMID:22685441

Looking for myself: current multisensory input alters self-face recognition.

PubMed

Tsakiris, Manos

2008-01-01

How do I know the person I see in the mirror is really me? Is it because I know the person simply looks like me, or is it because the mirror reflection moves when I move, and I see it being touched when I feel touch myself? Studies of face-recognition suggest that visual recognition of stored visual features inform self-face recognition. In contrast, body-recognition studies conclude that multisensory integration is the main cue to selfhood. The present study investigates for the first time the specific contribution of current multisensory input for self-face recognition. Participants were stroked on their face while they were looking at a morphed face being touched in synchrony or asynchrony. Before and after the visuo-tactile stimulation participants performed a self-recognition task. The results show that multisensory signals have a significant effect on self-face recognition. Synchronous tactile stimulation while watching another person's face being similarly touched produced a bias in recognizing one's own face, in the direction of the other person included in the representation of one's own face. Multisensory integration can update cognitive representations of one's body, such as the sense of ownership. The present study extends this converging evidence by showing that the correlation of synchronous multisensory signals also updates the representation of one's face. The face is a key feature of our identity, but at the same time is a source of rich multisensory experiences used to maintain or update self-representations.

Rating Nasolabial Aesthetics in Unilateral Cleft Lip and Palate Patients: Cropped Versus Full-Face Images.

PubMed

Schwirtz, Roderic M F; Mulder, Frans J; Mosmuller, David G M; Tan, Robin A; Maal, Thomas J; Prahl, Charlotte; de Vet, Henrica C W; Don Griot, J Peter W

2018-05-01

To determine if cropping facial images affects nasolabial aesthetics assessments in unilateral cleft lip patients and to evaluate the effect of facial attractiveness on nasolabial evaluation. Two cleft surgeons and one cleft orthodontist assessed standardized frontal photographs 4 times; nasolabial aesthetics were rated on cropped and full-face images using the Cleft Aesthetic Rating Scale, and total facial attractiveness was rated on full-face images with and without the nasolabial area blurred using a 5-point Likert scale. Cleft Palate Craniofacial Unit of a University Medical Center. Inclusion criteria: nonsyndromic unilateral cleft lip and an available frontal view photograph around 10 years of age. a history of facial trauma and an incomplete cleft. Eighty-one photographs were available for assessment. Differences in mean CARS scores between cropped versus full-face photographs and attractive versus unattractive rated patients were evaluated by paired t test. Nasolabial aesthetics are scored more negatively on full-face photographs compared to cropped photographs, regardless of facial attractiveness. (Mean CARS score, nose: cropped = 2.8, full-face = 3.0, P < .001; lip: cropped = 2.4, full-face = 2.7, P < .001; nose and lip: cropped = 2.6, full-face = 2.8, P < .001). Aesthetic outcomes of the nasolabial area are assessed significantly more positively when using cropped images compared to full-face images. For this reason, cropping images, revealing the nasolabial area only, is recommended for aesthetical assessments.

Fusion of LBP and SWLD using spatio-spectral information for hyperspectral face recognition

NASA Astrophysics Data System (ADS)

Xie, Zhihua; Jiang, Peng; Zhang, Shuai; Xiong, Jinquan

2018-01-01

Hyperspectral imaging, recording intrinsic spectral information of the skin cross different spectral bands, become an important issue for robust face recognition. However, the main challenges for hyperspectral face recognition are high data dimensionality, low signal to noise ratio and inter band misalignment. In this paper, hyperspectral face recognition based on LBP (Local binary pattern) and SWLD (Simplified Weber local descriptor) is proposed to extract discriminative local features from spatio-spectral fusion information. Firstly, the spatio-spectral fusion strategy based on statistical information is used to attain discriminative features of hyperspectral face images. Secondly, LBP is applied to extract the orientation of the fusion face edges. Thirdly, SWLD is proposed to encode the intensity information in hyperspectral images. Finally, we adopt a symmetric Kullback-Leibler distance to compute the encoded face images. The hyperspectral face recognition is tested on Hong Kong Polytechnic University Hyperspectral Face database (PolyUHSFD). Experimental results show that the proposed method has higher recognition rate (92.8%) than the state of the art hyperspectral face recognition algorithms.

On the integral use of foundational concepts in verifying validity during skull-photo superimposition.

PubMed

Jayaprakash, Paul T

2017-09-01

Often cited reliability test on video superimposition method integrated scaling face-images in relation to skull-images, tragus-auditory meatus relationship in addition to exocanthion-Whitnall's tubercle relationship when orientating the skull-image and wipe mode imaging in addition to mix mode imaging when obtaining skull-face image overlay and evaluating the goodness of match. However, a report that found higher false positive matches in computer assisted superimposition method transited from the above foundational concepts and relied on images of unspecified sizes that are lesser than 'life-size', frontal plane landmarks in the skull- and face- images alone for orientating the skull-image and mix images alone for evaluating the goodness of match. Recently, arguing the use of 'life-size' images as 'archaic', the authors who tested the reliability in the computer assisted superimposition method have denied any method transition. This article describes that the use of images of unspecified sizes at lesser than 'life-size' eliminates the only possibility to quantify parameters during superimposition which alone enables dynamic skull orientation when overlaying a skull-image with a face-image in an anatomically acceptable orientation. The dynamic skull orientation process mandatorily requires aligning the tragus in the 2D face-image with the auditory meatus in the 3D skull-image for anatomically orientating the skull-image in relation to the posture in the face-image, a step not mentioned by the authors describing the computer assisted superimposition method. Furthermore, mere reliance on mix type images during image overlay eliminates the possibility to assess the relationship between the leading edges of the skull- and face-image outlines as also specific area match among the corresponding craniofacial organs during superimposition. Indicating the possibility of increased false positive matches as a consequence of the above method transitions, the need for testing the reliability in the superimposition method adopting concepts that are considered safe is stressed. Copyright © 2017 Elsevier B.V. All rights reserved.

Applicability of common measures in multifocus image fusion comparison

NASA Astrophysics Data System (ADS)

Vajgl, Marek

2017-11-01

Image fusion is an image processing area aimed at fusion of multiple input images to achieve an output image somehow better then each of the input ones. In the case of "multifocus fusion", input images are capturing the same scene differing ina focus distance. The aim is to obtain an image, which is sharp in all its areas. The are several different approaches and methods used to solve this problem. However, it is common question which one is the best. This work describes a research covering the field of common measures with a question, if some of them can be used as a quality measure of the fusion result evaluation.

Optical power splitter for splitting high power light

DOEpatents

English, R.E. Jr.; Christensen, J.J.

1995-04-18

An optical power splitter for the distribution of high-power light energy has a plurality of prisms arranged about a central axis to form a central channel. The input faces of the prisms are in a common plane which is substantially perpendicular to the central axis. A beam of light which is substantially coaxial to the central axis is incident on the prisms and at least partially strikes a surface area of each prism input face. The incident beam also partially passes through the central channel. 5 figs.

Smiles in face matching: Idiosyncratic information revealed through a smile improves unfamiliar face matching performance.

PubMed

Mileva, Mila; Burton, A Mike

2018-06-19

Unfamiliar face matching is a surprisingly difficult task, yet we often rely on people's matching decisions in applied settings (e.g., border control). Most attempts to improve accuracy (including training and image manipulation) have had very limited success. In a series of studies, we demonstrate that using smiling rather than neutral pairs of images brings about significant improvements in face matching accuracy. This is true for both match and mismatch trials, implying that the information provided through a smile helps us detect images of the same identity as well as distinguishing between images of different identities. Study 1 compares matching performance when images in the face pair display either an open-mouth smile or a neutral expression. In Study 2, we add an intermediate level, closed-mouth smile, to identify the effect of teeth being exposed, and Study 3 explores face matching accuracy when only information about the lower part of the face is available. Results demonstrate that an open-mouth smile changes the face in an idiosyncratic way which aids face matching decisions. Such findings have practical implications for matching in the applied context where we typically use neutral images to represent ourselves in official documents. © 2018 The British Psychological Society.

Face sketch recognition based on edge enhancement via deep learning

NASA Astrophysics Data System (ADS)

Xie, Zhenzhu; Yang, Fumeng; Zhang, Yuming; Wu, Congzhong

2017-11-01

In this paper,we address the face sketch recognition problem. Firstly, we utilize the eigenface algorithm to convert a sketch image into a synthesized sketch face image. Subsequently, considering the low-level vision problem in synthesized face sketch image .Super resolution reconstruction algorithm based on CNN(convolutional neural network) is employed to improve the visual effect. To be specific, we uses a lightweight super-resolution structure to learn a residual mapping instead of directly mapping the feature maps from the low-level space to high-level patch representations, which making the networks are easier to optimize and have lower computational complexity. Finally, we adopt LDA(Linear Discriminant Analysis) algorithm to realize face sketch recognition on synthesized face image before super resolution and after respectively. Extensive experiments on the face sketch database(CUFS) from CUHK demonstrate that the recognition rate of SVM(Support Vector Machine) algorithm improves from 65% to 69% and the recognition rate of LDA(Linear Discriminant Analysis) algorithm improves from 69% to 75%.What'more,the synthesized face image after super resolution can not only better describer image details such as hair ,nose and mouth etc, but also improve the recognition accuracy effectively.

Uyghur face recognition method combining 2DDCT with POEM

NASA Astrophysics Data System (ADS)

Yi, Lihamu; Ya, Ermaimaiti

2017-11-01

In this paper, in light of the reduced recognition rate and poor robustness of Uyghur face under illumination and partial occlusion, a Uyghur face recognition method combining Two Dimension Discrete Cosine Transform (2DDCT) with Patterns Oriented Edge Magnitudes (POEM) was proposed. Firstly, the Uyghur face images were divided into 8×8 block matrix, and the Uyghur face images after block processing were converted into frequency-domain status using 2DDCT; secondly, the Uyghur face images were compressed to exclude non-sensitive medium frequency parts and non-high frequency parts, so it can reduce the feature dimensions necessary for the Uyghur face images, and further reduce the amount of computation; thirdly, the corresponding POEM histograms of the Uyghur face images were obtained by calculating the feature quantity of POEM; fourthly, the POEM histograms were cascaded together as the texture histogram of the center feature point to obtain the texture features of the Uyghur face feature points; finally, classification of the training samples was carried out using deep learning algorithm. The simulation experiment results showed that the proposed algorithm further improved the recognition rate of the self-built Uyghur face database, and greatly improved the computing speed of the self-built Uyghur face database, and had strong robustness.

Face detection assisted auto exposure: supporting evidence from a psychophysical study

NASA Astrophysics Data System (ADS)

Jin, Elaine W.; Lin, Sheng; Dharumalingam, Dhandapani

2010-01-01

Face detection has been implemented in many digital still cameras and camera phones with the promise of enhancing existing camera functions (e.g. auto exposure) and adding new features to cameras (e.g. blink detection). In this study we examined the use of face detection algorithms in assisting auto exposure (AE). The set of 706 images, used in this study, was captured using Canon Digital Single Lens Reflex cameras and subsequently processed with an image processing pipeline. A psychophysical study was performed to obtain optimal exposure along with the upper and lower bounds of exposure for all 706 images. Three methods of marking faces were utilized: manual marking, face detection algorithm A (FD-A), and face detection algorithm B (FD-B). The manual marking method found 751 faces in 426 images, which served as the ground-truth for face regions of interest. The remaining images do not have any faces or the faces are too small to be considered detectable. The two face detection algorithms are different in resource requirements and in performance. FD-A uses less memory and gate counts compared to FD-B, but FD-B detects more faces and has less false positives. A face detection assisted auto exposure algorithm was developed and tested against the evaluation results from the psychophysical study. The AE test results showed noticeable improvement when faces were detected and used in auto exposure. However, the presence of false positives would negatively impact the added benefit.

En-face Flying Spot OCT/Ophthalmoscope

NASA Astrophysics Data System (ADS)

Rosen, Richard B.; Garcia, Patricia; Podoleanu, Adrian Gh.; Cucu, Radu; Dobre, George; Trifanov, Irina; van Velthoven, Mirjam E. J.; de Smet, Marc D.; Rogers, John A.; Hathaway, Mark; Pedro, Justin; Weitz, Rishard

This is a review of a technique for high-resolution imaging of the eye that allows multiple sample sectioning perspectives with different axial resolutions. The technique involves the flying spot approach employed in confocal scanning laser ophthalmoscopy which is extended to OCT imaging via time domain en face fast lateral scanning. The ability of imaging with multiple axial resolutions stimulated the development of the dual en face OCT-confocal imaging technology. Dual imaging also allows various other imaging combinations, such as OCT with confocal microscopy for imaging the eye anterior segment and OCT with fluorescence angiography imaging.

Optoelectronic associative memory

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin (Inventor)

1993-01-01

An associative optical memory including an input spatial light modulator (SLM) in the form of an edge enhanced liquid crystal light valve (LCLV) and a pair of memory SLM's in the form of liquid crystal televisions (LCTV's) forms a matrix array of an input image which is cross correlated with a matrix array of stored images. The correlation product is detected and nonlinearly amplified to illuminate a replica of the stored image array to select the stored image correlating with the input image. The LCLV is edge enhanced by reducing the bias frequency and voltage and rotating its orientation. The edge enhancement and nonlinearity of the photodetection improves the orthogonality of the stored image. The illumination of the replicate stored image provides a clean stored image, uncontaminated by the image comparison process.

Original and Mirror Face Images and Minimum Squared Error Classification for Visible Light Face Recognition.

PubMed

Wang, Rong

2015-01-01

In real-world applications, the image of faces varies with illumination, facial expression, and poses. It seems that more training samples are able to reveal possible images of the faces. Though minimum squared error classification (MSEC) is a widely used method, its applications on face recognition usually suffer from the problem of a limited number of training samples. In this paper, we improve MSEC by using the mirror faces as virtual training samples. We obtained the mirror faces generated from original training samples and put these two kinds of samples into a new set. The face recognition experiments show that our method does obtain high accuracy performance in classification.

Infrared and visible fusion face recognition based on NSCT domain

NASA Astrophysics Data System (ADS)

Xie, Zhihua; Zhang, Shuai; Liu, Guodong; Xiong, Jinquan

2018-01-01

Visible face recognition systems, being vulnerable to illumination, expression, and pose, can not achieve robust performance in unconstrained situations. Meanwhile, near infrared face images, being light- independent, can avoid or limit the drawbacks of face recognition in visible light, but its main challenges are low resolution and signal noise ratio (SNR). Therefore, near infrared and visible fusion face recognition has become an important direction in the field of unconstrained face recognition research. In this paper, a novel fusion algorithm in non-subsampled contourlet transform (NSCT) domain is proposed for Infrared and visible face fusion recognition. Firstly, NSCT is used respectively to process the infrared and visible face images, which exploits the image information at multiple scales, orientations, and frequency bands. Then, to exploit the effective discriminant feature and balance the power of high-low frequency band of NSCT coefficients, the local Gabor binary pattern (LGBP) and Local Binary Pattern (LBP) are applied respectively in different frequency parts to obtain the robust representation of infrared and visible face images. Finally, the score-level fusion is used to fuse the all the features for final classification. The visible and near infrared face recognition is tested on HITSZ Lab2 visible and near infrared face database. Experiments results show that the proposed method extracts the complementary features of near-infrared and visible-light images and improves the robustness of unconstrained face recognition.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Polese, Luigi Gentile; Brackney, Larry

An image-based occupancy sensor includes a motion detection module that receives and processes an image signal to generate a motion detection signal, a people detection module that receives the image signal and processes the image signal to generate a people detection signal, a face detection module that receives the image signal and processes the image signal to generate a face detection signal, and a sensor integration module that receives the motion detection signal from the motion detection module, receives the people detection signal from the people detection module, receives the face detection signal from the face detection module, and generatesmore » an occupancy signal using the motion detection signal, the people detection signal, and the face detection signal, with the occupancy signal indicating vacancy or occupancy, with an occupancy indication specifying that one or more people are detected within the monitored volume.« less

Reconstructing 3D Face Model with Associated Expression Deformation from a Single Face Image via Constructing a Low-Dimensional Expression Deformation Manifold.

PubMed

Wang, Shu-Fan; Lai, Shang-Hong

2011-10-01

Facial expression modeling is central to facial expression recognition and expression synthesis for facial animation. In this work, we propose a manifold-based 3D face reconstruction approach to estimating the 3D face model and the associated expression deformation from a single face image. With the proposed robust weighted feature map (RWF), we can obtain the dense correspondences between 3D face models and build a nonlinear 3D expression manifold from a large set of 3D facial expression models. Then a Gaussian mixture model in this manifold is learned to represent the distribution of expression deformation. By combining the merits of morphable neutral face model and the low-dimensional expression manifold, a novel algorithm is developed to reconstruct the 3D face geometry as well as the facial deformation from a single face image in an energy minimization framework. Experimental results on simulated and real images are shown to validate the effectiveness and accuracy of the proposed algorithm.

Reflectance from images: a model-based approach for human faces.

PubMed

Fuchs, Martin; Blanz, Volker; Lensch, Hendrik; Seidel, Hans-Peter

2005-01-01

In this paper, we present an image-based framework that acquires the reflectance properties of a human face. A range scan of the face is not required. Based on a morphable face model, the system estimates the 3D shape and establishes point-to-point correspondence across images taken from different viewpoints and across different individuals' faces. This provides a common parameterization of all reconstructed surfaces that can be used to compare and transfer BRDF data between different faces. Shape estimation from images compensates deformations of the face during the measurement process, such as facial expressions. In the common parameterization, regions of homogeneous materials on the face surface can be defined a priori. We apply analytical BRDF models to express the reflectance properties of each region and we estimate their parameters in a least-squares fit from the image data. For each of the surface points, the diffuse component of the BRDF is locally refined, which provides high detail. We present results for multiple analytical BRDF models, rendered at novel orientations and lighting conditions.

Imaging the eye fundus with real-time en-face spectral domain optical coherence tomography

PubMed Central

Bradu, Adrian; Podoleanu, Adrian Gh.

2014-01-01

Real-time display of processed en-face spectral domain optical coherence tomography (SD-OCT) images is important for diagnosis. However, due to many steps of data processing requirements, such as Fast Fourier transformation (FFT), data re-sampling, spectral shaping, apodization, zero padding, followed by software cut of the 3D volume acquired to produce an en-face slice, conventional high-speed SD-OCT cannot render an en-face OCT image in real time. Recently we demonstrated a Master/Slave (MS)-OCT method that is highly parallelizable, as it provides reflectivity values of points at depth within an A-scan in parallel. This allows direct production of en-face images. In addition, the MS-OCT method does not require data linearization, which further simplifies the processing. The computation in our previous paper was however time consuming. In this paper we present an optimized algorithm that can be used to provide en-face MS-OCT images much quicker. Using such an algorithm we demonstrate around 10 times faster production of sets of en-face OCT images than previously obtained as well as simultaneous real-time display of up to 4 en-face OCT images of 200 × 200 pixels2 from the fovea and the optic nerve of a volunteer. We also demonstrate 3D and B-scan OCT images obtained from sets of MS-OCT C-scans, i.e. with no FFT and no intermediate step of generation of A-scans. PMID:24761303

Retinotopy and attention to the face and house images in the human visual cortex.

PubMed

Wang, Bin; Yan, Tianyi; Ohno, Seiichiro; Kanazawa, Susumu; Wu, Jinglong

2016-06-01

Attentional modulation of the neural activities in human visual areas has been well demonstrated. However, the retinotopic activities that are driven by face and house images and attention to face and house images remain unknown. In the present study, we used images of faces and houses to estimate the retinotopic activities that were driven by both the images and attention to the images, driven by attention to the images, and driven by the images. Generally, our results show that both face and house images produced similar retinotopic activities in visual areas, which were only observed in the attention + stimulus and the attention conditions, but not in the stimulus condition. The fusiform face area (FFA) responded to faces that were presented on the horizontal meridian, whereas parahippocampal place area (PPA) rarely responded to house at any visual field. We further analyzed the amplitudes of the neural responses to the target wedge. In V1, V2, V3, V3A, lateral occipital area 1 (LO-1), and hV4, the neural responses to the attended target wedge were significantly greater than those to the unattended target wedge. However, in LO-2, ventral occipital areas 1 and 2 (VO-1 and VO-2) and FFA and PPA, the differences were not significant. We proposed that these areas likely have large fields of attentional modulation for face and house images and exhibit responses to both the target wedge and the background stimuli. In addition, we proposed that the absence of retinotopic activity in the stimulus condition might imply no perceived difference between the target wedge and the background stimuli.

New concept high-speed and high-resolution color scanner

NASA Astrophysics Data System (ADS)

Nakashima, Keisuke; Shinoda, Shin'ichi; Konishi, Yoshiharu; Sugiyama, Kenji; Hori, Tetsuya

2003-05-01

We have developed a new concept high-speed and high-resolution color scanner (Blinkscan) using digital camera technology. With our most advanced sub-pixel image processing technology, approximately 12 million pixel image data can be captured. High resolution imaging capability allows various uses such as OCR, color document read, and document camera. The scan time is only about 3 seconds for a letter size sheet. Blinkscan scans documents placed "face up" on its scan stage and without any special illumination lights. Using Blinkscan, a high-resolution color document can be easily inputted into a PC at high speed, a paperless system can be built easily. It is small, and since the occupancy area is also small, setting it on an individual desk is possible. Blinkscan offers the usability of a digital camera and accuracy of a flatbed scanner with high-speed processing. Now, about several hundred of Blinkscan are mainly shipping for the receptionist operation in a bank and a security. We will show the high-speed and high-resolution architecture of Blinkscan. Comparing operation-time with conventional image capture device, the advantage of Blinkscan will make clear. And image evaluation for variety of environment, such as geometric distortions or non-uniformity of brightness, will be made.

Western Region: A Report Identifying and Addressing the Educational Needs

ERIC Educational Resources Information Center

US Department of Education, 2011

2011-01-01

During a four-week period (May 23, 2011-June 21, 2011), the Western Regional Advisory Committee (RAC) held a series of public meetings to solicit input and deliberate on key educational needs facing the four states in the region--Arizona, California, Nevada, and Utah. A two-day, face-to-face, public meeting was held May 23-24, 2011 in Arlington,…

Personal identification based on blood vessels of retinal fundus images

NASA Astrophysics Data System (ADS)

Fukuta, Keisuke; Nakagawa, Toshiaki; Hayashi, Yoshinori; Hatanaka, Yuji; Hara, Takeshi; Fujita, Hiroshi

2008-03-01

Biometric technique has been implemented instead of conventional identification methods such as password in computer, automatic teller machine (ATM), and entrance and exit management system. We propose a personal identification (PI) system using color retinal fundus images which are unique to each individual. The proposed procedure for identification is based on comparison of an input fundus image with reference fundus images in the database. In the first step, registration between the input image and the reference image is performed. The step includes translational and rotational movement. The PI is based on the measure of similarity between blood vessel images generated from the input and reference images. The similarity measure is defined as the cross-correlation coefficient calculated from the pixel values. When the similarity is greater than a predetermined threshold, the input image is identified. This means both the input and the reference images are associated to the same person. Four hundred sixty-two fundus images including forty-one same-person's image pairs were used for the estimation of the proposed technique. The false rejection rate and the false acceptance rate were 9.9×10 -5% and 4.3×10 -5%, respectively. The results indicate that the proposed method has a higher performance than other biometrics except for DNA. To be used for practical application in the public, the device which can take retinal fundus images easily is needed. The proposed method is applied to not only the PI but also the system which warns about misfiling of fundus images in medical facilities.

Emotional responses associated with self-face processing in individuals with autism spectrum disorders: an fMRI study.

PubMed

Morita, Tomoyo; Kosaka, Hirotaka; Saito, Daisuke N; Ishitobi, Makoto; Munesue, Toshio; Itakura, Shoji; Omori, Masao; Okazawa, Hidehiko; Wada, Yuji; Sadato, Norihiro

2012-01-01

Individuals with autism spectrum disorders (ASD) show impaired emotional responses to self-face processing, but the underlying neural bases are unclear. Using functional magnetic resonance imaging, we investigated brain activity when 15 individuals with high-functioning ASD and 15 controls rated the photogenicity of self-face images and photographs of others' faces. Controls showed a strong correlation between photogenicity ratings and extent of embarrassment evoked by self-face images; this correlation was weaker among ASD individuals, indicating a decoupling between the cognitive evaluation of self-face images and emotional responses. Individuals with ASD demonstrated relatively low self-related activity in the posterior cingulate cortex (PCC), which was related to specific autistic traits. There were significant group differences in the modulation of activity by embarrassment ratings in the right insular (IC) and lateral orbitofrontal cortices. Task-related activity in the right IC was lower in the ASD group. The reduced activity in the right IC for self-face images was associated with weak coupling between cognitive evaluation and emotional responses to self-face images. The PCC is responsible for self-referential processing, and the IC plays a role in emotional experience. Dysfunction in these areas could contribute to the lack of self-conscious behaviors in response to self-reflection in ASD individuals.

Ultrasonic input-output for transmitting and receiving longitudinal transducers coupled to same face of isotropic elastic plate

NASA Technical Reports Server (NTRS)

Williams, J. H., Jr.; Karagulle, H.; Lee, S. S.

1982-01-01

The quantitative understanding of ultrasonic nondestructive evaluation parameters such as the stress wave factor were studied. Ultrasonic input/output characteristics for an isotropic elastic plate with transmitting and receiving longitudinal transducers coupled to the same face were analyzed. The asymptotic normal stress is calculated for an isotropic elastic half space subjected to a uniform harmonic normal stress applied to a circular region at the surface. The radiated stress waves are traced within the plate by considering wave reflections at the top and bottom faces. The output voltage amplitude of the receiving transducer is estimated by considering only longitudinal waves. Agreement is found between the output voltage wave packet amplitudes and times of arrival due to multiple reflections of the longitudinal waves.

Combining Deep and Handcrafted Image Features for Presentation Attack Detection in Face Recognition Systems Using Visible-Light Camera Sensors

PubMed Central

Nguyen, Dat Tien; Pham, Tuyen Danh; Baek, Na Rae; Park, Kang Ryoung

2018-01-01

Although face recognition systems have wide application, they are vulnerable to presentation attack samples (fake samples). Therefore, a presentation attack detection (PAD) method is required to enhance the security level of face recognition systems. Most of the previously proposed PAD methods for face recognition systems have focused on using handcrafted image features, which are designed by expert knowledge of designers, such as Gabor filter, local binary pattern (LBP), local ternary pattern (LTP), and histogram of oriented gradients (HOG). As a result, the extracted features reflect limited aspects of the problem, yielding a detection accuracy that is low and varies with the characteristics of presentation attack face images. The deep learning method has been developed in the computer vision research community, which is proven to be suitable for automatically training a feature extractor that can be used to enhance the ability of handcrafted features. To overcome the limitations of previously proposed PAD methods, we propose a new PAD method that uses a combination of deep and handcrafted features extracted from the images by visible-light camera sensor. Our proposed method uses the convolutional neural network (CNN) method to extract deep image features and the multi-level local binary pattern (MLBP) method to extract skin detail features from face images to discriminate the real and presentation attack face images. By combining the two types of image features, we form a new type of image features, called hybrid features, which has stronger discrimination ability than single image features. Finally, we use the support vector machine (SVM) method to classify the image features into real or presentation attack class. Our experimental results indicate that our proposed method outperforms previous PAD methods by yielding the smallest error rates on the same image databases. PMID:29495417

Combining Deep and Handcrafted Image Features for Presentation Attack Detection in Face Recognition Systems Using Visible-Light Camera Sensors.

PubMed

Nguyen, Dat Tien; Pham, Tuyen Danh; Baek, Na Rae; Park, Kang Ryoung

2018-02-26

Although face recognition systems have wide application, they are vulnerable to presentation attack samples (fake samples). Therefore, a presentation attack detection (PAD) method is required to enhance the security level of face recognition systems. Most of the previously proposed PAD methods for face recognition systems have focused on using handcrafted image features, which are designed by expert knowledge of designers, such as Gabor filter, local binary pattern (LBP), local ternary pattern (LTP), and histogram of oriented gradients (HOG). As a result, the extracted features reflect limited aspects of the problem, yielding a detection accuracy that is low and varies with the characteristics of presentation attack face images. The deep learning method has been developed in the computer vision research community, which is proven to be suitable for automatically training a feature extractor that can be used to enhance the ability of handcrafted features. To overcome the limitations of previously proposed PAD methods, we propose a new PAD method that uses a combination of deep and handcrafted features extracted from the images by visible-light camera sensor. Our proposed method uses the convolutional neural network (CNN) method to extract deep image features and the multi-level local binary pattern (MLBP) method to extract skin detail features from face images to discriminate the real and presentation attack face images. By combining the two types of image features, we form a new type of image features, called hybrid features, which has stronger discrimination ability than single image features. Finally, we use the support vector machine (SVM) method to classify the image features into real or presentation attack class. Our experimental results indicate that our proposed method outperforms previous PAD methods by yielding the smallest error rates on the same image databases.

Face Recognition for Access Control Systems Combining Image-Difference Features Based on a Probabilistic Model

NASA Astrophysics Data System (ADS)

Miwa, Shotaro; Kage, Hiroshi; Hirai, Takashi; Sumi, Kazuhiko

We propose a probabilistic face recognition algorithm for Access Control System(ACS)s. Comparing with existing ACSs using low cost IC-cards, face recognition has advantages in usability and security that it doesn't require people to hold cards over scanners and doesn't accept imposters with authorized cards. Therefore face recognition attracts more interests in security markets than IC-cards. But in security markets where low cost ACSs exist, price competition is important, and there is a limitation on the quality of available cameras and image control. Therefore ACSs using face recognition are required to handle much lower quality images, such as defocused and poor gain-controlled images than high security systems, such as immigration control. To tackle with such image quality problems we developed a face recognition algorithm based on a probabilistic model which combines a variety of image-difference features trained by Real AdaBoost with their prior probability distributions. It enables to evaluate and utilize only reliable features among trained ones during each authentication, and achieve high recognition performance rates. The field evaluation using a pseudo Access Control System installed in our office shows that the proposed system achieves a constant high recognition performance rate independent on face image qualities, that is about four times lower EER (Equal Error Rate) under a variety of image conditions than one without any prior probability distributions. On the other hand using image difference features without any prior probabilities are sensitive to image qualities. We also evaluated PCA, and it has worse, but constant performance rates because of its general optimization on overall data. Comparing with PCA, Real AdaBoost without any prior distribution performs twice better under good image conditions, but degrades to a performance as good as PCA under poor image conditions.

Illumination-tolerant face verification of low-bit-rate JPEG2000 wavelet images with advanced correlation filters for handheld devices

NASA Astrophysics Data System (ADS)

Wijaya, Surya Li; Savvides, Marios; Vijaya Kumar, B. V. K.

2005-02-01

Face recognition on mobile devices, such as personal digital assistants and cell phones, is a big challenge owing to the limited computational resources available to run verifications on the devices themselves. One approach is to transmit the captured face images by use of the cell-phone connection and to run the verification on a remote station. However, owing to limitations in communication bandwidth, it may be necessary to transmit a compressed version of the image. We propose using the image compression standard JPEG2000, which is a wavelet-based compression engine used to compress the face images to low bit rates suitable for transmission over low-bandwidth communication channels. At the receiver end, the face images are reconstructed with a JPEG2000 decoder and are fed into the verification engine. We explore how advanced correlation filters, such as the minimum average correlation energy filter [Appl. Opt. 26, 3633 (1987)] and its variants, perform by using face images captured under different illumination conditions and encoded with different bit rates under the JPEG2000 wavelet-encoding standard. We evaluate the performance of these filters by using illumination variations from the Carnegie Mellon University's Pose, Illumination, and Expression (PIE) face database. We also demonstrate the tolerance of these filters to noisy versions of images with illumination variations.

Quality labeled faces in the wild (QLFW): a database for studying face recognition in real-world environments

NASA Astrophysics Data System (ADS)

Karam, Lina J.; Zhu, Tong

2015-03-01

The varying quality of face images is an important challenge that limits the effectiveness of face recognition technology when applied in real-world applications. Existing face image databases do not consider the effect of distortions that commonly occur in real-world environments. This database (QLFW) represents an initial attempt to provide a set of labeled face images spanning the wide range of quality, from no perceived impairment to strong perceived impairment for face detection and face recognition applications. Types of impairment include JPEG2000 compression, JPEG compression, additive white noise, Gaussian blur and contrast change. Subjective experiments are conducted to assess the perceived visual quality of faces under different levels and types of distortions and also to assess the human recognition performance under the considered distortions. One goal of this work is to enable automated performance evaluation of face recognition technologies in the presence of different types and levels of visual distortions. This will consequently enable the development of face recognition systems that can operate reliably on real-world visual content in the presence of real-world visual distortions. Another goal is to enable the development and assessment of visual quality metrics for face images and for face detection and recognition applications.

Image processing tool for automatic feature recognition and quantification

DOEpatents

Chen, Xing; Stoddard, Ryan J.

2017-05-02

A system for defining structures within an image is described. The system includes reading of an input file, preprocessing the input file while preserving metadata such as scale information and then detecting features of the input file. In one version the detection first uses an edge detector followed by identification of features using a Hough transform. The output of the process is identified elements within the image.

Effect of random phase mask on input plane in photorefractive authentic memory with two-wave encryption method

NASA Astrophysics Data System (ADS)

Mita, Akifumi; Okamoto, Atsushi; Funakoshi, Hisatoshi

2004-06-01

We have proposed an all-optical authentic memory with the two-wave encryption method. In the recording process, the image data are encrypted to a white noise by the random phase masks added on the input beam with the image data and the reference beam. Only reading beam with the phase-conjugated distribution of the reference beam can decrypt the encrypted data. If the encrypted data are read out with an incorrect phase distribution, the output data are transformed into a white noise. Moreover, during read out, reconstructions of the encrypted data interfere destructively resulting in zero intensity. Therefore our memory has a merit that we can detect unlawful accesses easily by measuring the output beam intensity. In our encryption method, the random phase mask on the input plane plays important roles in transforming the input image into a white noise and prohibiting to decrypt a white noise to the input image by the blind deconvolution method. Without this mask, when unauthorized users observe the output beam by using CCD in the readout with the plane wave, the completely same intensity distribution as that of Fourier transform of the input image is obtained. Therefore the encrypted image will be decrypted easily by using the blind deconvolution method. However in using this mask, even if unauthorized users observe the output beam using the same method, the encrypted image cannot be decrypted because the observed intensity distribution is dispersed at random by this mask. Thus it can be said the robustness is increased by this mask. In this report, we compare two correlation coefficients, which represents the degree of a white noise of the output image, between the output image and the input image in using this mask or not. We show that the robustness of this encryption method is increased as the correlation coefficient is improved from 0.3 to 0.1 by using this mask.

Activity in Face-Responsive Brain Regions is Modulated by Invisible, Attended Faces: Evidence from Masked Priming

PubMed Central

Eger, Evelyn; Dolan, Raymond; Henson, Richard N.

2009-01-01

It is often assumed that neural activity in face-responsive regions of primate cortex correlates with conscious perception of faces. However, whether such activity occurs without awareness is still debated. Using functional magnetic resonance imaging (fMRI) in conjunction with a novel masked face priming paradigm, we observed neural modulations that could not be attributed to perceptual awareness. More specifically, we found reduced activity in several classic face-processing regions, including the “fusiform face area,” “occipital face area,” and superior temporal sulcus, when a face was preceded by a briefly flashed image of the same face, relative to a different face, even when 2 images of the same face differed. Importantly, unlike most previous studies, which have minimized awareness by using conditions of inattention, the present results occurred when the stimuli (the primes) were attended. By contrast, when primes were perceived consciously, in a long-lag priming paradigm, we found repetition-related activity increases in additional frontal and parietal regions. These data not only demonstrate that fMRI activity in face-responsive regions can be modulated independently of perceptual awareness, but also document where such subliminal face-processing occurs (i.e., restricted to face-responsive regions of occipital and temporal cortex) and to what extent (i.e., independent of the specific image). PMID:18400791

Right mesial temporal lobe epilepsy impairs empathy-related brain responses to dynamic fearful faces.

PubMed

Toller, Gianina; Adhimoolam, Babu; Grunwald, Thomas; Huppertz, Hans-Jürgen; Kurthen, Martin; Rankin, Katherine P; Jokeit, Hennric

2015-03-01

Unilateral mesial temporal lobe epilepsy (MTLE) has been associated with reduced amygdala responsiveness to fearful faces. However, the effect of unilateral MTLE on empathy-related brain responses in extra-amygdalar regions has not been investigated. Using functional magnetic resonance imaging, we measured empathy-related brain responses to dynamic fearful faces in 34 patients with unilateral MTLE (18 right sided), in an epilepsy (extra-MTLE; n = 16) and in a healthy control group (n = 30). The primary finding was that right MTLE (RMTLE) was associated with decreased activity predominantly in the right amygdala and also in bilateral periaqueductal gray (PAG) but normal activity in the right anterior insula. The results of the extra-MTLE group demonstrate that these reduced amygdala and PAG responses go beyond the attenuation caused by antiepileptic and antidepressant medication. These findings clearly indicate that RMTLE affects the function of mesial temporal and midbrain structures that mediate basic interoceptive input necessary for the emotional awareness of empathic experiences of fear. Together with the decreased empathic concern found in the RMTLE group, this study provides neurobehavioral evidence that patients with RMTLE are at increased risk for reduced empathy towards others' internal states and sheds new light on the nature of social-cognitive impairments frequently accompanying MTLE.

Self-Adaptive Correction of Heading Direction in Stair Climbing for Tracked Mobile Robots Using Visual Servoing Approach

NASA Astrophysics Data System (ADS)

Ji, Peng; Song, Aiguo; Song, Zimo; Liu, Yuqing; Jiang, Guohua; Zhao, Guopu

2017-02-01

In this paper, we describe a heading direction correction algorithm for a tracked mobile robot. To save hardware resources as far as possible, the mobile robot’s wrist camera is used as the only sensor, which is rotated to face stairs. An ensemble heading deviation detector is proposed to help the mobile robot correct its heading direction. To improve the generalization ability, a multi-scale Gabor filter is used to process the input image previously. Final deviation result is acquired by applying the majority vote strategy on all the classifiers’ results. The experimental results show that our detector is able to enable the mobile robot to correct its heading direction adaptively while it is climbing the stairs.

Left-right facial orientation of familiar faces: developmental aspects of « the mere exposure hypothesis ».

PubMed

Amestoy, Anouck; Bouvard, Manuel P; Cazalets, Jean-René

2010-01-01

We investigated the developmental aspect of sensitivity to the orientation of familiar faces by asking 38 adults and 72 children from 3 to 12 years old to make a preference choice between standard and mirror images of themselves and of familiar faces, presented side-by-side or successively. When familiar (parental) faces were presented simultaneously, 3- to 5-year-olds showed no preference, but by age 5-7 years an adult-like preference for the standard image emerged. Similarly, the adult-like preference for the mirror image of their own face emerged by 5-7 years of age. When familiar or self faces were presented successively, 3- to 7-year-olds showed no preference, and adult-like preference for the standard image emerged by age 7-12 years. These results suggest the occurrence of a developmental process in the perception of familiar face asymmetries which is retained in memory related to knowledge about faces.

Development and application of computer assisted optimal method for treatment of femoral neck fracture.

PubMed

Wang, Monan; Zhang, Kai; Yang, Ning

2018-04-09

To help doctors decide their treatment from the aspect of mechanical analysis, the work built a computer assisted optimal system for treatment of femoral neck fracture oriented to clinical application. The whole system encompassed the following three parts: Preprocessing module, finite element mechanical analysis module, post processing module. Preprocessing module included parametric modeling of bone, parametric modeling of fracture face, parametric modeling of fixed screw and fixed position and input and transmission of model parameters. Finite element mechanical analysis module included grid division, element type setting, material property setting, contact setting, constraint and load setting, analysis method setting and batch processing operation. Post processing module included extraction and display of batch processing operation results, image generation of batch processing operation, optimal program operation and optimal result display. The system implemented the whole operations from input of fracture parameters to output of the optimal fixed plan according to specific patient real fracture parameter and optimal rules, which demonstrated the effectiveness of the system. Meanwhile, the system had a friendly interface, simple operation and could improve the system function quickly through modifying single module.

Working for a sustainable future: healthcare leaders provide input for new model.

PubMed

2003-06-01

With each tick of the clock, healthcare leaders are coming face to face with a pressing quandary: How can they best guide their organizations to success and sustainability in a rocky and ever-changing healthcare environment? A new "model of sustainability," developed with input from nine CEOs of top medical institutions, may provide some guidance. The model includes six leadership imperatives that underscore critical approaches to supporting the hospital of the future: Build strong organization-wide leadership, become the employer of choice, generate financial strength, redesign structures and processes, develop productive physician relationships, and engage consumers.

Synthesis and identification of three-dimensional faces from image(s) and three-dimensional generic models

NASA Astrophysics Data System (ADS)

Liu, Zexi; Cohen, Fernand

2017-11-01

We describe an approach for synthesizing a three-dimensional (3-D) face structure from an image or images of a human face taken at a priori unknown poses using gender and ethnicity specific 3-D generic models. The synthesis process starts with a generic model, which is personalized as images of the person become available using preselected landmark points that are tessellated to form a high-resolution triangular mesh. From a single image, two of the three coordinates of the model are reconstructed in accordance with the given image of the person, while the third coordinate is sampled from the generic model, and the appearance is made in accordance with the image. With multiple images, all coordinates and appearance are reconstructed in accordance with the observed images. This method allows for accurate pose estimation as well as face identification in 3-D rendering of a difficult two-dimensional (2-D) face recognition problem into a much simpler 3-D surface matching problem. The estimation of the unknown pose is achieved using the Levenberg-Marquardt optimization process. Encouraging experimental results are obtained in a controlled environment with high-resolution images under a good illumination condition, as well as for images taken in an uncontrolled environment under arbitrary illumination with low-resolution cameras.

Perceptual expertise in forensic facial image comparison

PubMed Central

White, David; Phillips, P. Jonathon; Hahn, Carina A.; Hill, Matthew; O'Toole, Alice J.

2015-01-01

Forensic facial identification examiners are required to match the identity of faces in images that vary substantially, owing to changes in viewing conditions and in a person's appearance. These identifications affect the course and outcome of criminal investigations and convictions. Despite calls for research on sources of human error in forensic examination, existing scientific knowledge of face matching accuracy is based, almost exclusively, on people without formal training. Here, we administered three challenging face matching tests to a group of forensic examiners with many years' experience of comparing face images for law enforcement and government agencies. Examiners outperformed untrained participants and computer algorithms, thereby providing the first evidence that these examiners are experts at this task. Notably, computationally fusing responses of multiple experts produced near-perfect performance. Results also revealed qualitative differences between expert and non-expert performance. First, examiners' superiority was greatest at longer exposure durations, suggestive of more entailed comparison in forensic examiners. Second, experts were less impaired by image inversion than non-expert students, contrasting with face memory studies that show larger face inversion effects in high performers. We conclude that expertise in matching identity across unfamiliar face images is supported by processes that differ qualitatively from those supporting memory for individual faces. PMID:26336174

Internal representations for face detection: an application of noise-based image classification to BOLD responses.

PubMed

Nestor, Adrian; Vettel, Jean M; Tarr, Michael J

2013-11-01

What basic visual structures underlie human face detection and how can we extract such structures directly from the amplitude of neural responses elicited by face processing? Here, we address these issues by investigating an extension of noise-based image classification to BOLD responses recorded in high-level visual areas. First, we assess the applicability of this classification method to such data and, second, we explore its results in connection with the neural processing of faces. To this end, we construct luminance templates from white noise fields based on the response of face-selective areas in the human ventral cortex. Using behaviorally and neurally-derived classification images, our results reveal a family of simple but robust image structures subserving face representation and detection. Thus, we confirm the role played by classical face selective regions in face detection and we help clarify the representational basis of this perceptual function. From a theory standpoint, our findings support the idea of simple but highly diagnostic neurally-coded features for face detection. At the same time, from a methodological perspective, our work demonstrates the ability of noise-based image classification in conjunction with fMRI to help uncover the structure of high-level perceptual representations. Copyright © 2012 Wiley Periodicals, Inc.

Multiple Representations-Based Face Sketch-Photo Synthesis.

PubMed

Peng, Chunlei; Gao, Xinbo; Wang, Nannan; Tao, Dacheng; Li, Xuelong; Li, Jie

2016-11-01

Face sketch-photo synthesis plays an important role in law enforcement and digital entertainment. Most of the existing methods only use pixel intensities as the feature. Since face images can be described using features from multiple aspects, this paper presents a novel multiple representations-based face sketch-photo-synthesis method that adaptively combines multiple representations to represent an image patch. In particular, it combines multiple features from face images processed using multiple filters and deploys Markov networks to exploit the interacting relationships between the neighboring image patches. The proposed framework could be solved using an alternating optimization strategy and it normally converges in only five outer iterations in the experiments. Our experimental results on the Chinese University of Hong Kong (CUHK) face sketch database, celebrity photos, CUHK Face Sketch FERET Database, IIIT-D Viewed Sketch Database, and forensic sketches demonstrate the effectiveness of our method for face sketch-photo synthesis. In addition, cross-database and database-dependent style-synthesis evaluations demonstrate the generalizability of this novel method and suggest promising solutions for face identification in forensic science.

A special purpose knowledge-based face localization method

NASA Astrophysics Data System (ADS)

Hassanat, Ahmad; Jassim, Sabah

2008-04-01

This paper is concerned with face localization for visual speech recognition (VSR) system. Face detection and localization have got a great deal of attention in the last few years, because it is an essential pre-processing step in many techniques that handle or deal with faces, (e.g. age, face, gender, race and visual speech recognition). We shall present an efficient method for localization human's faces in video images captured on mobile constrained devices, under a wide variation in lighting conditions. We use a multiphase method that may include all or some of the following steps starting with image pre-processing, followed by a special purpose edge detection, then an image refinement step. The output image will be passed through a discrete wavelet decomposition procedure, and the computed LL sub-band at a certain level will be transformed into a binary image that will be scanned by using a special template to select a number of possible candidate locations. Finally, we fuse the scores from the wavelet step with scores determined by color information for the candidate location and employ a form of fuzzy logic to distinguish face from non-face locations. We shall present results of large number of experiments to demonstrate that the proposed face localization method is efficient and achieve high level of accuracy that outperforms existing general-purpose face detection methods.

Maximal likelihood correspondence estimation for face recognition across pose.

PubMed

Li, Shaoxin; Liu, Xin; Chai, Xiujuan; Zhang, Haihong; Lao, Shihong; Shan, Shiguang

2014-10-01

Due to the misalignment of image features, the performance of many conventional face recognition methods degrades considerably in across pose scenario. To address this problem, many image matching-based methods are proposed to estimate semantic correspondence between faces in different poses. In this paper, we aim to solve two critical problems in previous image matching-based correspondence learning methods: 1) fail to fully exploit face specific structure information in correspondence estimation and 2) fail to learn personalized correspondence for each probe image. To this end, we first build a model, termed as morphable displacement field (MDF), to encode face specific structure information of semantic correspondence from a set of real samples of correspondences calculated from 3D face models. Then, we propose a maximal likelihood correspondence estimation (MLCE) method to learn personalized correspondence based on maximal likelihood frontal face assumption. After obtaining the semantic correspondence encoded in the learned displacement, we can synthesize virtual frontal images of the profile faces for subsequent recognition. Using linear discriminant analysis method with pixel-intensity features, state-of-the-art performance is achieved on three multipose benchmarks, i.e., CMU-PIE, FERET, and MultiPIE databases. Owe to the rational MDF regularization and the usage of novel maximal likelihood objective, the proposed MLCE method can reliably learn correspondence between faces in different poses even in complex wild environment, i.e., labeled face in the wild database.

Image preprocessing study on KPCA-based face recognition

NASA Astrophysics Data System (ADS)

Li, Xuan; Li, Dehua

2015-12-01

Face recognition as an important biometric identification method, with its friendly, natural, convenient advantages, has obtained more and more attention. This paper intends to research a face recognition system including face detection, feature extraction and face recognition, mainly through researching on related theory and the key technology of various preprocessing methods in face detection process, using KPCA method, focuses on the different recognition results in different preprocessing methods. In this paper, we choose YCbCr color space for skin segmentation and choose integral projection for face location. We use erosion and dilation of the opening and closing operation and illumination compensation method to preprocess face images, and then use the face recognition method based on kernel principal component analysis method for analysis and research, and the experiments were carried out using the typical face database. The algorithms experiment on MATLAB platform. Experimental results show that integration of the kernel method based on PCA algorithm under certain conditions make the extracted features represent the original image information better for using nonlinear feature extraction method, which can obtain higher recognition rate. In the image preprocessing stage, we found that images under various operations may appear different results, so as to obtain different recognition rate in recognition stage. At the same time, in the process of the kernel principal component analysis, the value of the power of the polynomial function can affect the recognition result.

Heterogeneous sharpness for cross-spectral face recognition

NASA Astrophysics Data System (ADS)

Cao, Zhicheng; Schmid, Natalia A.

2017-05-01

Matching images acquired in different electromagnetic bands remains a challenging problem. An example of this type of comparison is matching active or passive infrared (IR) against a gallery of visible face images, known as cross-spectral face recognition. Among many unsolved issues is the one of quality disparity of the heterogeneous images. Images acquired in different spectral bands are of unequal image quality due to distinct imaging mechanism, standoff distances, or imaging environment, etc. To reduce the effect of quality disparity on the recognition performance, one can manipulate images to either improve the quality of poor-quality images or to degrade the high-quality images to the level of the quality of their heterogeneous counterparts. To estimate the level of discrepancy in quality of two heterogeneous images a quality metric such as image sharpness is needed. It provides a guidance in how much quality improvement or degradation is appropriate. In this work we consider sharpness as a relative measure of heterogeneous image quality. We propose a generalized definition of sharpness by first achieving image quality parity and then finding and building a relationship between the image quality of two heterogeneous images. Therefore, the new sharpness metric is named heterogeneous sharpness. Image quality parity is achieved by experimentally finding the optimal cross-spectral face recognition performance where quality of the heterogeneous images is varied using a Gaussian smoothing function with different standard deviation. This relationship is established using two models; one of them involves a regression model and the other involves a neural network. To train, test and validate the model, we use composite operators developed in our lab to extract features from heterogeneous face images and use the sharpness metric to evaluate the face image quality within each band. Images from three different spectral bands visible light, near infrared, and short-wave infrared are considered in this work. Both error of a regression model and validation error of a neural network are analyzed.

Convolution Operation of Optical Information via Quantum Storage

NASA Astrophysics Data System (ADS)

Li, Zhixiang; Liu, Jianji; Fan, Hongming; Zhang, Guoquan

2017-06-01

We proposed a novel method to achieve optical convolution of two input images via quantum storage based on electromagnetically induced transparency (EIT) effect. By placing an EIT media in the confocal Fourier plane of the 4f-imaging system, the optical convolution of the two input images can be achieved in the image plane.

Online image classification under monotonic decision boundary constraint

NASA Astrophysics Data System (ADS)

Lu, Cheng; Allebach, Jan; Wagner, Jerry; Pitta, Brandi; Larson, David; Guo, Yandong

2015-01-01

Image classification is a prerequisite for copy quality enhancement in all-in-one (AIO) device that comprises a printer and scanner, and which can be used to scan, copy and print. Different processing pipelines are provided in an AIO printer. Each of the processing pipelines is designed specifically for one type of input image to achieve the optimal output image quality. A typical approach to this problem is to apply Support Vector Machine to classify the input image and feed it to its corresponding processing pipeline. The online training SVM can help users to improve the performance of classification as input images accumulate. At the same time, we want to make quick decision on the input image to speed up the classification which means sometimes the AIO device does not need to scan the entire image to make a final decision. These two constraints, online SVM and quick decision, raise questions regarding: 1) what features are suitable for classification; 2) how we should control the decision boundary in online SVM training. This paper will discuss the compatibility of online SVM and quick decision capability.

Face-selective regions show invariance to linear, but not to non-linear, changes in facial images.

PubMed

Baseler, Heidi A; Young, Andrew W; Jenkins, Rob; Mike Burton, A; Andrews, Timothy J

2016-12-01

Familiar face recognition is remarkably invariant across huge image differences, yet little is understood concerning how image-invariant recognition is achieved. To investigate the neural correlates of invariance, we localized the core face-responsive regions and then compared the pattern of fMR-adaptation to different stimulus transformations in each region to behavioural data demonstrating the impact of the same transformations on familiar face recognition. In Experiment 1, we compared linear transformations of size and aspect ratio to a non-linear transformation affecting only part of the face. We found that adaptation to facial identity in face-selective regions showed invariance to linear changes, but there was no invariance to non-linear changes. In Experiment 2, we measured the sensitivity to non-linear changes that fell within the normal range of variation across face images. We found no adaptation to facial identity for any of the non-linear changes in the image, including to faces that varied in different levels of caricature. These results show a compelling difference in the sensitivity to linear compared to non-linear image changes in face-selective regions of the human brain that is only partially consistent with their effect on behavioural judgements of identity. We conclude that while regions such as the FFA may well be involved in the recognition of face identity, they are more likely to contribute to some form of normalisation that underpins subsequent recognition than to form the neural substrate of recognition per se. Copyright © 2016 Elsevier Ltd. All rights reserved.

The effect of input data transformations on object-based image analysis

PubMed Central

LIPPITT, CHRISTOPHER D.; COULTER, LLOYD L.; FREEMAN, MARY; LAMANTIA-BISHOP, JEFFREY; PANG, WYSON; STOW, DOUGLAS A.

2011-01-01

The effect of using spectral transform images as input data on segmentation quality and its potential effect on products generated by object-based image analysis are explored in the context of land cover classification in Accra, Ghana. Five image data transformations are compared to untransformed spectral bands in terms of their effect on segmentation quality and final product accuracy. The relationship between segmentation quality and product accuracy is also briefly explored. Results suggest that input data transformations can aid in the delineation of landscape objects by image segmentation, but the effect is idiosyncratic to the transformation and object of interest. PMID:21673829

Facial Asymmetry-Based Age Group Estimation: Role in Recognizing Age-Separated Face Images.

PubMed

Sajid, Muhammad; Taj, Imtiaz Ahmad; Bajwa, Usama Ijaz; Ratyal, Naeem Iqbal

2018-04-23

Face recognition aims to establish the identity of a person based on facial characteristics. On the other hand, age group estimation is the automatic calculation of an individual's age range based on facial features. Recognizing age-separated face images is still a challenging research problem due to complex aging processes involving different types of facial tissues, skin, fat, muscles, and bones. Certain holistic and local facial features are used to recognize age-separated face images. However, most of the existing methods recognize face images without incorporating the knowledge learned from age group estimation. In this paper, we propose an age-assisted face recognition approach to handle aging variations. Inspired by the observation that facial asymmetry is an age-dependent intrinsic facial feature, we first use asymmetric facial dimensions to estimate the age group of a given face image. Deeply learned asymmetric facial features are then extracted for face recognition using a deep convolutional neural network (dCNN). Finally, we integrate the knowledge learned from the age group estimation into the face recognition algorithm using the same dCNN. This integration results in a significant improvement in the overall performance compared to using the face recognition algorithm alone. The experimental results on two large facial aging datasets, the MORPH and FERET sets, show that the proposed age group estimation based on the face recognition approach yields superior performance compared to some existing state-of-the-art methods. © 2018 American Academy of Forensic Sciences.

Fast hierarchical knowledge-based approach for human face detection in color images

NASA Astrophysics Data System (ADS)

Jiang, Jun; Gong, Jie; Zhang, Guilin; Hu, Ruolan

2001-09-01

This paper presents a fast hierarchical knowledge-based approach for automatically detecting multi-scale upright faces in still color images. The approach consists of three levels. At the highest level, skin-like regions are determinated by skin model, which is based on the color attributes hue and saturation in HSV color space, as well color attributes red and green in normalized color space. In level 2, a new eye model is devised to select human face candidates in segmented skin-like regions. An important feature of the eye model is that it is independent of the scale of human face. So it is possible for finding human faces in different scale with scanning image only once, and it leads to reduction the computation time of face detection greatly. In level 3, a human face mosaic image model, which is consistent with physical structure features of human face well, is applied to judge whether there are face detects in human face candidate regions. This model includes edge and gray rules. Experiment results show that the approach has high robustness and fast speed. It has wide application perspective at human-computer interactions and visual telephone etc.

Personality judgments from everyday images of faces

PubMed Central

Sutherland, Clare A. M.; Rowley, Lauren E.; Amoaku, Unity T.; Daguzan, Ella; Kidd-Rossiter, Kate A.; Maceviciute, Ugne; Young, Andrew W.

2015-01-01

People readily make personality attributions to images of strangers' faces. Here we investigated the basis of these personality attributions as made to everyday, naturalistic face images. In a first study, we used 1000 highly varying “ambient image” face photographs to test the correspondence between personality judgments of the Big Five and dimensions known to underlie a range of facial first impressions: approachability, dominance, and youthful-attractiveness. Interestingly, the facial Big Five judgments were found to separate to some extent: judgments of openness, extraversion, emotional stability, and agreeableness were mainly linked to facial first impressions of approachability, whereas conscientiousness judgments involved a combination of approachability and dominance. In a second study we used average face images to investigate which main cues are used by perceivers to make impressions of the Big Five, by extracting consistent cues to impressions from the large variation in the original images. When forming impressions of strangers from highly varying, naturalistic face photographs, perceivers mainly seem to rely on broad facial cues to approachability, such as smiling. PMID:26579008

A smart technique for attendance system to recognize faces through parallelism

NASA Astrophysics Data System (ADS)

Prabhavathi, B.; Tanuja, V.; Madhu Viswanatham, V.; Rajashekhara Babu, M.

2017-11-01

Major part of recognising a person is face with the help of image processing techniques we can exploit the physical features of a person. In the old approach method that is used in schools and colleges it is there that the professor calls the student name and then the attendance for the students marked. Here in paper want to deviate from the old approach and go with the new approach by using techniques that are there in image processing. In this paper we presenting spontaneous presence for students in classroom. At first classroom image has been in use and after that image is kept in data record. For the images that are stored in the database we apply system algorithm which includes steps such as, histogram classification, noise removal, face detection and face recognition methods. So by using these steps we detect the faces and then compare it with the database. The attendance gets marked automatically if the system recognizes the faces.

High frame-rate en face optical coherence tomography system using KTN optical beam deflector

NASA Astrophysics Data System (ADS)

Ohmi, Masato; Shinya, Yusuke; Imai, Tadayuki; Toyoda, Seiji; Kobayashi, Junya; Sakamoto, Tadashi

2017-02-01

We developed high frame-rate en face optical coherence tomography (OCT) system using KTa1-xNbxO3 (KTN) optical beam deflector. In the imaging system, the fast scanning was performed at 200 kHz by the KTN optical beam deflector, while the slow scanning was performed at 800 Hz by the galvanometer mirror. As a preliminary experiment, we succeeded in obtaining en face OCT images of human fingerprint with a frame rate of 800 fps. This is the highest frame-rate obtained using time-domain (TD) en face OCT imaging. The 3D-OCT image of sweat gland was also obtained by our imaging system.

Development of novel high-speed en face optical coherence tomography system using KTN optical beam deflector

NASA Astrophysics Data System (ADS)

Ohmi, Masato; Fukuda, Akihiro; Miyazu, Jun; Ueno, Masahiro; Toyoda, Seiji; Kobayashi, Junya

2015-02-01

We developed a novel high-speed en face optical coherence tomography (OCT) system using a KTa1-xNbxO3 (KTN) optical beam deflector. Using the imaging system, fast scanning was performed at 200 kHz by the KTN beam deflector, while slow scanning was performed at 400 Hz by the galvanometer mirror. In a preliminary experiment, we obtained en face OCT images of a human fingerprint at 400 fps. This is the highest speed reported in time-domain en face OCT imaging and is comparable to the speed of swept-source OCT. A 3D-OCT image of a sweat gland was also obtained by our imaging system.

A robust human face detection algorithm

NASA Astrophysics Data System (ADS)

Raviteja, Thaluru; Karanam, Srikrishna; Yeduguru, Dinesh Reddy V.

2012-01-01

Human face detection plays a vital role in many applications like video surveillance, managing a face image database, human computer interface among others. This paper proposes a robust algorithm for face detection in still color images that works well even in a crowded environment. The algorithm uses conjunction of skin color histogram, morphological processing and geometrical analysis for detecting human faces. To reinforce the accuracy of face detection, we further identify mouth and eye regions to establish the presence/absence of face in a particular region of interest.

High-performance serial block-face SEM of nonconductive biological samples enabled by focal gas injection-based charge compensation.

PubMed

Deerinck, T J; Shone, T M; Bushong, E A; Ramachandra, R; Peltier, S T; Ellisman, M H

2018-05-01

A longstanding limitation of imaging with serial block-face scanning electron microscopy is specimen surface charging. This charging is largely due to the difficulties in making biological specimens and the resins in which they are embedded sufficiently conductive. Local accumulation of charge on the specimen surface can result in poor image quality and distortions. Even minor charging can lead to misalignments between sequential images of the block-face due to image jitter. Typically, variable-pressure SEM is used to reduce specimen charging, but this results in a significant reduction to spatial resolution, signal-to-noise ratio and overall image quality. Here we show the development and application of a simple system that effectively mitigates specimen charging by using focal gas injection of nitrogen over the sample block-face during imaging. A standard gas injection valve is paired with a precisely positioned but retractable application nozzle, which is mechanically coupled to the reciprocating action of the serial block-face ultramicrotome. This system enables the application of nitrogen gas precisely over the block-face during imaging while allowing the specimen chamber to be maintained under high vacuum to maximise achievable SEM image resolution. The action of the ultramicrotome drives the nozzle retraction, automatically moving it away from the specimen area during the cutting cycle of the knife. The device described was added to a Gatan 3View system with minimal modifications, allowing high-resolution block-face imaging of even the most charge prone of epoxy-embedded biological samples. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.

Study on image feature extraction and classification for human colorectal cancer using optical coherence tomography

NASA Astrophysics Data System (ADS)

Huang, Shu-Wei; Yang, Shan-Yi; Huang, Wei-Cheng; Chiu, Han-Mo; Lu, Chih-Wei

2011-06-01

Most of the colorectal cancer has grown from the adenomatous polyp. Adenomatous lesions have a well-documented relationship to colorectal cancer in previous studies. Thus, to detect the morphological changes between polyp and tumor can allow early diagnosis of colorectal cancer and simultaneous removal of lesions. OCT (Optical coherence tomography) has been several advantages including high resolution and non-invasive cross-sectional image in vivo. In this study, we investigated the relationship between the B-scan OCT image features and histology of malignant human colorectal tissues, also en-face OCT image and the endoscopic image pattern. The in-vitro experiments were performed by a swept-source optical coherence tomography (SS-OCT) system; the swept source has a center wavelength at 1310 nm and 160nm in wavelength scanning range which produced 6 um axial resolution. In the study, the en-face images were reconstructed by integrating the axial values in 3D OCT images. The reconstructed en-face images show the same roundish or gyrus-like pattern with endoscopy images. The pattern of en-face images relate to the stages of colon cancer. Endoscopic OCT technique would provide three-dimensional imaging and rapidly reconstruct en-face images which can increase the speed of colon cancer diagnosis. Our results indicate a great potential for early detection of colorectal adenomas by using the OCT imaging.

Reconstruction of input functions from a dynamic PET image with sequential administration of 15O2 and [Formula: see text] for noninvasive and ultra-rapid measurement of CBF, OEF, and CMRO2.

PubMed

Kudomi, Nobuyuki; Maeda, Yukito; Yamamoto, Hiroyuki; Yamamoto, Yuka; Hatakeyama, Tetsuhiro; Nishiyama, Yoshihiro

2018-05-01

CBF, OEF, and CMRO 2 images can be quantitatively assessed using PET. Their image calculation requires arterial input functions, which require invasive procedure. The aim of the present study was to develop a non-invasive approach with image-derived input functions (IDIFs) using an image from an ultra-rapid O 2 and C 15 O 2 protocol. Our technique consists of using a formula to express the input using tissue curve with rate constants. For multiple tissue curves, the rate constants were estimated so as to minimize the differences of the inputs using the multiple tissue curves. The estimated rates were used to express the inputs and the mean of the estimated inputs was used as an IDIF. The method was tested in human subjects ( n = 24). The estimated IDIFs were well-reproduced against the measured ones. The difference in the calculated CBF, OEF, and CMRO 2 values by the two methods was small (<10%) against the invasive method, and the values showed tight correlations ( r = 0.97). The simulation showed errors associated with the assumed parameters were less than ∼10%. Our results demonstrate that IDIFs can be reconstructed from tissue curves, suggesting the possibility of using a non-invasive technique to assess CBF, OEF, and CMRO 2 .

Do Infants Recognize the Arcimboldo Images as Faces? Behavioral and Near-Infrared Spectroscopic Study

ERIC Educational Resources Information Center

Kobayashi, Megumi; Otsuka, Yumiko; Nakato, Emi; Kanazawa, So; Yamaguchi, Masami K.; Kakigi, Ryusuke

2012-01-01

Arcimboldo images induce the perception of faces when shown upright despite the fact that only nonfacial objects such as vegetables and fruits are painted. In the current study, we examined whether infants recognize a face in the Arcimboldo images by using the preferential looking technique and near-infrared spectroscopy (NIRS). In the first…

Vector generator scan converter

DOEpatents

Moore, James M.; Leighton, James F.

1990-01-01

High printing speeds for graphics data are achieved with a laser printer by transmitting compressed graphics data from a main processor over an I/O (input/output) channel to a vector generator scan converter which reconstructs a full graphics image for input to the laser printer through a raster data input port. The vector generator scan converter includes a microprocessor with associated microcode memory containing a microcode instruction set, a working memory for storing compressed data, vector generator hardward for drawing a full graphic image from vector parameters calculated by the microprocessor, image buffer memory for storing the reconstructed graphics image and an output scanner for reading the graphics image data and inputting the data to the printer. The vector generator scan converter eliminates the bottleneck created by the I/O channel for transmitting graphics data from the main processor to the laser printer, and increases printer speed up to thirty fold.

Alpha-band rhythm modulation under the condition of subliminal face presentation: MEG study.

PubMed

Sakuraba, Satoshi; Kobayashi, Hana; Sakai, Shinya; Yokosawa, Koichi

2013-01-01

The human brain has two streams to process visual information: a dorsal stream and a ventral stream. Negative potential N170 or its magnetic counterpart M170 is known as the face-specific signal originating from the ventral stream. It is possible to present a visual image unconsciously by using continuous flash suppression (CFS), which is a visual masking technique adopting binocular rivalry. In this work, magnetoencephalograms were recorded during presentation of the three invisible images: face images, which are processed by the ventral stream; tool images, which could be processed by the dorsal stream, and a blank image. Alpha-band activities detected by sensors that are sensitive to M170 were compared. The alpha-band rhythm was suppressed more during presentation of face images than during presentation of the blank image (p=.028). The suppression remained for about 1 s after ending presentations. However, no significant difference was observed between tool and other images. These results suggest that alpha-band rhythm can be modulated also by unconscious visual images.

En face swept-source optical coherence tomographic analysis of X-linked juvenile retinoschisis.

PubMed

Ono, Shinji; Takahashi, Atsushi; Mase, Tomoko; Nagaoka, Taiji; Yoshida, Akitoshi

2016-07-01

To clarify the area of retinoschisis by X-linked juvenile retinoschisis (XLRS) using swept-source optical coherence tomography (SS-OCT) en face images. We report two cases of XLRS in the same family. The patients presented with bilateral blurred vision. The posterior segment examination showed a spoked-wheel pattern in the macula. SS-OCT cross-sectional images revealed widespread retinal splitting at the level of the inner nuclear layer bilaterally. We diagnosed XLRS. To evaluate the area of retinoschisis, we obtained en face SS-OCT images, which clearly visualized the area of retinoschisis seen as a sunflower-like structure in the macula. We report the findings on en face SS-OCT images from patients with XLRS. The en face images using SS-OCT showed the precise area of retinoschisis compared with the SS-OCT thickness map and are useful for managing patients with XLRS.

Morphological-transformation-based technique of edge detection and skeletonization of an image using a single spatial light modulator

NASA Astrophysics Data System (ADS)

Munshi, Soumika; Datta, A. K.

2003-03-01

A technique of optically detecting the edge and skeleton of an image by defining shift operations for morphological transformation is described. A (2 × 2) source array, which acts as the structuring element of morphological operations, casts four angularly shifted optical projections of the input image. The resulting dilated image, when superimposed with the complementary input image, produces the edge image. For skeletonization, the source array casts four partially overlapped output images of the inverted input image, which is negated, and the resultant image is recorded in a CCD camera. This overlapped eroded image is again eroded and then dilated, producing an opened image. The difference between the eroded and opened image is then computed, resulting in a thinner image. This procedure of obtaining a thinned image is iterated until the difference image becomes zero, maintaining the connectivity conditions. The technique has been optically implemented using a single spatial modulator and has the advantage of single-instruction parallel processing of the image. The techniques have been tested both for binary and grey images.

Influence of speckle image reconstruction on photometric precision for large solar telescopes

NASA Astrophysics Data System (ADS)

Peck, C. L.; Wöger, F.; Marino, J.

2017-11-01

Context. High-resolution observations from large solar telescopes require adaptive optics (AO) systems to overcome image degradation caused by Earth's turbulent atmosphere. AO corrections are, however, only partial. Achieving near-diffraction limited resolution over a large field of view typically requires post-facto image reconstruction techniques to reconstruct the source image. Aims: This study aims to examine the expected photometric precision of amplitude reconstructed solar images calibrated using models for the on-axis speckle transfer functions and input parameters derived from AO control data. We perform a sensitivity analysis of the photometric precision under variations in the model input parameters for high-resolution solar images consistent with four-meter class solar telescopes. Methods: Using simulations of both atmospheric turbulence and partial compensation by an AO system, we computed the speckle transfer function under variations in the input parameters. We then convolved high-resolution numerical simulations of the solar photosphere with the simulated atmospheric transfer function, and subsequently deconvolved them with the model speckle transfer function to obtain a reconstructed image. To compute the resulting photometric precision, we compared the intensity of the original image with the reconstructed image. Results: The analysis demonstrates that high photometric precision can be obtained for speckle amplitude reconstruction using speckle transfer function models combined with AO-derived input parameters. Additionally, it shows that the reconstruction is most sensitive to the input parameter that characterizes the atmospheric distortion, and sub-2% photometric precision is readily obtained when it is well estimated.

Pose-Invariant Face Recognition via RGB-D Images.

PubMed

Sang, Gaoli; Li, Jing; Zhao, Qijun

2016-01-01

Three-dimensional (3D) face models can intrinsically handle large pose face recognition problem. In this paper, we propose a novel pose-invariant face recognition method via RGB-D images. By employing depth, our method is able to handle self-occlusion and deformation, both of which are challenging problems in two-dimensional (2D) face recognition. Texture images in the gallery can be rendered to the same view as the probe via depth. Meanwhile, depth is also used for similarity measure via frontalization and symmetric filling. Finally, both texture and depth contribute to the final identity estimation. Experiments on Bosphorus, CurtinFaces, Eurecom, and Kiwi databases demonstrate that the additional depth information has improved the performance of face recognition with large pose variations and under even more challenging conditions.

Automatic face recognition in HDR imaging

NASA Astrophysics Data System (ADS)

Pereira, Manuela; Moreno, Juan-Carlos; Proença, Hugo; Pinheiro, António M. G.

2014-05-01

The gaining popularity of the new High Dynamic Range (HDR) imaging systems is raising new privacy issues caused by the methods used for visualization. HDR images require tone mapping methods for an appropriate visualization on conventional and non-expensive LDR displays. These visualization methods might result in completely different visualization raising several issues on privacy intrusion. In fact, some visualization methods result in a perceptual recognition of the individuals, while others do not even show any identity. Although perceptual recognition might be possible, a natural question that can rise is how computer based recognition will perform using tone mapping generated images? In this paper, a study where automatic face recognition using sparse representation is tested with images that result from common tone mapping operators applied to HDR images. Its ability for the face identity recognition is described. Furthermore, typical LDR images are used for the face recognition training.

Eye-motion-corrected optical coherence tomography angiography using Lissajous scanning.

PubMed

Chen, Yiwei; Hong, Young-Joo; Makita, Shuichi; Yasuno, Yoshiaki

2018-03-01

To correct eye motion artifacts in en face optical coherence tomography angiography (OCT-A) images, a Lissajous scanning method with subsequent software-based motion correction is proposed. The standard Lissajous scanning pattern is modified to be compatible with OCT-A and a corresponding motion correction algorithm is designed. The effectiveness of our method was demonstrated by comparing en face OCT-A images with and without motion correction. The method was further validated by comparing motion-corrected images with scanning laser ophthalmoscopy images, and the repeatability of the method was evaluated using a checkerboard image. A motion-corrected en face OCT-A image from a blinking case is presented to demonstrate the ability of the method to deal with eye blinking. Results show that the method can produce accurate motion-free en face OCT-A images of the posterior segment of the eye in vivo .

Perceptual expertise in forensic facial image comparison.

PubMed

White, David; Phillips, P Jonathon; Hahn, Carina A; Hill, Matthew; O'Toole, Alice J

2015-09-07

Forensic facial identification examiners are required to match the identity of faces in images that vary substantially, owing to changes in viewing conditions and in a person's appearance. These identifications affect the course and outcome of criminal investigations and convictions. Despite calls for research on sources of human error in forensic examination, existing scientific knowledge of face matching accuracy is based, almost exclusively, on people without formal training. Here, we administered three challenging face matching tests to a group of forensic examiners with many years' experience of comparing face images for law enforcement and government agencies. Examiners outperformed untrained participants and computer algorithms, thereby providing the first evidence that these examiners are experts at this task. Notably, computationally fusing responses of multiple experts produced near-perfect performance. Results also revealed qualitative differences between expert and non-expert performance. First, examiners' superiority was greatest at longer exposure durations, suggestive of more entailed comparison in forensic examiners. Second, experts were less impaired by image inversion than non-expert students, contrasting with face memory studies that show larger face inversion effects in high performers. We conclude that expertise in matching identity across unfamiliar face images is supported by processes that differ qualitatively from those supporting memory for individual faces. © 2015 The Author(s).

Self-organized Evaluation of Dynamic Hand Gestures for Sign Language Recognition

NASA Astrophysics Data System (ADS)

Buciu, Ioan; Pitas, Ioannis

Two main theories exist with respect to face encoding and representation in the human visual system (HVS). The first one refers to the dense (holistic) representation of the face, where faces have "holon"-like appearance. The second one claims that a more appropriate face representation is given by a sparse code, where only a small fraction of the neural cells corresponding to face encoding is activated. Theoretical and experimental evidence suggest that the HVS performs face analysis (encoding, storing, face recognition, facial expression recognition) in a structured and hierarchical way, where both representations have their own contribution and goal. According to neuropsychological experiments, it seems that encoding for face recognition, relies on holistic image representation, while a sparse image representation is used for facial expression analysis and classification. From the computer vision perspective, the techniques developed for automatic face and facial expression recognition fall into the same two representation types. Like in Neuroscience, the techniques which perform better for face recognition yield a holistic image representation, while those techniques suitable for facial expression recognition use a sparse or local image representation. The proposed mathematical models of image formation and encoding try to simulate the efficient storing, organization and coding of data in the human cortex. This is equivalent with embedding constraints in the model design regarding dimensionality reduction, redundant information minimization, mutual information minimization, non-negativity constraints, class information, etc. The presented techniques are applied as a feature extraction step followed by a classification method, which also heavily influences the recognition results.

Robust Point Set Matching for Partial Face Recognition.

PubMed

Weng, Renliang; Lu, Jiwen; Tan, Yap-Peng

2016-03-01

Over the past three decades, a number of face recognition methods have been proposed in computer vision, and most of them use holistic face images for person identification. In many real-world scenarios especially some unconstrained environments, human faces might be occluded by other objects, and it is difficult to obtain fully holistic face images for recognition. To address this, we propose a new partial face recognition approach to recognize persons of interest from their partial faces. Given a pair of gallery image and probe face patch, we first detect keypoints and extract their local textural features. Then, we propose a robust point set matching method to discriminatively match these two extracted local feature sets, where both the textural information and geometrical information of local features are explicitly used for matching simultaneously. Finally, the similarity of two faces is converted as the distance between these two aligned feature sets. Experimental results on four public face data sets show the effectiveness of the proposed approach.

Hyperspectral face recognition with spatiospectral information fusion and PLS regression.

PubMed

Uzair, Muhammad; Mahmood, Arif; Mian, Ajmal

2015-03-01

Hyperspectral imaging offers new opportunities for face recognition via improved discrimination along the spectral dimension. However, it poses new challenges, including low signal-to-noise ratio, interband misalignment, and high data dimensionality. Due to these challenges, the literature on hyperspectral face recognition is not only sparse but is limited to ad hoc dimensionality reduction techniques and lacks comprehensive evaluation. We propose a hyperspectral face recognition algorithm using a spatiospectral covariance for band fusion and partial least square regression for classification. Moreover, we extend 13 existing face recognition techniques, for the first time, to perform hyperspectral face recognition.We formulate hyperspectral face recognition as an image-set classification problem and evaluate the performance of seven state-of-the-art image-set classification techniques. We also test six state-of-the-art grayscale and RGB (color) face recognition algorithms after applying fusion techniques on hyperspectral images. Comparison with the 13 extended and five existing hyperspectral face recognition techniques on three standard data sets show that the proposed algorithm outperforms all by a significant margin. Finally, we perform band selection experiments to find the most discriminative bands in the visible and near infrared response spectrum.

Team Electronic Gameplay Combining Different Means of Control

NASA Technical Reports Server (NTRS)

Palsson, Olafur S. (Inventor); Pope, Alan T. (Inventor)

2014-01-01

Disclosed are methods and apparatuses provided for modifying the effect of an operator controlled input device on an interactive device to encourage the self-regulation of at least one physiological activity by a person different than the operator. The interactive device comprises a display area which depicts images and apparatus for receiving at least one input from the operator controlled input device to thus permit the operator to control and interact with at least some of the depicted images. One effect modification comprises measurement of the physiological activity of a person different from the operator, while modifying the ability of the operator to control and interact with at least some of the depicted images by modifying the input from the operator controlled input device in response to changes in the measured physiological signal.

Multimodal Translation System Using Texture-Mapped Lip-Sync Images for Video Mail and Automatic Dubbing Applications

NASA Astrophysics Data System (ADS)

Morishima, Shigeo; Nakamura, Satoshi

2004-12-01

We introduce a multimodal English-to-Japanese and Japanese-to-English translation system that also translates the speaker's speech motion by synchronizing it to the translated speech. This system also introduces both a face synthesis technique that can generate any viseme lip shape and a face tracking technique that can estimate the original position and rotation of a speaker's face in an image sequence. To retain the speaker's facial expression, we substitute only the speech organ's image with the synthesized one, which is made by a 3D wire-frame model that is adaptable to any speaker. Our approach provides translated image synthesis with an extremely small database. The tracking motion of the face from a video image is performed by template matching. In this system, the translation and rotation of the face are detected by using a 3D personal face model whose texture is captured from a video frame. We also propose a method to customize the personal face model by using our GUI tool. By combining these techniques and the translated voice synthesis technique, an automatic multimodal translation can be achieved that is suitable for video mail or automatic dubbing systems into other languages.

Still-to-video face recognition in unconstrained environments

NASA Astrophysics Data System (ADS)

Wang, Haoyu; Liu, Changsong; Ding, Xiaoqing

2015-02-01

Face images from video sequences captured in unconstrained environments usually contain several kinds of variations, e.g. pose, facial expression, illumination, image resolution and occlusion. Motion blur and compression artifacts also deteriorate recognition performance. Besides, in various practical systems such as law enforcement, video surveillance and e-passport identification, only a single still image per person is enrolled as the gallery set. Many existing methods may fail to work due to variations in face appearances and the limit of available gallery samples. In this paper, we propose a novel approach for still-to-video face recognition in unconstrained environments. By assuming that faces from still images and video frames share the same identity space, a regularized least squares regression method is utilized to tackle the multi-modality problem. Regularization terms based on heuristic assumptions are enrolled to avoid overfitting. In order to deal with the single image per person problem, we exploit face variations learned from training sets to synthesize virtual samples for gallery samples. We adopt a learning algorithm combining both affine/convex hull-based approach and regularizations to match image sets. Experimental results on a real-world dataset consisting of unconstrained video sequences demonstrate that our method outperforms the state-of-the-art methods impressively.

Multiple Mice Based Collaborative One-to-One Learning

ERIC Educational Resources Information Center

Infante, Cristian; Hidalgo, Pedro; Nussbaum, Miguel; Alarcon, Rosa; Gottlieb, Andres

2009-01-01

Exchange is a collaborative learning application, originally developed for wirelessly interconnected Pocket PCs, that provides support for students and a teacher performing a face-to-face computer supported collaborative learning (CSCL) activity in a Single Input/Single Display (SISD) mode. We extend the application to support a single display…

Laser Doppler imaging of cutaneous blood flow through transparent face masks: a necessary preamble to computer-controlled rapid prototyping fabrication with submillimeter precision.

PubMed

Allely, Rebekah R; Van-Buendia, Lan B; Jeng, James C; White, Patricia; Wu, Jingshu; Niszczak, Jonathan; Jordan, Marion H

2008-01-01

A paradigm shift in management of postburn facial scarring is lurking "just beneath the waves" with the widespread availability of two recent technologies: precise three-dimensional scanning/digitizing of complex surfaces and computer-controlled rapid prototyping three-dimensional "printers". Laser Doppler imaging may be the sensible method to track the scar hyperemia that should form the basis of assessing progress and directing incremental changes in the digitized topographical face mask "prescription". The purpose of this study was to establish feasibility of detecting perfusion through transparent face masks using the Laser Doppler Imaging scanner. Laser Doppler images of perfusion were obtained at multiple facial regions on five uninjured staff members. Images were obtained without a mask, followed by images with a loose fitting mask with and without a silicone liner, and then with a tight fitting mask with and without a silicone liner. Right and left oblique images, in addition to the frontal images, were used to overcome unobtainable measurements at the extremes of face mask curvature. General linear model, mixed model, and t tests were used for data analysis. Three hundred seventy-five measurements were used for analysis, with a mean perfusion unit of 299 and pixel validity of 97%. The effect of face mask pressure with and without the silicone liner was readily quantified with significant changes in mean cutaneous blood flow (P < .5). High valid pixel rate laser Doppler imager flow data can be obtained through transparent face masks. Perfusion decreases with the application of pressure and with silicone. Every participant measured differently in perfusion units; however, consistent perfusion patterns in the face were observed.

Perceptual distortion of face deletion by local anaesthesia of the human lips and teeth.

PubMed

Türker, Kemal S; Yeo, Purdee L M; Gandevia, Simon C

2005-08-01

As visual guidance of facial movements is impossible, accurate movements for speech and mastication require an established body image that is formed via the information from mechanoreceptors in the skin, mucosa, periodontium, and proprioceptors in the facial and masticatory muscles and in the jaw joints. In this study we aimed to investigate how the acute deafferentation of lips and teeth alters the established image of lips, teeth and the thumb. We used a psychophysical method to determine whether the perceived sizes of the upper lip and front teeth change when the sensory input from the lips and front teeth is fully blocked. We also examined the perceived size of the thumb to test for acute interactions between the thumb and facial structures. Local anaesthetic blocking of upper lip and upper front teeth significantly increased the perceived size of the upper lip by as much as 100% (range 21-100%) in ten out of eleven subjects tested (overall mean 52%; p=0.001). The perceived size of the upper teeth also significantly increased by as much as 155% (range 30-155%) in eight of the eleven subjects during anaesthesia (overall mean 41%; p=0.035). When the region of anaesthesia was increased and both upper and lower teeth and lips were anaesthetised, the perceived size of the upper lip again increased, by 53% (p=0.040), but the change in perceived size of the upper front teeth (18%) was not significant (p=0.206). In both studies there was no change in perceived size of the thumb. The results illustrate the labile central interaction between sensory inputs and the importance of feedback from peripheral afferents in generating the subjective facial image. The timing, level, and area of anaesthesia may be important modifiers of these interactions.

SOURCE EXPLORER: Towards Web Browser Based Tools for Astronomical Source Visualization and Analysis

NASA Astrophysics Data System (ADS)

Young, M. D.; Hayashi, S.; Gopu, A.

2014-05-01

As a new generation of large format, high-resolution imagers come online (ODI, DECAM, LSST, etc.) we are faced with the daunting prospect of astronomical images containing upwards of hundreds of thousands of identifiable sources. Visualizing and interacting with such large datasets using traditional astronomical tools appears to be unfeasible, and a new approach is required. We present here a method for the display and analysis of arbitrarily large source datasets using dynamically scaling levels of detail, enabling scientists to rapidly move from large-scale spatial overviews down to the level of individual sources and everything in-between. Based on the recognized standards of HTML5+JavaScript, we enable observers and archival users to interact with their images and sources from any modern computer without having to install specialized software. We demonstrate the ability to produce large-scale source lists from the images themselves, as well as overlaying data from publicly available source ( 2MASS, GALEX, SDSS, etc.) or user provided source lists. A high-availability cluster of computational nodes allows us to produce these source maps on demand and customized based on user input. User-generated source lists and maps are persistent across sessions and are available for further plotting, analysis, refinement, and culling.

Gender classification system in uncontrolled environments

NASA Astrophysics Data System (ADS)

Zeng, Pingping; Zhang, Yu-Jin; Duan, Fei

2011-01-01

Most face analysis systems available today perform mainly on restricted databases of images in terms of size, age, illumination. In addition, it is frequently assumed that all images are frontal and unconcealed. Actually, in a non-guided real-time supervision, the face pictures taken may often be partially covered and with head rotation less or more. In this paper, a special system supposed to be used in real-time surveillance with un-calibrated camera and non-guided photography is described. It mainly consists of five parts: face detection, non-face filtering, best-angle face selection, texture normalization, and gender classification. Emphases are focused on non-face filtering and best-angle face selection parts as well as texture normalization. Best-angle faces are figured out by PCA reconstruction, which equals to an implicit face alignment and results in a huge increase of the accuracy for gender classification. Dynamic skin model and a masked PCA reconstruction algorithm are applied to filter out faces detected in error. In order to fully include facial-texture and shape-outline features, a hybrid feature that is a combination of Gabor wavelet and PHoG (pyramid histogram of gradients) was proposed to equitable inner texture and outer contour. Comparative study on the effects of different non-face filtering and texture masking methods in the context of gender classification by SVM is reported through experiments on a set of UT (a company name) face images, a large number of internet images and CAS (Chinese Academy of Sciences) face database. Some encouraging results are obtained.

Motion facilitates face perception across changes in viewpoint and expression in older adults.

PubMed

Maguinness, Corrina; Newell, Fiona N

2014-12-01

Faces are inherently dynamic stimuli. However, face perception in younger adults appears to be mediated by the ability to extract structural cues from static images and a benefit of motion is inconsistent. In contrast, static face processing is poorer and more image-dependent in older adults. We therefore compared the role of facial motion in younger and older adults to assess whether motion can enhance perception when static cues are insufficient. In our studies, older and younger adults learned faces presented in motion or in a sequence of static images, containing rigid (viewpoint) or nonrigid (expression) changes. Immediately following learning, participants matched a static test image to the learned face which varied by viewpoint (Experiment 1) or expression (Experiment 2) and was either learned or novel. First, we found an age effect with better face matching performance in younger than in older adults. However, we observed face matching performance improved in the older adult group, across changes in viewpoint and expression, when faces were learned in motion relative to static presentation. There was no benefit for facial (nonrigid) motion when the task involved matching inverted faces (Experiment 3), suggesting that the ability to use dynamic face information for the purpose of recognition reflects motion encoding which is specific to upright faces. Our results suggest that ageing may offer a unique insight into how dynamic cues support face processing, which may not be readily observed in younger adults' performance. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Segmentation and learning in the quantitative analysis of microscopy images

NASA Astrophysics Data System (ADS)

Ruggiero, Christy; Ross, Amy; Porter, Reid

2015-02-01

In material science and bio-medical domains the quantity and quality of microscopy images is rapidly increasing and there is a great need to automatically detect, delineate and quantify particles, grains, cells, neurons and other functional "objects" within these images. These are challenging problems for image processing because of the variability in object appearance that inevitably arises in real world image acquisition and analysis. One of the most promising (and practical) ways to address these challenges is interactive image segmentation. These algorithms are designed to incorporate input from a human operator to tailor the segmentation method to the image at hand. Interactive image segmentation is now a key tool in a wide range of applications in microscopy and elsewhere. Historically, interactive image segmentation algorithms have tailored segmentation on an image-by-image basis, and information derived from operator input is not transferred between images. But recently there has been increasing interest to use machine learning in segmentation to provide interactive tools that accumulate and learn from the operator input over longer periods of time. These new learning algorithms reduce the need for operator input over time, and can potentially provide a more dynamic balance between customization and automation for different applications. This paper reviews the state of the art in this area, provides a unified view of these algorithms, and compares the segmentation performance of various design choices.

Face Hallucination with Linear Regression Model in Semi-Orthogonal Multilinear PCA Method

NASA Astrophysics Data System (ADS)

Asavaskulkiet, Krissada

2018-04-01

In this paper, we propose a new face hallucination technique, face images reconstruction in HSV color space with a semi-orthogonal multilinear principal component analysis method. This novel hallucination technique can perform directly from tensors via tensor-to-vector projection by imposing the orthogonality constraint in only one mode. In our experiments, we use facial images from FERET database to test our hallucination approach which is demonstrated by extensive experiments with high-quality hallucinated color faces. The experimental results assure clearly demonstrated that we can generate photorealistic color face images by using the SO-MPCA subspace with a linear regression model.

Local structure-based image decomposition for feature extraction with applications to face recognition.

PubMed

Qian, Jianjun; Yang, Jian; Xu, Yong

2013-09-01

This paper presents a robust but simple image feature extraction method, called image decomposition based on local structure (IDLS). It is assumed that in the local window of an image, the macro-pixel (patch) of the central pixel, and those of its neighbors, are locally linear. IDLS captures the local structural information by describing the relationship between the central macro-pixel and its neighbors. This relationship is represented with the linear representation coefficients determined using ridge regression. One image is actually decomposed into a series of sub-images (also called structure images) according to a local structure feature vector. All the structure images, after being down-sampled for dimensionality reduction, are concatenated into one super-vector. Fisher linear discriminant analysis is then used to provide a low-dimensional, compact, and discriminative representation for each super-vector. The proposed method is applied to face recognition and examined using our real-world face image database, NUST-RWFR, and five popular, publicly available, benchmark face image databases (AR, Extended Yale B, PIE, FERET, and LFW). Experimental results show the performance advantages of IDLS over state-of-the-art algorithms.

Choosing face: The curse of self in profile image selection.

PubMed

White, David; Sutherland, Clare A M; Burton, Amy L

2017-01-01

People draw automatic social inferences from photos of unfamiliar faces and these first impressions are associated with important real-world outcomes. Here we examine the effect of selecting online profile images on first impressions. We model the process of profile image selection by asking participants to indicate the likelihood that images of their own face ("self-selection") and of an unfamiliar face ("other-selection") would be used as profile images on key social networking sites. Across two large Internet-based studies (n = 610), in line with predictions, image selections accentuated favorable social impressions and these impressions were aligned to the social context of the networking sites. However, contrary to predictions based on people's general expertise in self-presentation, other-selected images conferred more favorable impressions than self-selected images. We conclude that people make suboptimal choices when selecting their own profile pictures, such that self-perception places important limits on facial first impressions formed by others. These results underscore the dynamic nature of person perception in real-world contexts.

Effects of spatial resolution ratio in image fusion

USGS Publications Warehouse

Ling, Y.; Ehlers, M.; Usery, E.L.; Madden, M.

2008-01-01

In image fusion, the spatial resolution ratio can be defined as the ratio between the spatial resolution of the high-resolution panchromatic image and that of the low-resolution multispectral image. This paper attempts to assess the effects of the spatial resolution ratio of the input images on the quality of the fused image. Experimental results indicate that a spatial resolution ratio of 1:10 or higher is desired for optimal multisensor image fusion provided the input panchromatic image is not downsampled to a coarser resolution. Due to the synthetic pixels generated from resampling, the quality of the fused image decreases as the spatial resolution ratio decreases (e.g. from 1:10 to 1:30). However, even with a spatial resolution ratio as small as 1:30, the quality of the fused image is still better than the original multispectral image alone for feature interpretation. In cases where the spatial resolution ratio is too small (e.g. 1:30), to obtain better spectral integrity of the fused image, one may downsample the input high-resolution panchromatic image to a slightly lower resolution before fusing it with the multispectral image.

Healthcare Policy Statement on the Utility of Coronary Computed Tomography for Evaluation of Cardiovascular Conditions and Preventive Healthcare: From the Health Policy Working Group of the Society of Cardiovascular Computed Tomography.

PubMed

Slim, Ahmad M; Jerome, Scott; Blankstein, Ron; Weigold, Wm Guy; Patel, Amit R; Kalra, Dinesh K; Miller, Ryan; Branch, Kelley; Rabbat, Mark G; Hecht, Harvey; Nicol, Edward D; Villines, Todd C; Shaw, Leslee J

The rising cost of healthcare is prompting numerous policy and advocacy discussions regarding strategies for constraining growth and creating a more efficient and effective healthcare system. Cardiovascular imaging is central to the care of patients at risk of, and living with, heart disease. Estimates are that utilization of cardiovascular imaging exceeds 20 million studies per year. The Society of Cardiovascular CT (SCCT), alongside Rush University Medical Center, and in collaboration with government agencies, regional payers, and industry healthcare experts met in November 2016 in Chicago, IL to evaluate obstacles and hurdles facing the cardiovascular imaging community and how they can contribute to efficacy while maintaining or even improving outcomes and quality. The summit incorporated inputs from payers, providers, and patients' perspectives, providing a platform for all voices to be heard, allowing for a constructive dialogue with potential solutions moving forward. This article outlines the proceedings from the summit, with a detailed review of past hurdles, current status, and potential solutions as we move forward in an ever-changing healthcare landscape. Copyright © 2017 Society of Cardiovascular Computed Tomography. All rights reserved.

Doppler optical coherence tomography imaging of local fluid flow and shear stress within microporous scaffolds

NASA Astrophysics Data System (ADS)

Jia, Yali; Bagnaninchi, Pierre O.; Yang, Ying; Haj, Alicia El; Hinds, Monica T.; Kirkpatrick, Sean J.; Wang, Ruikang K.

2009-05-01

Establishing a relationship between perfusion rate and fluid shear stress in a 3D cell culture environment is an ongoing and challenging task faced by tissue engineers. We explore Doppler optical coherence tomography (DOCT) as a potential imaging tool for in situ monitoring of local fluid flow profiles inside porous chitosan scaffolds. From the measured fluid flow profiles, the fluid shear stresses are evaluated. We examine the localized fluid flow and shear stress within low- and high-porosity chitosan scaffolds, which are subjected to a constant input flow rate of 0.5 ml.min-1. The DOCT results show that the behavior of the fluid flow and shear stress in micropores is strongly dependent on the micropore interconnectivity, porosity, and size of pores within the scaffold. For low-porosity and high-porosity chitosan scaffolds examined, the measured local fluid flow and shear stress varied from micropore to micropore, with a mean shear stress of 0.49+/-0.3 dyn.cm-2 and 0.38+/-0.2 dyn.cm-2, respectively. In addition, we show that the scaffold's porosity and interconnectivity can be quantified by combining analyses of the 3D structural and flow images obtained from DOCT.

Image Enhancement via Subimage Histogram Equalization Based on Mean and Variance

PubMed Central

2017-01-01

This paper puts forward a novel image enhancement method via Mean and Variance based Subimage Histogram Equalization (MVSIHE), which effectively increases the contrast of the input image with brightness and details well preserved compared with some other methods based on histogram equalization (HE). Firstly, the histogram of input image is divided into four segments based on the mean and variance of luminance component, and the histogram bins of each segment are modified and equalized, respectively. Secondly, the result is obtained via the concatenation of the processed subhistograms. Lastly, the normalization method is deployed on intensity levels, and the integration of the processed image with the input image is performed. 100 benchmark images from a public image database named CVG-UGR-Database are used for comparison with other state-of-the-art methods. The experiment results show that the algorithm can not only enhance image information effectively but also well preserve brightness and details of the original image. PMID:29403529

A text input system developed by using lips image recognition based LabVIEW for the seriously disabled.

PubMed

Chen, S C; Shao, C L; Liang, C K; Lin, S W; Huang, T H; Hsieh, M C; Yang, C H; Luo, C H; Wuo, C M

2004-01-01

In this paper, we present a text input system for the seriously disabled by using lips image recognition based on LabVIEW. This system can be divided into the software subsystem and the hardware subsystem. In the software subsystem, we adopted the technique of image processing to recognize the status of mouth-opened or mouth-closed depending the relative distance between the upper lip and the lower lip. In the hardware subsystem, parallel port built in PC is used to transmit the recognized result of mouth status to the Morse-code text input system. Integrating the software subsystem with the hardware subsystem, we implement a text input system by using lips image recognition programmed in LabVIEW language. We hope the system can help the seriously disabled to communicate with normal people more easily.

Characteristics and Innovations in American Education of Relevance for Indian Education.

ERIC Educational Resources Information Center

Stambler, Moses

American responses to educational problems faced around the globe can serve as models for developing nations. The following characteristics of American education with particular relevance for education in developing nations have been organized as inputs, structures and strategies, and outputs. Inputs to the system of American education, defined in…

An objective electrophysiological marker of face individualisation impairment in acquired prosopagnosia with fast periodic visual stimulation.

PubMed

Liu-Shuang, Joan; Torfs, Katrien; Rossion, Bruno

2016-03-01

One of the most striking pieces of evidence for a specialised face processing system in humans is acquired prosopagnosia, i.e. the inability to individualise faces following brain damage. However, a sensitive and objective non-behavioural marker for this deficit is difficult to provide with standard event-related potentials (ERPs), such as the well-known face-related N170 component reported and investigated in-depth by our late distinguished colleague Shlomo Bentin. Here we demonstrate that fast periodic visual stimulation (FPVS) in electrophysiology can quantify face individualisation impairment in acquired prosopagnosia. In Experiment 1 (Liu-Shuang et al., 2014), identical faces were presented at a rate of 5.88 Hz (i.e., ≈ 6 images/s, SOA=170 ms, 1 fixation per image), with different faces appearing every 5th face (5.88 Hz/5=1.18 Hz). Responses of interest were identified at these predetermined frequencies (i.e., objectively) in the EEG frequency-domain data. A well-studied case of acquired prosopagnosia (PS) and a group of age- and gender-matched controls completed only 4 × 1-min stimulation sequences, with an orthogonal fixation cross task. Contrarily to controls, PS did not show face individualisation responses at 1.18 Hz, in line with her prosopagnosia. However, her response at 5.88 Hz, reflecting general visual processing, was within the normal range. In Experiment 2 (Rossion et al., 2015), we presented natural (i.e., unsegmented) images of objects at 5.88 Hz, with face images shown every 5th image (1.18 Hz). In accordance with her preserved ability to categorise a face as a face, and despite extensive brain lesions potentially affecting the overall EEG signal-to-noise ratio, PS showed 1.18 Hz face-selective responses within the normal range. Collectively, these findings show that fast periodic visual stimulation provides objective and sensitive electrophysiological markers of preserved and impaired face processing abilities in the neuropsychological population. Copyright © 2015 Elsevier Ltd. All rights reserved.

Interactive display system having a scaled virtual target zone

DOEpatents

Veligdan, James T.; DeSanto, Leonard

2006-06-13

A display system includes a waveguide optical panel having an inlet face and an opposite outlet face. A projector and imaging device cooperate with the panel for projecting a video image thereon. An optical detector bridges at least a portion of the waveguides for detecting a location on the outlet face within a target zone of an inbound light spot. A controller is operatively coupled to the imaging device and detector for displaying a cursor on the outlet face corresponding with the detected location of the spot within the target zone.

The Influence of Social Comparison on Visual Representation of One's Face

PubMed Central

Zell, Ethan; Balcetis, Emily

2012-01-01

Can the effects of social comparison extend beyond explicit evaluation to visual self-representation—a perceptual stimulus that is objectively verifiable, unambiguous, and frequently updated? We morphed images of participants' faces with attractive and unattractive references. With access to a mirror, participants selected the morphed image they perceived as depicting their face. Participants who engaged in upward comparison with relevant attractive targets selected a less attractive morph compared to participants exposed to control images (Study 1). After downward comparison with relevant unattractive targets compared to control images, participants selected a more attractive morph (Study 2). Biased representations were not the products of cognitive accessibility of beauty constructs; comparisons did not influence representations of strangers' faces (Study 3). We discuss implications for vision, social comparison, and body image. PMID:22662124

Ensemble coding of face identity is present but weaker in congenital prosopagnosia.

PubMed

Robson, Matthew K; Palermo, Romina; Jeffery, Linda; Neumann, Markus F

2018-03-01

Individuals with congenital prosopagnosia (CP) are impaired at identifying individual faces but do not appear to show impairments in extracting the average identity from a group of faces (known as ensemble coding). However, possible deficits in ensemble coding in a previous study (CPs n = 4) may have been masked because CPs relied on pictorial (image) cues rather than identity cues. Here we asked whether a larger sample of CPs (n = 11) would show intact ensemble coding of identity when availability of image cues was minimised. Participants viewed a "set" of four faces and then judged whether a subsequent individual test face, either an exemplar or a "set average", was in the preceding set. Ensemble coding occurred when matching (vs. mismatching) averages were mistakenly endorsed as set members. We assessed both image- and identity-based ensemble coding, by varying whether test faces were either the same or different images of the identities in the set. CPs showed significant ensemble coding in both tasks, indicating that their performance was independent of image cues. As a group, CPs' ensemble coding was weaker than controls in both tasks, consistent with evidence that perceptual processing of face identity is disrupted in CP. This effect was driven by CPs (n= 3) who, in addition to having impaired face memory, also performed particularly poorly on a measure of face perception (CFPT). Future research, using larger samples, should examine whether deficits in ensemble coding may be restricted to CPs who also have substantial face perception deficits. Copyright © 2018 Elsevier Ltd. All rights reserved.

Automatic Detection of Frontal Face Midline by Chain-coded Merlin-Farber Hough Trasform

NASA Astrophysics Data System (ADS)

Okamoto, Daichi; Ohyama, Wataru; Wakabayashi, Tetsushi; Kimura, Fumitaka

We propose a novel approach for detection of the facial midline (facial symmetry axis) from a frontal face image. The facial midline has several applications, for instance reducing computational cost required for facial feature extraction (FFE) and postoperative assessment for cosmetic or dental surgery. The proposed method detects the facial midline of a frontal face from an edge image as the symmetry axis using the Merlin-Faber Hough transformation. And a new performance improvement scheme for midline detection by MFHT is present. The main concept of the proposed scheme is suppression of redundant vote on the Hough parameter space by introducing chain code representation for the binary edge image. Experimental results on the image dataset containing 2409 images from FERET database indicate that the proposed algorithm can improve the accuracy of midline detection from 89.9% to 95.1 % for face images with different scales and rotation.

Responses of chimpanzees to cues of conspecific observation☆

PubMed Central

Nettle, Daniel; Cronin, Katherine A.; Bateson, Melissa

2013-01-01

Recent evidence has shown that humans are remarkably sensitive to artificial cues of conspecific observation when making decisions with potential social consequences. Whether similar effects are found in other great apes has not yet been investigated. We carried out two experiments in which individual chimpanzees, Pan troglodytes, took items of food from an array in the presence of either an image of a large conspecific face or a scrambled control image. In experiment 1 we compared three versions of the face image varying in size and the amount of the face displayed. In experiment 2 we compared a fourth variant of the image with more prominent coloured eyes displayed closer to the focal chimpanzee. The chimpanzees did not look at the face images significantly more than at the control images in either experiment. Although there were trends for some individuals in each experiment to be slower to take high-value food items in the face conditions, these were not consistent or robust. We suggest that the extreme human sensitivity to cues of potential conspecific observation may not be shared with chimpanzees. PMID:24027343

Identifiable Images of Bystanders Extracted from Corneal Reflections

PubMed Central

Jenkins, Rob; Kerr, Christie

2013-01-01

Criminal investigations often use photographic evidence to identify suspects. Here we combined robust face perception and high-resolution photography to mine face photographs for hidden information. By zooming in on high-resolution face photographs, we were able to recover images of unseen bystanders from reflections in the subjects' eyes. To establish whether these bystanders could be identified from the reflection images, we presented them as stimuli in a face matching task (Experiment 1). Accuracy in the face matching task was well above chance (50%), despite the unpromising source of the stimuli. Participants who were unfamiliar with the bystanders' faces (n = 16) performed at 71% accuracy [t(15) = 7.64, p<.0001, d = 1.91], and participants who were familiar with the faces (n = 16) performed at 84% accuracy [t(15) = 11.15, p<.0001, d = 2.79]. In a test of spontaneous recognition (Experiment 2), observers could reliably name a familiar face from an eye reflection image. For crimes in which the victims are photographed (e.g., hostage taking, child sex abuse), reflections in the eyes of the photographic subject could help to identify perpetrators. PMID:24386177

DeitY-TU face database: its design, multiple camera capturing, characteristics, and evaluation

NASA Astrophysics Data System (ADS)

Bhowmik, Mrinal Kanti; Saha, Kankan; Saha, Priya; Bhattacharjee, Debotosh

2014-10-01

The development of the latest face databases is providing researchers different and realistic problems that play an important role in the development of efficient algorithms for solving the difficulties during automatic recognition of human faces. This paper presents the creation of a new visual face database, named the Department of Electronics and Information Technology-Tripura University (DeitY-TU) face database. It contains face images of 524 persons belonging to different nontribes and Mongolian tribes of north-east India, with their anthropometric measurements for identification. Database images are captured within a room with controlled variations in illumination, expression, and pose along with variability in age, gender, accessories, make-up, and partial occlusion. Each image contains the combined primary challenges of face recognition, i.e., illumination, expression, and pose. This database also represents some new features: soft biometric traits such as mole, freckle, scar, etc., and facial anthropometric variations that may be helpful for researchers for biometric recognition. It also gives an equivalent study of the existing two-dimensional face image databases. The database has been tested using two baseline algorithms: linear discriminant analysis and principal component analysis, which may be used by other researchers as the control algorithm performance score.

Quantal and Nonquantal Transmission in Calyx-Bearing Fibers of the Turtle Posterior Crista

PubMed Central

Holt, Joseph C.; Chatlani, Shilpa; Lysakowski, Anna; Goldberg, Jay M.

2010-01-01

Intracellular recordings were made from nerve fibers in the posterior ampullary nerve near the neuroepithelium. Calyx-bearing afferents were identified by their distinctive efferent-mediated responses. Such fibers receive inputs from both type I and type II hair cells. Type II inputs are made by synapses on the outer face of the calyx ending and on the boutons of dimorphic fibers. Quantal activity, consisting of brief mEPSPs, is reduced by lowering the external concentration of Ca2+ and blocked by the AMPA-receptor antagonist CNQX. Poisson statistics govern the timing of mEPSPs, which occur at high rates (250–2,500/s) in the absence of mechanical stimulation. Excitation produced by canal-duct indentation can increase mEPSP rates to nearly 5,000/s. As the rate increases, mEPSPs can change from a monophasic depolarization to a biphasic depolarizing– hyperpolarizing sequence, both of whose components are blocked by CNQX. Blockers of voltage-gated currents affect mEPSP size, which is decreased by TTX and is increased by linopirdine. mEPSP size decreases several fold after impalement. The size decrease, although it may be triggered by the depolarization occurring during impalement, persists even at hyperpolarized membrane potentials. Nonquantal transmission is indicated by shot-noise calculations and by the presence of voltage modulations after quantal activity is abolished pharmacologically. An ultrastructural study shows that inner-face inputs from type I hair cells outnumber outer-face inputs from type II hair cells by an almost 6:1 ratio. PMID:17596419

Efficient, nonlinear phase estimation with the nonmodulated pyramid wavefront sensor.

PubMed

Frazin, Richard A

2018-04-01

The sensitivity of the pyramid wavefront sensor (PyWFS) has made it a popular choice for astronomical adaptive optics (AAO) systems. The PyWFS is at its most sensitive when it is used without modulation of the input beam. In nonmodulated mode, the device is highly nonlinear. Hence, all PyWFS implementations on current AAO systems employ modulation to make the device more linear. The upcoming era of 30-m class telescopes and the demand for ultra-precise wavefront control stemming from science objectives that include direct imaging of exoplanets make using the PyWFS without modulation desirable. This article argues that nonlinear estimation based on Newton's method for nonlinear optimization can be useful for mitigating the effects of nonlinearity in the nonmodulated PyWFS. The proposed approach requires all optical modeling to be pre-computed, which has the advantage of avoiding real-time simulations of beam propagation. Further, the required real-time calculations are amenable to massively parallel computation. Numerical experiments simulate a PyWFS with faces sloped 3.7° to the horizontal, operating at a wavelength of 0.85 μm, and with an index of refraction of 1.45. A singular value analysis shows that the common practice of calculating two "slope" images from the four PyWFS pupil images discards critical information and is unsuitable for the nonmodulated PyWFS simulated here. Instead, this article advocates estimators that use the raw pixel values not only from the four geometrical images of the pupil, but from surrounding pixels as well. The simulations indicate that nonlinear estimation can be effective when the Strehl ratio of the input beam is greater than 0.3, and the improvement relative to linear estimation tends to increase at larger Strehl ratios. At Strehl ratios less than about 0.5, the performances of both the nonlinear and linear estimators are relatively insensitive to noise since they are dominated by nonlinearity error.

Face recognition in the thermal infrared domain

NASA Astrophysics Data System (ADS)

Kowalski, M.; Grudzień, A.; Palka, N.; Szustakowski, M.

2017-10-01

Biometrics refers to unique human characteristics. Each unique characteristic may be used to label and describe individuals and for automatic recognition of a person based on physiological or behavioural properties. One of the most natural and the most popular biometric trait is a face. The most common research methods on face recognition are based on visible light. State-of-the-art face recognition systems operating in the visible light spectrum achieve very high level of recognition accuracy under controlled environmental conditions. Thermal infrared imagery seems to be a promising alternative or complement to visible range imaging due to its relatively high resistance to illumination changes. A thermal infrared image of the human face presents its unique heat-signature and can be used for recognition. The characteristics of thermal images maintain advantages over visible light images, and can be used to improve algorithms of human face recognition in several aspects. Mid-wavelength or far-wavelength infrared also referred to as thermal infrared seems to be promising alternatives. We present the study on 1:1 recognition in thermal infrared domain. The two approaches we are considering are stand-off face verification of non-moving person as well as stop-less face verification on-the-move. The paper presents methodology of our studies and challenges for face recognition systems in the thermal infrared domain.

Face detection in color images using skin color, Laplacian of Gaussian, and Euler number

NASA Astrophysics Data System (ADS)

Saligrama Sundara Raman, Shylaja; Kannanedhi Narasimha Sastry, Balasubramanya Murthy; Subramanyam, Natarajan; Senkutuvan, Ramya; Srikanth, Radhika; John, Nikita; Rao, Prateek

2010-02-01

In this a paper, a feature based approach to face detection has been proposed using an ensemble of algorithms. The method uses chrominance values and edge features to classify the image as skin and nonskin regions. The edge detector used for this purpose is Laplacian of Gaussian (LoG) which is found to be appropriate when images having multiple faces with noise in them. Eight connectivity analysis of these regions will segregate them as probable face or nonface. The procedure is made more robust by identifying local features within these skin regions which include number of holes, percentage of skin and the golden ratio. The method proposed has been tested on color face images of various races obtained from different sources and its performance is found to be encouraging as the color segmentation cleans up almost all the complex facial features. The result obtained has a calculated accuracy of 86.5% on a test set of 230 images.

Face pose tracking using the four-point algorithm

NASA Astrophysics Data System (ADS)

Fung, Ho Yin; Wong, Kin Hong; Yu, Ying Kin; Tsui, Kwan Pang; Kam, Ho Chuen

2017-06-01

In this paper, we have developed an algorithm to track the pose of a human face robustly and efficiently. Face pose estimation is very useful in many applications such as building virtual reality systems and creating an alternative input method for the disabled. Firstly, we have modified a face detection toolbox called DLib for the detection of a face in front of a camera. The detected face features are passed to a pose estimation method, known as the four-point algorithm, for pose computation. The theory applied and the technical problems encountered during system development are discussed in the paper. It is demonstrated that the system is able to track the pose of a face in real time using a consumer grade laptop computer.

Tunable pulsed narrow bandwidth light source

DOEpatents

Powers, Peter E.; Kulp, Thomas J.

2002-01-01

A tunable pulsed narrow bandwidth light source and a method of operating a light source are provided. The light source includes a pump laser, first and second non-linear optical crystals, a tunable filter, and light pulse directing optics. The method includes the steps of operating the pump laser to generate a pulsed pump beam characterized by a nanosecond pulse duration and arranging the light pulse directing optics so as to (i) split the pulsed pump beam into primary and secondary pump beams; (ii) direct the primary pump beam through an input face of the first non-linear optical crystal such that a primary output beam exits from an output face of the first non-linear optical crystal; (iii) direct the primary output beam through the tunable filter to generate a sculpted seed beam; and direct the sculpted seed beam and the secondary pump beam through an input face of the second non-linear optical crystal such that a secondary output beam characterized by at least one spectral bandwidth on the order of about 0.1 cm.sup.-1 and below exits from an output face of the second non-linear optical crystal.

The So-Called Face

NASA Image and Video Library

2002-05-21

The so-called Face on Mars can be seen slightly above center and to the right in this NASA Mars Odyssey image. This 3-km long knob was first imaged by NASA Viking spacecraft in the 1970 and to some resembled a face carved into the rocks of Mars.

Relevance of Whitnall's tubercle and auditory meatus in diagnosing exclusions during skull-photo superimposition.

PubMed

Jayaprakash, Paul T; Hashim, Natassha; Yusop, Ridzuan Abd Aziz Mohd

2015-08-01

Video vision mixer based skull-photo superimposition is a popular method for identifying skulls retrieved from unidentified human remains. A report on the reliability of the superimposition method suggested increased failure rates of 17.3 to 32% to exclude and 15 to 20% to include skulls while using related and unrelated face photographs. Such raise in failures prompted an analysis of the methods employed for the research. The protocols adopted for assessing the reliability are seen to vary from those suggested by the practitioners in the field. The former include overlaying the skull- and face-images on the basis of morphology by relying on anthropometric landmarks on the front plane of the face-images and evaluating the goodness of match depending on mix-mode images; the latter consist of orienting the skull considering landmarks on both the eye and ear planes of the face- and skull-images and evaluating the match utilizing images seen in wipe-mode in addition to those in mix-mode. Superimposition of a skull with face-images of five living individuals in two sets of experiments, one following the procedure described for the research on reliability and the other applying the methods suggested by the practitioners has shown that overlaying the images on the basis of morphology depending on the landmarks on the front plane alone and assessing the match in mix-mode fails to exclude the skull. However, orienting the skull relying on the relationship between the anatomical landmarks on the skull- and face-images such as Whitnall's tubercle and exocanthus in the front (eye) plane and the porion and tragus in the rear (ear) plane as well as assessing the match using wipe-mode images enables excluding that skull while superimposing with the same set of face-images. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The N170 component is sensitive to face-like stimuli: a study of Chinese Peking opera makeup.

PubMed

Liu, Tiantian; Mu, Shoukuan; He, Huamin; Zhang, Lingcong; Fan, Cong; Ren, Jie; Zhang, Mingming; He, Weiqi; Luo, Wenbo

2016-12-01

The N170 component is considered a neural marker of face-sensitive processing. In the present study, the face-sensitive N170 component of event-related potentials (ERPs) was investigated with a modified oddball paradigm using a natural face (the standard stimulus), human- and animal-like makeup stimuli, scrambled control images that mixed human- and animal-like makeup pieces, and a grey control image. Nineteen participants were instructed to respond within 1000 ms by pressing the ' F ' or ' J ' key in response to the standard or deviant stimuli, respectively. We simultaneously recorded ERPs, response accuracy, and reaction times. The behavioral results showed that the main effect of stimulus type was significant for reaction time, whereas there were no significant differences in response accuracies among stimulus types. In relation to the ERPs, N170 amplitudes elicited by human-like makeup stimuli, animal-like makeup stimuli, scrambled control images, and a grey control image progressively decreased. A right hemisphere advantage was observed in the N170 amplitudes for human-like makeup stimuli, animal-like makeup stimuli, and scrambled control images but not for grey control image. These results indicate that the N170 component is sensitive to face-like stimuli and reflect configural processing in face recognition.

Uncrossed cortico-muscular projections in humans are abundant to facial muscles of the upper and lower face, but may differ between sexes.

PubMed

Fischer, Urs; Hess, Christian W; Rösler, Kai M

2005-01-01

It is a popular concept in clinical neurology that muscles of the lower face receive predominantly crossed cortico-bulbar motor input, whereas muscles of the upper face receive additional ipsilateral, uncrossed input. To test this notion, we used focal transcranial magnetic brain stimulation to quantify crossed and uncrossed cortico-muscular projections to 6 different facial muscles (right and left Mm. frontalis, nasalis, and orbicularis oris) in 36 healthy right-handed volunteers (15 men, 21 women, mean age 25 years). Uncrossed input was present in 78% to 92% of the 6 examined muscles. The mean uncrossed: crossed response amplitude ratios were 0.74/0.65 in right/left frontalis, 0.73/0.59 in nasalis, and 0.54/0.71 in orbicularis oris; ANOVA p>0.05). Judged by the sizes of motor evoked potentials, the cortical representation of the 3 muscles was similar. The amount of uncrossed projections was different between men and women, since men had stronger left-to-left projections and women stronger right-to-right projections. We conclude that the amount of uncrossed pyramidal projections is not different for muscles of the upper from those of the lower face. The clinical observation that frontal muscles are often spared in central facial palsies must, therefore, be explained differently. Moreover, gender specific lateralization phenomena may not only be present for higher level behavioural functions, but may also affect simple systems on a lower level of motor hierarchy.

Disruption of visual awareness during the attentional blink is reflected by selective disruption of late-stage neural processing

PubMed Central

Harris, Joseph A.; McMahon, Alex R.; Woldorff, Marty G.

2015-01-01

Any information represented in the brain holds the potential to influence behavior. It is therefore of broad interest to determine the extent and quality of neural processing of stimulus input that occurs with and without awareness. The attentional blink is a useful tool for dissociating neural and behavioral measures of perceptual visual processing across conditions of awareness. The extent of higher-order visual information beyond basic sensory signaling that is processed during the attentional blink remains controversial. To determine what neural processing at the level of visual-object identification occurs in the absence of awareness, electrophysiological responses to images of faces and houses were recorded both within and outside of the attentional blink period during a rapid serial visual presentation (RSVP) stream. Electrophysiological results were sorted according to behavioral performance (correctly identified targets versus missed targets) within these blink and non-blink periods. An early index of face-specific processing (the N170, 140–220 ms post-stimulus) was observed regardless of whether the subject demonstrated awareness of the stimulus, whereas a later face-specific effect with the same topographic distribution (500–700 ms post-stimulus) was only seen for accurate behavioral discrimination of the stimulus content. The present findings suggest a multi-stage process of object-category processing, with only the later phase being associated with explicit visual awareness. PMID:23859644

Explaining neural signals in human visual cortex with an associative learning model.

PubMed

Jiang, Jiefeng; Schmajuk, Nestor; Egner, Tobias

2012-08-01

"Predictive coding" models posit a key role for associative learning in visual cognition, viewing perceptual inference as a process of matching (learned) top-down predictions (or expectations) against bottom-up sensory evidence. At the neural level, these models propose that each region along the visual processing hierarchy entails one set of processing units encoding predictions of bottom-up input, and another set computing mismatches (prediction error or surprise) between predictions and evidence. This contrasts with traditional views of visual neurons operating purely as bottom-up feature detectors. In support of the predictive coding hypothesis, a recent human neuroimaging study (Egner, Monti, & Summerfield, 2010) showed that neural population responses to expected and unexpected face and house stimuli in the "fusiform face area" (FFA) could be well-described as a summation of hypothetical face-expectation and -surprise signals, but not by feature detector responses. Here, we used computer simulations to test whether these imaging data could be formally explained within the broader framework of a mathematical neural network model of associative learning (Schmajuk, Gray, & Lam, 1996). Results show that FFA responses could be fit very closely by model variables coding for conditional predictions (and their violations) of stimuli that unconditionally activate the FFA. These data document that neural population signals in the ventral visual stream that deviate from classic feature detection responses can formally be explained by associative prediction and surprise signals.

Is the N170 for faces cognitively penetrable? Evidence from repetition priming of Mooney faces of familiar and unfamiliar persons.

PubMed

Jemel, Boutheina; Pisani, Michèle; Calabria, Marco; Crommelinck, Marc; Bruyer, Raymond

2003-07-01

Impoverished images of faces, two-tone Mooney faces, severely impair the ability to recognize to whom the face pertains. However, previously seeing the corresponding face in a clear format helps fame-judgments to Mooney faces. In the present experiment, we sought to demonstrate that enhancement in the perceptual encoding of Mooney faces results from top-down effects, due to previous activation of familiar face representation. Event-related potentials (ERPs) were obtained for target Mooney images of familiar and unfamiliar faces preceded by clear pictures portraying either the same photo (same photo prime), or a different photo of the same person (different photo prime) or a new unfamiliar face (no-prime). In agreement with previous findings the use of primes was effective in enhancing the recognition of familiar faces in Mooney images; this priming effect was larger in the same than in different photo priming condition. ERP data revealed that the amplitude of the N170 face-sensitive component was smaller when elicited by familiar than by unfamiliar face targets, and for familiar face targets primed by the same than by different photos (a graded priming effect). Because the priming effect was restricted to familiar faces and occurred at the peak of the N170, we suggest that the early perceptual stage of face processing is likely to be penetrable by the top-down effect due to the activation of face representations within the face recognition system.

Fingerprint imaging from the inside of a finger with full-field optical coherence tomography

PubMed Central

Auksorius, Egidijus; Boccara, A. Claude

2015-01-01

Imaging below fingertip surface might be a useful alternative to the traditional fingerprint sensing since the internal finger features are more reliable than the external ones. One of the most promising subsurface imaging technique is optical coherence tomography (OCT), which, however, has to acquire 3-D data even when a single en face image is required. This makes OCT inherently slow for en face imaging and produce unnecessary large data sets. Here we demonstrate that full-field optical coherence tomography (FF-OCT) can be used to produce en face images of sweat pores and internal fingerprints, which can be used for the identification purposes. PMID:26601009

Discrimination of human and dog faces and inversion responses in domestic dogs (Canis familiaris).

PubMed

Racca, Anaïs; Amadei, Eleonora; Ligout, Séverine; Guo, Kun; Meints, Kerstin; Mills, Daniel

2010-05-01

Although domestic dogs can respond to many facial cues displayed by other dogs and humans, it remains unclear whether they can differentiate individual dogs or humans based on facial cues alone and, if so, whether they would demonstrate the face inversion effect, a behavioural hallmark commonly used in primates to differentiate face processing from object processing. In this study, we first established the applicability of the visual paired comparison (VPC or preferential looking) procedure for dogs using a simple object discrimination task with 2D pictures. The animals demonstrated a clear looking preference for novel objects when simultaneously presented with prior-exposed familiar objects. We then adopted this VPC procedure to assess their face discrimination and inversion responses. Dogs showed a deviation from random behaviour, indicating discrimination capability when inspecting upright dog faces, human faces and object images; but the pattern of viewing preference was dependent upon image category. They directed longer viewing time at novel (vs. familiar) human faces and objects, but not at dog faces, instead, a longer viewing time at familiar (vs. novel) dog faces was observed. No significant looking preference was detected for inverted images regardless of image category. Our results indicate that domestic dogs can use facial cues alone to differentiate individual dogs and humans and that they exhibit a non-specific inversion response. In addition, the discrimination response by dogs of human and dog faces appears to differ with the type of face involved.

The roles of perceptual and conceptual information in face recognition.

PubMed

Schwartz, Linoy; Yovel, Galit

2016-11-01

The representation of familiar objects is comprised of perceptual information about their visual properties as well as the conceptual knowledge that we have about them. What is the relative contribution of perceptual and conceptual information to object recognition? Here, we examined this question by designing a face familiarization protocol during which participants were either exposed to rich perceptual information (viewing each face in different angles and illuminations) or with conceptual information (associating each face with a different name). Both conditions were compared with single-view faces presented with no labels. Recognition was tested on new images of the same identities to assess whether learning generated a view-invariant representation. Results showed better recognition of novel images of the learned identities following association of a face with a name label, but no enhancement following exposure to multiple face views. Whereas these findings may be consistent with the role of category learning in object recognition, face recognition was better for labeled faces only when faces were associated with person-related labels (name, occupation), but not with person-unrelated labels (object names or symbols). These findings suggest that association of meaningful conceptual information with an image shifts its representation from an image-based percept to a view-invariant concept. They further indicate that the role of conceptual information should be considered to account for the superior recognition that we have for familiar faces and objects. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Effects of threshold on single-target detection by using modified amplitude-modulated joint transform correlator

NASA Astrophysics Data System (ADS)

Kaewkasi, Pitchaya; Widjaja, Joewono; Uozumi, Jun

2007-03-01

Effects of threshold value on detection performance of the modified amplitude-modulated joint transform correlator are quantitatively studied using computer simulation. Fingerprint and human face images are used as test scenes in the presence of noise and a contrast difference. Simulation results demonstrate that this correlator improves detection performance for both types of image used, but moreso for human face images. Optimal detection of low-contrast human face images obscured by strong noise can be obtained by selecting an appropriate threshold value.

Comparison of the Diagnostic Accuracy of DSC- and Dynamic Contrast-Enhanced MRI in the Preoperative Grading of Astrocytomas.

PubMed

Nguyen, T B; Cron, G O; Perdrizet, K; Bezzina, K; Torres, C H; Chakraborty, S; Woulfe, J; Jansen, G H; Sinclair, J; Thornhill, R E; Foottit, C; Zanette, B; Cameron, I G

2015-11-01

Dynamic contrast-enhanced MR imaging parameters can be biased by poor measurement of the vascular input function. We have compared the diagnostic accuracy of dynamic contrast-enhanced MR imaging by using a phase-derived vascular input function and "bookend" T1 measurements with DSC MR imaging for preoperative grading of astrocytomas. This prospective study included 48 patients with a new pathologic diagnosis of an astrocytoma. Preoperative MR imaging was performed at 3T, which included 2 injections of 5-mL gadobutrol for dynamic contrast-enhanced and DSC MR imaging. During dynamic contrast-enhanced MR imaging, both magnitude and phase images were acquired to estimate plasma volume obtained from phase-derived vascular input function (Vp_Φ) and volume transfer constant obtained from phase-derived vascular input function (K(trans)_Φ) as well as plasma volume obtained from magnitude-derived vascular input function (Vp_SI) and volume transfer constant obtained from magnitude-derived vascular input function (K(trans)_SI). From DSC MR imaging, corrected relative CBV was computed. Four ROIs were placed over the solid part of the tumor, and the highest value among the ROIs was recorded. A Mann-Whitney U test was used to test for difference between grades. Diagnostic accuracy was assessed by using receiver operating characteristic analysis. Vp_ Φ and K(trans)_Φ values were lower for grade II compared with grade III astrocytomas (P < .05). Vp_SI and K(trans)_SI were not significantly different between grade II and grade III astrocytomas (P = .08-0.15). Relative CBV and dynamic contrast-enhanced MR imaging parameters except for K(trans)_SI were lower for grade III compared with grade IV (P ≤ .05). In differentiating low- and high-grade astrocytomas, we found no statistically significant difference in diagnostic accuracy between relative CBV and dynamic contrast-enhanced MR imaging parameters. In the preoperative grading of astrocytomas, the diagnostic accuracy of dynamic contrast-enhanced MR imaging parameters is similar to that of relative CBV. © 2015 by American Journal of Neuroradiology.

Transfer learning for bimodal biometrics recognition

NASA Astrophysics Data System (ADS)

Dan, Zhiping; Sun, Shuifa; Chen, Yanfei; Gan, Haitao

2013-10-01

Biometrics recognition aims to identify and predict new personal identities based on their existing knowledge. As the use of multiple biometric traits of the individual may enables more information to be used for recognition, it has been proved that multi-biometrics can produce higher accuracy than single biometrics. However, a common problem with traditional machine learning is that the training and test data should be in the same feature space, and have the same underlying distribution. If the distributions and features are different between training and future data, the model performance often drops. In this paper, we propose a transfer learning method for face recognition on bimodal biometrics. The training and test samples of bimodal biometric images are composed of the visible light face images and the infrared face images. Our algorithm transfers the knowledge across feature spaces, relaxing the assumption of same feature space as well as same underlying distribution by automatically learning a mapping between two different but somewhat similar face images. According to the experiments in the face images, the results show that the accuracy of face recognition has been greatly improved by the proposed method compared with the other previous methods. It demonstrates the effectiveness and robustness of our method.

3D FaceCam: a fast and accurate 3D facial imaging device for biometrics applications

NASA Astrophysics Data System (ADS)

Geng, Jason; Zhuang, Ping; May, Patrick; Yi, Steven; Tunnell, David

2004-08-01

Human faces are fundamentally three-dimensional (3D) objects, and each face has its unique 3D geometric profile. The 3D geometric features of a human face can be used, together with its 2D texture, for rapid and accurate face recognition purposes. Due to the lack of low-cost and robust 3D sensors and effective 3D facial recognition (FR) algorithms, almost all existing FR systems use 2D face images. Genex has developed 3D solutions that overcome the inherent problems in 2D while also addressing limitations in other 3D alternatives. One important aspect of our solution is a unique 3D camera (the 3D FaceCam) that combines multiple imaging sensors within a single compact device to provide instantaneous, ear-to-ear coverage of a human face. This 3D camera uses three high-resolution CCD sensors and a color encoded pattern projection system. The RGB color information from each pixel is used to compute the range data and generate an accurate 3D surface map. The imaging system uses no moving parts and combines multiple 3D views to provide detailed and complete 3D coverage of the entire face. Images are captured within a fraction of a second and full-frame 3D data is produced within a few seconds. This described method provides much better data coverage and accuracy in feature areas with sharp features or details (such as the nose and eyes). Using this 3D data, we have been able to demonstrate that a 3D approach can significantly improve the performance of facial recognition. We have conducted tests in which we have varied the lighting conditions and angle of image acquisition in the "field." These tests have shown that the matching results are significantly improved when enrolling a 3D image rather than a single 2D image. With its 3D solutions, Genex is working toward unlocking the promise of powerful 3D FR and transferring FR from a lab technology into a real-world biometric solution.

Deep learning and face recognition: the state of the art

NASA Astrophysics Data System (ADS)

Balaban, Stephen

2015-05-01

Deep Neural Networks (DNNs) have established themselves as a dominant technique in machine learning. DNNs have been top performers on a wide variety of tasks including image classification, speech recognition, and face recognition.1-3 Convolutional neural networks (CNNs) have been used in nearly all of the top performing methods on the Labeled Faces in the Wild (LFW) dataset.3-6 In this talk and accompanying paper, I attempt to provide a review and summary of the deep learning techniques used in the state-of-the-art. In addition, I highlight the need for both larger and more challenging public datasets to benchmark these systems. Despite the ability of DNNs and autoencoders to perform unsupervised feature learning, modern facial recognition pipelines still require domain specific engineering in the form of re-alignment. For example, in Facebook's recent DeepFace paper, a 3D "frontalization" step lies at the beginning of the pipeline. This step creates a 3D face model for the incoming image and then uses a series of affine transformations of the fiducial points to "frontalize" the image. This step enables the DeepFace system to use a neural network architecture with locally connected layers without weight sharing as opposed to standard convolutional layers.6 Deep learning techniques combined with large datasets have allowed research groups to surpass human level performance on the LFW dataset.3, 5 The high accuracy (99.63% for FaceNet at the time of publishing) and utilization of outside data (hundreds of millions of images in the case of Google's FaceNet) suggest that current face verification benchmarks such as LFW may not be challenging enough, nor provide enough data, for current techniques.3, 5 There exist a variety of organizations with mobile photo sharing applications that would be capable of releasing a very large scale and highly diverse dataset of facial images captured on mobile devices. Such an "ImageNet for Face Recognition" would likely receive a warm welcome from researchers and practitioners alike.

45 CFR 164.514 - Other requirements relating to uses and disclosures of protected health information.

Code of Federal Regulations, 2013 CFR

2013-10-01

... numbers; (J) Account numbers; (K) Certificate/license numbers; (L) Vehicle identifiers and serial numbers... and voice prints; (Q) Full face photographic images and any comparable images; and (R) Any other..., including finger and voice prints; and (xvi) Full face photographic images and any comparable images. (3...

45 CFR 164.514 - Other requirements relating to uses and disclosures of protected health information.

Code of Federal Regulations, 2012 CFR

2012-10-01

... numbers; (J) Account numbers; (K) Certificate/license numbers; (L) Vehicle identifiers and serial numbers... and voice prints; (Q) Full face photographic images and any comparable images; and (R) Any other..., including finger and voice prints; and (xvi) Full face photographic images and any comparable images. (3...

45 CFR 164.514 - Other requirements relating to uses and disclosures of protected health information.

Code of Federal Regulations, 2014 CFR

2014-10-01

... numbers; (J) Account numbers; (K) Certificate/license numbers; (L) Vehicle identifiers and serial numbers... and voice prints; (Q) Full face photographic images and any comparable images; and (R) Any other..., including finger and voice prints; and (xvi) Full face photographic images and any comparable images. (3...

45 CFR 164.514 - Other requirements relating to uses and disclosures of protected health information.

Code of Federal Regulations, 2010 CFR

2010-10-01

... numbers; (J) Account numbers; (K) Certificate/license numbers; (L) Vehicle identifiers and serial numbers... and voice prints; (Q) Full face photographic images and any comparable images; and (R) Any other..., including finger and voice prints; and (xvi) Full face photographic images and any comparable images. (3...

45 CFR 164.514 - Other requirements relating to uses and disclosures of protected health information.

Code of Federal Regulations, 2011 CFR

2011-10-01

... numbers; (J) Account numbers; (K) Certificate/license numbers; (L) Vehicle identifiers and serial numbers... and voice prints; (Q) Full face photographic images and any comparable images; and (R) Any other..., including finger and voice prints; and (xvi) Full face photographic images and any comparable images. (3...

Nonlinear analysis and synthesis of video images using deep dynamic bottleneck neural networks for face recognition.

PubMed

Moghadam, Saeed Montazeri; Seyyedsalehi, Seyyed Ali

2018-05-31

Nonlinear components extracted from deep structures of bottleneck neural networks exhibit a great ability to express input space in a low-dimensional manifold. Sharing and combining the components boost the capability of the neural networks to synthesize and interpolate new and imaginary data. This synthesis is possibly a simple model of imaginations in human brain where the components are expressed in a nonlinear low dimensional manifold. The current paper introduces a novel Dynamic Deep Bottleneck Neural Network to analyze and extract three main features of videos regarding the expression of emotions on the face. These main features are identity, emotion and expression intensity that are laid in three different sub-manifolds of one nonlinear general manifold. The proposed model enjoying the advantages of recurrent networks was used to analyze the sequence and dynamics of information in videos. It is noteworthy to mention that this model also has also the potential to synthesize new videos showing variations of one specific emotion on the face of unknown subjects. Experiments on discrimination and recognition ability of extracted components showed that the proposed model has an average of 97.77% accuracy in recognition of six prominent emotions (Fear, Surprise, Sadness, Anger, Disgust, and Happiness), and 78.17% accuracy in the recognition of intensity. The produced videos revealed variations from neutral to the apex of an emotion on the face of the unfamiliar test subject which is on average 0.8 similar to reference videos in the scale of the SSIM method. Copyright © 2018 Elsevier Ltd. All rights reserved.

Object knowledge changes visual appearance: semantic effects on color afterimages.

PubMed

Lupyan, Gary

2015-10-01

According to predictive coding models of perception, what we see is determined jointly by the current input and the priors established by previous experience, expectations, and other contextual factors. The same input can thus be perceived differently depending on the priors that are brought to bear during viewing. Here, I show that expected (diagnostic) colors are perceived more vividly than arbitrary or unexpected colors, particularly when color input is unreliable. Participants were tested on a version of the 'Spanish Castle Illusion' in which viewing a hue-inverted image renders a subsequently shown achromatic version of the image in vivid color. Adapting to objects with intrinsic colors (e.g., a pumpkin) led to stronger afterimages than adapting to arbitrarily colored objects (e.g., a pumpkin-colored car). Considerably stronger afterimages were also produced by scenes containing intrinsically colored elements (grass, sky) compared to scenes with arbitrarily colored objects (books). The differences between images with diagnostic and arbitrary colors disappeared when the association between the image and color priors was weakened by, e.g., presenting the image upside-down, consistent with the prediction that color appearance is being modulated by color knowledge. Visual inputs that conflict with prior knowledge appear to be phenomenologically discounted, but this discounting is moderated by input certainty, as shown by the final study which uses conventional images rather than afterimages. As input certainty is increased, unexpected colors can become easier to detect than expected ones, a result consistent with predictive-coding models. Copyright © 2015 Elsevier B.V. All rights reserved.

Prototype Focal-Plane-Array Optoelectronic Image Processor

NASA Technical Reports Server (NTRS)

Fang, Wai-Chi; Shaw, Timothy; Yu, Jeffrey

1995-01-01

Prototype very-large-scale integrated (VLSI) planar array of optoelectronic processing elements combines speed of optical input and output with flexibility of reconfiguration (programmability) of electronic processing medium. Basic concept of processor described in "Optical-Input, Optical-Output Morphological Processor" (NPO-18174). Performs binary operations on binary (black and white) images. Each processing element corresponds to one picture element of image and located at that picture element. Includes input-plane photodetector in form of parasitic phototransistor part of processing circuit. Output of each processing circuit used to modulate one picture element in output-plane liquid-crystal display device. Intended to implement morphological processing algorithms that transform image into set of features suitable for high-level processing; e.g., recognition.

Planar microlens with front-face angle: design, fabrication, and characterization

NASA Astrophysics Data System (ADS)

Al Hafiz, Md. Abdullah; Michael, Aron; Kwok, Chee-Yee

2016-07-01

This paper studies the effect of microlens front-face angle on the performance of an optical system consisting of a planar-graded refractive index (GRIN) lens pair facing each other separated by a free-space region. The planar silica microlens pairs are designed to facilitate low-loss optical signal propagation in the free-space region between the opposing optical waveguides. The planar lens is fabricated from a 38-μm-thick fluorine-doped silica layer on a silicon substrate. It has a parabolic refractive index profile in the vertical direction, which is achieved by controlled fluorine incorporation in the silica film to collimate the optical beam in the vertical direction. Horizontal beam collimation is achieved by incorporating a horizontal curvature at the front face of the lens defined by deep oxide etch. A generalized 3×3 ABCDGH transformation matrix method has been derived to compute the coupling efficiency of such microlens pairs to take front-face angles that may be present due to fabrication variations or limitations and possible input/output optical fiber offset/tilt into considerations. Pairs of such planar GRIN lens with various free-space propagation distances between them ranging from 75 to 2500 μm and with front-face angles of 1.5 deg, 2 deg, and 4 deg have been fabricated and characterized. Beam propagation method simulations have been carried out to substantiate the theoretical and experimental results. The results indicate that the optical loss is reasonably low up to 1.5 deg of front-face angles and increases significantly with further increase in the front-face angle. Analysis shows that for a given system with specific microlens front-face angle, the optical loss can be significantly reduced by properly compensating the vertical position of the input and output fibers.

Flat or curved thin optical display panel

DOEpatents

Veligdan, J.T.

1995-01-10

An optical panel includes a plurality of waveguides stacked together, with each waveguide having a first end and an opposite second end. The first ends collectively define a first face, and the second ends collectively define a second face of the panel. The second face is disposed at an acute face angle relative to the waveguides to provide a panel which is relatively thin compared to the height of the second face. In an exemplary embodiment for use in a projection TV, the first face is substantially smaller in height than the second face and receives a TV image, with the second face defining a screen for viewing the image enlarged. 7 figures.

Experimental image alignment system

NASA Technical Reports Server (NTRS)

Moyer, A. L.; Kowel, S. T.; Kornreich, P. G.

1980-01-01

A microcomputer-based instrument for image alignment with respect to a reference image is described which uses the DEFT sensor (Direct Electronic Fourier Transform) for image sensing and preprocessing. The instrument alignment algorithm which uses the two-dimensional Fourier transform as input is also described. It generates signals used to steer the stage carrying the test image into the correct orientation. This algorithm has computational advantages over algorithms which use image intensity data as input and is suitable for a microcomputer-based instrument since the two-dimensional Fourier transform is provided by the DEFT sensor.

Single-image super-resolution based on Markov random field and contourlet transform

NASA Astrophysics Data System (ADS)

Wu, Wei; Liu, Zheng; Gueaieb, Wail; He, Xiaohai

2011-04-01

Learning-based methods are well adopted in image super-resolution. In this paper, we propose a new learning-based approach using contourlet transform and Markov random field. The proposed algorithm employs contourlet transform rather than the conventional wavelet to represent image features and takes into account the correlation between adjacent pixels or image patches through the Markov random field (MRF) model. The input low-resolution (LR) image is decomposed with the contourlet transform and fed to the MRF model together with the contourlet transform coefficients from the low- and high-resolution image pairs in the training set. The unknown high-frequency components/coefficients for the input low-resolution image are inferred by a belief propagation algorithm. Finally, the inverse contourlet transform converts the LR input and the inferred high-frequency coefficients into the super-resolved image. The effectiveness of the proposed method is demonstrated with the experiments on facial, vehicle plate, and real scene images. A better visual quality is achieved in terms of peak signal to noise ratio and the image structural similarity measurement.

Non-rigid, but not rigid, motion interferes with the processing of structural face information in developmental prosopagnosia.

PubMed

Maguinness, Corrina; Newell, Fiona N

2015-04-01

There is growing evidence to suggest that facial motion is an important cue for face recognition. However, it is poorly understood whether motion is integrated with facial form information or whether it provides an independent cue to identity. To provide further insight into this issue, we compared the effect of motion on face perception in two developmental prosopagnosics and age-matched controls. Participants first learned faces presented dynamically (video), or in a sequence of static images, in which rigid (viewpoint) or non-rigid (expression) changes occurred. Immediately following learning, participants were required to match a static face image to the learned face. Test face images varied by viewpoint (Experiment 1) or expression (Experiment 2) and were learned or novel face images. We found similar performance across prosopagnosics and controls in matching facial identity across changes in viewpoint when the learned face was shown moving in a rigid manner. However, non-rigid motion interfered with face matching across changes in expression in both individuals with prosopagnosia compared to the performance of control participants. In contrast, non-rigid motion did not differentially affect the matching of facial expressions across changes in identity for either prosopagnosics (Experiment 3). Our results suggest that whilst the processing of rigid motion information of a face may be preserved in developmental prosopagnosia, non-rigid motion can specifically interfere with the representation of structural face information. Taken together, these results suggest that both form and motion cues are important in face perception and that these cues are likely integrated in the representation of facial identity. Copyright © 2015 Elsevier Ltd. All rights reserved.

A novel deep learning algorithm for incomplete face recognition: Low-rank-recovery network.

PubMed

Zhao, Jianwei; Lv, Yongbiao; Zhou, Zhenghua; Cao, Feilong

2017-10-01

There have been a lot of methods to address the recognition of complete face images. However, in real applications, the images to be recognized are usually incomplete, and it is more difficult to realize such a recognition. In this paper, a novel convolution neural network frame, named a low-rank-recovery network (LRRNet), is proposed to conquer the difficulty effectively inspired by matrix completion and deep learning techniques. The proposed LRRNet first recovers the incomplete face images via an approach of matrix completion with the truncated nuclear norm regularization solution, and then extracts some low-rank parts of the recovered images as the filters. With these filters, some important features are obtained by means of the binaryzation and histogram algorithms. Finally, these features are classified with the classical support vector machines (SVMs). The proposed LRRNet method has high face recognition rate for the heavily corrupted images, especially for the images in the large databases. The proposed LRRNet performs well and efficiently for the images with heavily corrupted, especially in the case of large databases. Extensive experiments on several benchmark databases demonstrate that the proposed LRRNet performs better than some other excellent robust face recognition methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Visual face-movement sensitive cortex is relevant for auditory-only speech recognition.

PubMed

Riedel, Philipp; Ragert, Patrick; Schelinski, Stefanie; Kiebel, Stefan J; von Kriegstein, Katharina

2015-07-01

It is commonly assumed that the recruitment of visual areas during audition is not relevant for performing auditory tasks ('auditory-only view'). According to an alternative view, however, the recruitment of visual cortices is thought to optimize auditory-only task performance ('auditory-visual view'). This alternative view is based on functional magnetic resonance imaging (fMRI) studies. These studies have shown, for example, that even if there is only auditory input available, face-movement sensitive areas within the posterior superior temporal sulcus (pSTS) are involved in understanding what is said (auditory-only speech recognition). This is particularly the case when speakers are known audio-visually, that is, after brief voice-face learning. Here we tested whether the left pSTS involvement is causally related to performance in auditory-only speech recognition when speakers are known by face. To test this hypothesis, we applied cathodal transcranial direct current stimulation (tDCS) to the pSTS during (i) visual-only speech recognition of a speaker known only visually to participants and (ii) auditory-only speech recognition of speakers they learned by voice and face. We defined the cathode as active electrode to down-regulate cortical excitability by hyperpolarization of neurons. tDCS to the pSTS interfered with visual-only speech recognition performance compared to a control group without pSTS stimulation (tDCS to BA6/44 or sham). Critically, compared to controls, pSTS stimulation additionally decreased auditory-only speech recognition performance selectively for voice-face learned speakers. These results are important in two ways. First, they provide direct evidence that the pSTS is causally involved in visual-only speech recognition; this confirms a long-standing prediction of current face-processing models. Secondly, they show that visual face-sensitive pSTS is causally involved in optimizing auditory-only speech recognition. These results are in line with the 'auditory-visual view' of auditory speech perception, which assumes that auditory speech recognition is optimized by using predictions from previously encoded speaker-specific audio-visual internal models. Copyright © 2015 Elsevier Ltd. All rights reserved.

Learning toward practical head pose estimation

NASA Astrophysics Data System (ADS)

Sang, Gaoli; He, Feixiang; Zhu, Rong; Xuan, Shibin

2017-08-01

Head pose is useful information for many face-related tasks, such as face recognition, behavior analysis, human-computer interfaces, etc. Existing head pose estimation methods usually assume that the face images have been well aligned or that sufficient and precise training data are available. In practical applications, however, these assumptions are very likely to be invalid. This paper first investigates the impact of the failure of these assumptions, i.e., misalignment of face images, uncertainty and undersampling of training data, on head pose estimation accuracy of state-of-the-art methods. A learning-based approach is then designed to enhance the robustness of head pose estimation to these factors. To cope with misalignment, instead of using hand-crafted features, it seeks suitable features by learning from a set of training data with a deep convolutional neural network (DCNN), such that the training data can be best classified into the correct head pose categories. To handle uncertainty and undersampling, it employs multivariate labeling distributions (MLDs) with dense sampling intervals to represent the head pose attributes of face images. The correlation between the features and the dense MLD representations of face images is approximated by a maximum entropy model, whose parameters are optimized on the given training data. To estimate the head pose of a face image, its MLD representation is first computed according to the model based on the features extracted from the image by the trained DCNN, and its head pose is then assumed to be the one corresponding to the peak in its MLD. Evaluation experiments on the Pointing'04, FacePix, Multi-PIE, and CASIA-PEAL databases prove the effectiveness and efficiency of the proposed method.

Children with Autism Spectrum Disorder (ASD) Attend Typically to Faces and Objects Presented within Their Picture Communication Systems

ERIC Educational Resources Information Center

Gillespie-Smith, K.; Riby, D. M.; Hancock, P. J. B.; Doherty-Sneddon, G.

2014-01-01

Background: Children with autism spectrum disorder (ASD) may require interventions for communication difficulties. One type of intervention is picture communication symbols which are proposed to improve comprehension of linguistic input for children with ASD. However, atypical attention to faces and objects is widely reported across the autism…

Securing Trust, Roles and Communication in E-Advising--Theoretical Inputs

ERIC Educational Resources Information Center

Ranglund, Ole Jørgen S.; Danielsen, Anette; Kiønig, Linda; Vold, Tone

2017-01-01

Students claim to learn a lot from advising and feedback on assignments. This is one of the results in a survey amongst students at The Inland Norway University of Applied Sciences. Traditionally, advising is mainly a face-to-face activity. However, with an increasing number of courses offered online, it is timely to discuss how to conduct…

Relationship between fatigue of generation II image intensifier and input illumination

NASA Astrophysics Data System (ADS)

Chen, Qingyou

1995-09-01

If there is fatigue for an image intesifier, then it has an effect on the imaging property of the night vision system. In this paper, using the principle of Joule Heat, we derive a mathematical formula for the generated heat of semiconductor photocathode. We describe the relationship among the various parameters in the formula. We also discuss reasons for the fatigue of Generation II image intensifier caused by bigger input illumination.

Improved automatic adjustment of density and contrast in FCR system using neural network

NASA Astrophysics Data System (ADS)

Takeo, Hideya; Nakajima, Nobuyoshi; Ishida, Masamitsu; Kato, Hisatoyo

1994-05-01

FCR system has an automatic adjustment of image density and contrast by analyzing the histogram of image data in the radiation field. Advanced image recognition methods proposed in this paper can improve the automatic adjustment performance, in which neural network technology is used. There are two methods. Both methods are basically used 3-layer neural network with back propagation. The image data are directly input to the input-layer in one method and the histogram data is input in the other method. The former is effective to the imaging menu such as shoulder joint in which the position of interest region occupied on the histogram changes by difference of positioning and the latter is effective to the imaging menu such as chest-pediatrics in which the histogram shape changes by difference of positioning. We experimentally confirm the validity of these methods (about the automatic adjustment performance) as compared with the conventional histogram analysis methods.

Pareidolia in infants.

PubMed

Kato, Masaharu; Mugitani, Ryoko

2015-01-01

Faces convey primal information for our social life. This information is so primal that we sometimes find faces in non-face objects. Such illusory perception is called pareidolia. In this study, using infants' orientation behavior toward a sound source, we demonstrated that infants also perceive pareidolic faces. An image formed by four blobs and an outline was shown to infants with or without pure tones, and the time they spent looking at each blob was compared. Since the mouth is the unique sound source in a face and the literature has shown that infants older than 6 months already have sound-mouth association, increased looking time towards the bottom blob (pareidolic mouth area) during sound presentation indicated that they illusorily perceive a face in the image. Infants aged 10 and 12 months looked longer at the bottom blob under the upright-image condition, whereas no differences in looking time were observed for any blob under the inverted-image condition. However, 8-month-olds did not show any difference in looking time under both the upright and inverted conditions, suggesting that the perception of pareidolic faces, through sound association, comes to develop at around 8 to 10 months after birth.

Pareidolia in Infants

PubMed Central

Kato, Masaharu; Mugitani, Ryoko

2015-01-01

Faces convey primal information for our social life. This information is so primal that we sometimes find faces in non-face objects. Such illusory perception is called pareidolia. In this study, using infants’ orientation behavior toward a sound source, we demonstrated that infants also perceive pareidolic faces. An image formed by four blobs and an outline was shown to infants with or without pure tones, and the time they spent looking at each blob was compared. Since the mouth is the unique sound source in a face and the literature has shown that infants older than 6 months already have sound-mouth association, increased looking time towards the bottom blob (pareidolic mouth area) during sound presentation indicated that they illusorily perceive a face in the image. Infants aged 10 and 12 months looked longer at the bottom blob under the upright-image condition, whereas no differences in looking time were observed for any blob under the inverted-image condition. However, 8-month-olds did not show any difference in looking time under both the upright and inverted conditions, suggesting that the perception of pareidolic faces, through sound association, comes to develop at around 8 to 10 months after birth. PMID:25689630

Decoding representations of face identity that are tolerant to rotation.

PubMed

Anzellotti, Stefano; Fairhall, Scott L; Caramazza, Alfonso

2014-08-01

In order to recognize the identity of a face we need to distinguish very similar images (specificity) while also generalizing identity information across image transformations such as changes in orientation (tolerance). Recent studies investigated the representation of individual faces in the brain, but it remains unclear whether the human brain regions that were found encode representations of individual images (specificity) or face identity (specificity plus tolerance). In the present article, we use multivoxel pattern analysis in the human ventral stream to investigate the representation of face identity across rotations in depth, a kind of transformation in which no point in the face image remains unchanged. The results reveal representations of face identity that are tolerant to rotations in depth in occipitotemporal cortex and in anterior temporal cortex, even when the similarity between mirror symmetrical views cannot be used to achieve tolerance. Converging evidence from different analysis techniques shows that the right anterior temporal lobe encodes a comparable amount of identity information to occipitotemporal regions, but this information is encoded over a smaller extent of cortex. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Sex-typicality and attractiveness: are supermale and superfemale faces super-attractive?

PubMed

Rhodes, G; Hickford, C; Jeffery, L

2000-02-01

Many animals find extreme versions of secondary sexual characteristics attractive, and such preferences can enhance reproductive success (Andersson, 1994). We hypothesized, therefore, that extreme versions of sex-typical traits may be attractive in human faces. We created supermale and superfemale faces by exaggerating all spatial differences between an average male and an average female face. In Expt 1 the male average was preferred to a supermale (50% exaggeration of differences from the female average). There was no clear preference for the female average or the superfemale (50% exaggeration). In Expt 2, participants chose the most attractive face from sets of images containing feminized as well as masculinized images for each sex, and spanning a wider range of exaggeration levels than in Expt 1. Chinese sets were also shown, to see whether similar preferences would occur for a less familiar race (participants were Caucasian). The most attractive female image was significantly feminized for faces of both races. However, the most attractive male image for both races was also significantly feminized. These results indicate that feminization, rather than sex exaggeration per se, is attractive in human faces, and they corroborate similar findings by Perrett et al. (1998).

Identity-level representations affect unfamiliar face matching performance in sequential but not simultaneous tasks.

PubMed

Menon, Nadia; White, David; Kemp, Richard I

2015-01-01

According to cognitive and neurological models of the face-processing system, faces are represented at two levels of abstraction. First, image-based pictorial representations code a particular instance of a face and include information that is unrelated to identity-such as lighting, pose, and expression. Second, at a more abstract level, identity-specific representations combine information from various encounters with a single face. Here we tested whether identity-level representations mediate unfamiliar face matching performance. Across three experiments we manipulated identity attributions to pairs of target images and measured the effect on subsequent identification decisions. Participants were instructed that target images were either two photos of the same person (1ID condition) or photos of two different people (2ID condition). This manipulation consistently affected performance in sequential matching: 1ID instructions improved accuracy on "match" trials and caused participants to adopt a more liberal response bias than the 2ID condition. However, this manipulation did not affect performance in simultaneous matching. We conclude that identity-level representations, generated in working memory, influence the amount of variation tolerated between images, when making identity judgements in sequential face matching.

Affective attitudes to face images associated with intracerebral EEG source location before face viewing.

PubMed

Pizzagalli, D; Koenig, T; Regard, M; Lehmann, D

1999-01-01

We investigated whether different, personality-related affective attitudes are associated with different brain electric field (EEG) sources before any emotional challenge (stimulus exposure). A 27-channel EEG was recorded in 15 subjects during eyes-closed resting. After recording, subjects rated 32 images of human faces for affective appeal. The subjects in the first (i.e., most negative) and fourth (i.e., most positive) quartile of general affective attitude were further analyzed. The EEG data (mean=25+/-4. 8 s/subject) were subjected to frequency-domain model dipole source analysis (FFT-Dipole-Approximation), resulting in 3-dimensional intracerebral source locations and strengths for the delta-theta, alpha, and beta EEG frequency band, and for the full range (1.5-30 Hz) band. Subjects with negative attitude (compared to those with positive attitude) showed the following source locations: more inferior for all frequency bands, more anterior for the delta-theta band, more posterior and more right for the alpha, beta and 1.5-30 Hz bands. One year later, the subjects were asked to rate the face images again. The rating scores for the same face images were highly correlated for all subjects, and original and retest affective mean attitude was highly correlated across subjects. The present results show that subjects with different affective attitudes to face images had different active, cerebral, neural populations in a task-free condition prior to viewing the images. We conclude that the brain functional state which implements affective attitude towards face images as a personality feature exists without elicitors, as a continuously present, dynamic feature of brain functioning. Copyright 1999 Elsevier Science B.V.

Face adaptation improves gender discrimination.

PubMed

Yang, Hua; Shen, Jianhong; Chen, Juan; Fang, Fang

2011-01-01

Adaptation to a visual pattern can alter the sensitivities of neuronal populations encoding the pattern. However, the functional roles of adaptation, especially in high-level vision, are still equivocal. In the present study, we performed three experiments to investigate if face gender adaptation could affect gender discrimination. Experiments 1 and 2 revealed that adapting to a male/female face could selectively enhance discrimination for male/female faces. Experiment 3 showed that the discrimination enhancement induced by face adaptation could transfer across a substantial change in three-dimensional face viewpoint. These results provide further evidence suggesting that, similar to low-level vision, adaptation in high-level vision could calibrate the visual system to current inputs of complex shapes (i.e. face) and improve discrimination at the adapted characteristic. Copyright © 2010 Elsevier Ltd. All rights reserved.

Generating virtual training samples for sparse representation of face images and face recognition

NASA Astrophysics Data System (ADS)

Du, Yong; Wang, Yu

2016-03-01

There are many challenges in face recognition. In real-world scenes, images of the same face vary with changing illuminations, different expressions and poses, multiform ornaments, or even altered mental status. Limited available training samples cannot convey these possible changes in the training phase sufficiently, and this has become one of the restrictions to improve the face recognition accuracy. In this article, we view the multiplication of two images of the face as a virtual face image to expand the training set and devise a representation-based method to perform face recognition. The generated virtual samples really reflect some possible appearance and pose variations of the face. By multiplying a training sample with another sample from the same subject, we can strengthen the facial contour feature and greatly suppress the noise. Thus, more human essential information is retained. Also, uncertainty of the training data is simultaneously reduced with the increase of the training samples, which is beneficial for the training phase. The devised representation-based classifier uses both the original and new generated samples to perform the classification. In the classification phase, we first determine K nearest training samples for the current test sample by calculating the Euclidean distances between the test sample and training samples. Then, a linear combination of these selected training samples is used to represent the test sample, and the representation result is used to classify the test sample. The experimental results show that the proposed method outperforms some state-of-the-art face recognition methods.

Effects of spatial frequency and location of fearful faces on human amygdala activity.

PubMed

Morawetz, Carmen; Baudewig, Juergen; Treue, Stefan; Dechent, Peter

2011-01-31

Facial emotion perception plays a fundamental role in interpersonal social interactions. Images of faces contain visual information at various spatial frequencies. The amygdala has previously been reported to be preferentially responsive to low-spatial frequency (LSF) rather than to high-spatial frequency (HSF) filtered images of faces presented at the center of the visual field. Furthermore, it has been proposed that the amygdala might be especially sensitive to affective stimuli in the periphery. In the present study we investigated the impact of spatial frequency and stimulus eccentricity on face processing in the human amygdala and fusiform gyrus using functional magnetic resonance imaging (fMRI). The spatial frequencies of pictures of fearful faces were filtered to produce images that retained only LSF or HSF information. Facial images were presented either in the left or right visual field at two different eccentricities. In contrast to previous findings, we found that the amygdala responds to LSF and HSF stimuli in a similar manner regardless of the location of the affective stimuli in the visual field. Furthermore, the fusiform gyrus did not show differential responses to spatial frequency filtered images of faces. Our findings argue against the view that LSF information plays a crucial role in the processing of facial expressions in the amygdala and of a higher sensitivity to affective stimuli in the periphery. Copyright © 2010 Elsevier B.V. All rights reserved.

Face perception is tuned to horizontal orientation in the N170 time window.

PubMed

Jacques, Corentin; Schiltz, Christine; Goffaux, Valerie

2014-02-07

The specificity of face perception is thought to reside both in its dramatic vulnerability to picture-plane inversion and its strong reliance on horizontally oriented image content. Here we asked when in the visual processing stream face-specific perception is tuned to horizontal information. We measured the behavioral performance and scalp event-related potentials (ERP) when participants viewed upright and inverted images of faces and cars (and natural scenes) that were phase-randomized in a narrow orientation band centered either on vertical or horizontal orientation. For faces, the magnitude of the inversion effect (IE) on behavioral discrimination performance was significantly reduced for horizontally randomized compared to vertically or nonrandomized images, confirming the importance of horizontal information for the recruitment of face-specific processing. Inversion affected the processing of nonrandomized and vertically randomized faces early, in the N170 time window. In contrast, the magnitude of the N170 IE was much smaller for horizontally randomized faces. The present research indicates that the early face-specific neural representations are preferentially tuned to horizontal information and offers new perspectives for a description of the visual information feeding face-specific perception.

The nature of face representations in subcortical regions.

PubMed

Gabay, Shai; Burlingham, Charles; Behrmann, Marlene

2014-07-01

Studies examining the neural correlates of face perception in humans have focused almost exclusively on the distributed cortical network of face-selective regions. Recently, however, investigations have also identified subcortical correlates of face perception and the question addressed here concerns the nature of these subcortical face representations. To explore this issue, we presented to participants pairs of images sequentially to the same or to different eyes. Superior performance in the former over latter condition implicates monocular, prestriate portions of the visual system. Over a series of five experiments, we manipulated both lower-level (size, location) as well as higher-level (identity) similarity across the pair of faces. A monocular advantage was observed even when the faces in a pair differed in location and in size, implicating some subcortical invariance across lower-level image properties. A monocular advantage was also observed when the faces in a pair were two different images of the same individual, indicating the engagement of subcortical representations in more abstract, higher-level aspects of face processing. We conclude that subcortical structures of the visual system are involved, perhaps interactively, in multiple aspects of face perception, and not simply in deriving initial coarse representations. Copyright © 2014 Elsevier Ltd. All rights reserved.

Psychophysical study of face identity discrimination in schizophrenia: association with facial morphology.

PubMed

Ekstrom, Tor; Maher, Stephen; Chen, Yue

2016-11-01

Identifying individual identities from faces is crucial for social functioning. In schizophrenia, previous studies showed mixed results as to whether face identity discrimination is compromised. How a social category factor (such as gender and race) affects schizophrenia patients' facial identity discrimination is unclear. Using psychophysics, we examined perceptual performance on within- and between- category face identity discrimination tasks in patients (n = 51) and controls (n = 31). Face images from each of six pairs of individuals (two White females, two White males, two Black males, two Asian females, one Black male and one White male, and one White female and one White male) were morphed to create additional images along a continuum of dissimilarity in facial morphology. Patients underperformed for five out of the six face pairs (the Black/White male pair was the exception). Perceptual performance was correlated with morphological changes in face images being discriminated, to a greater extent in patients than in controls. Face identity discrimination in schizophrenia was most impaired for those faces that presumably have extensive social exposures (such as White males). Patients' perceptual performance appears to depend more on physical feature changes of faces.

Automatic Detection of Clouds and Shadows Using High Resolution Satellite Image Time Series

NASA Astrophysics Data System (ADS)

Champion, Nicolas

2016-06-01

Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel) with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel) with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8 and Pléiades-HR images and our first experiments show the feasibility to automate the detection of shadows and clouds in satellite image sequences.

A familiarity disadvantage for remembering specific images of faces.

PubMed

Armann, Regine G M; Jenkins, Rob; Burton, A Mike

2016-04-01

Familiar faces are remembered better than unfamiliar faces. Furthermore, it is much easier to match images of familiar than unfamiliar faces. These findings could be accounted for by quantitative differences in the ease with which faces are encoded. However, it has been argued that there are also some qualitative differences in familiar and unfamiliar face processing. Unfamiliar faces are held to rely on superficial, pictorial representations, whereas familiar faces invoke more abstract representations. Here we present 2 studies that show, for 1 task, an advantage for unfamiliar faces. In recognition memory, viewers are better able to reject a new picture, if it depicts an unfamiliar face. This rare advantage for unfamiliar faces supports the notion that familiarity brings about some representational changes, and further emphasizes the idea that theoretical accounts of face processing should incorporate familiarity. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Modelling the perceptual similarity of facial expressions from image statistics and neural responses.

PubMed

Sormaz, Mladen; Watson, David M; Smith, William A P; Young, Andrew W; Andrews, Timothy J

2016-04-01

The ability to perceive facial expressions of emotion is essential for effective social communication. We investigated how the perception of facial expression emerges from the image properties that convey this important social signal, and how neural responses in face-selective brain regions might track these properties. To do this, we measured the perceptual similarity between expressions of basic emotions, and investigated how this is reflected in image measures and in the neural response of different face-selective regions. We show that the perceptual similarity of different facial expressions (fear, anger, disgust, sadness, happiness) can be predicted by both surface and feature shape information in the image. Using block design fMRI, we found that the perceptual similarity of expressions could also be predicted from the patterns of neural response in the face-selective posterior superior temporal sulcus (STS), but not in the fusiform face area (FFA). These results show that the perception of facial expression is dependent on the shape and surface properties of the image and on the activity of specific face-selective regions. Copyright © 2016 Elsevier Inc. All rights reserved.

Face recognition via sparse representation of SIFT feature on hexagonal-sampling image

NASA Astrophysics Data System (ADS)

Zhang, Daming; Zhang, Xueyong; Li, Lu; Liu, Huayong

2018-04-01

This paper investigates a face recognition approach based on Scale Invariant Feature Transform (SIFT) feature and sparse representation. The approach takes advantage of SIFT which is local feature other than holistic feature in classical Sparse Representation based Classification (SRC) algorithm and possesses strong robustness to expression, pose and illumination variations. Since hexagonal image has more inherit merits than square image to make recognition process more efficient, we extract SIFT keypoint in hexagonal-sampling image. Instead of matching SIFT feature, firstly the sparse representation of each SIFT keypoint is given according the constructed dictionary; secondly these sparse vectors are quantized according dictionary; finally each face image is represented by a histogram and these so-called Bag-of-Words vectors are classified by SVM. Due to use of local feature, the proposed method achieves better result even when the number of training sample is small. In the experiments, the proposed method gave higher face recognition rather than other methods in ORL and Yale B face databases; also, the effectiveness of the hexagonal-sampling in the proposed method is verified.

Optical performance effects of the misalignment of nonimaging optics solar collectors

NASA Astrophysics Data System (ADS)

Ferry, Jonathan; Ricketts, Melissa; Winston, Roland

2017-09-01

The use of non-imaging optics in the application of high temperature solar thermal collectors can be extremely advantageous in eliminating the need to track the sun. The stationary nature of non-imaging optics collectors, commonly called compound parabolic concentrators (CPC's), present a unique design challenge when orienting them to collect sunlight. Many facilities throughout the world that adopt CPCs are not situated to orient the collectors in the ideal angle facing the sun. This East-West misalignment can adversely affect the optical and power performance of the CPC collector. To characterize how this misalignment effects CPCs, reverse raytracing simulations are conducted for varying offset angles of the collectors from solar South. Optical performance is analyzed for an ideal East-West oriented CPC with a 40-degree acceptance angle. Direction cosine plots are used to develop a ratio of annual solar collection by the CPC over the total annual solar input. From these simulations, average annual collector performance is given for offset angles ranging from 0 to 90 degrees for different Earth Latitudes in 10 degree increments.

Thermal Imaging of the Periorbital Regions during the Presentation of an Auditory Startle Stimulus

PubMed Central

Gane, Luke; Power, Sarah; Kushki, Azadeh; Chau, Tom

2011-01-01

Infrared thermal imaging of the inner canthi of the periorbital regions of the face can potentially serve as an input signal modality for an alternative access system for individuals with conditions that preclude speech or voluntary movement, such as total locked-in syndrome. However, it is unknown if the temperature of these regions is affected by the human startle response, as changes in the facial temperature of the periorbital regions manifested during the startle response could generate false positives in a thermography-based access system. This study presents an examination of the temperature characteristics of the periorbital regions of 11 able-bodied adult participants before and after a 102 dB auditory startle stimulus. The results indicate that the startle response has no substantial effect on the mean temperature of the periorbital regions. This indicates that thermography-based access solutions would be insensitive to startle reactions in their user, an important advantage over other modalities being considered in the context of access solutions for individuals with a severe motor disability. PMID:22073302

Redesigning photo-ID to improve unfamiliar face matching performance.

PubMed

White, David; Burton, A Mike; Jenkins, Rob; Kemp, Richard I

2014-06-01

Viewers find it difficult to match photos of unfamiliar faces for identity. Despite this, the use of photographic ID is widespread. In this study we ask whether it is possible to improve face matching performance by replacing single photographs on ID documents with multiple photos or an average image of the bearer. In 3 experiments we compare photo-to-photo matching with photo-to-average matching (where the average is formed from multiple photos of the same person) and photo-to-array matching (where the array comprises separate photos of the same person). We consistently find an accuracy advantage for average images and photo arrays over single photos, and show that this improvement is driven by performance in match trials. In the final experiment, we find a benefit of 4-image arrays relative to average images for unfamiliar faces, but not for familiar faces. We propose that conventional photo-ID format can be improved, and discuss this finding in the context of face recognition more generally. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Socially Important Faces Are Processed Preferentially to Other Familiar and Unfamiliar Faces in a Priming Task across a Range of Viewpoints

PubMed Central

Keyes, Helen; Zalicks, Catherine

2016-01-01

Using a priming paradigm, we investigate whether socially important faces are processed preferentially compared to other familiar and unfamiliar faces, and whether any such effects are affected by changes in viewpoint. Participants were primed with frontal images of personally familiar, famous or unfamiliar faces, and responded to target images of congruent or incongruent identity, presented in frontal, three quarter or profile views. We report that participants responded significantly faster to socially important faces (a friend’s face) compared to other highly familiar (famous) faces or unfamiliar faces. Crucially, responses to famous and unfamiliar faces did not differ. This suggests that, when presented in the context of a socially important stimulus, socially unimportant familiar faces (famous faces) are treated in a similar manner to unfamiliar faces. This effect was not tied to viewpoint, and priming did not affect socially important face processing differently to other faces. PMID:27219101

Satellite Image Mosaic Engine

NASA Technical Reports Server (NTRS)

Plesea, Lucian

2006-01-01

A computer program automatically builds large, full-resolution mosaics of multispectral images of Earth landmasses from images acquired by Landsat 7, complete with matching of colors and blending between adjacent scenes. While the code has been used extensively for Landsat, it could also be used for other data sources. A single mosaic of as many as 8,000 scenes, represented by more than 5 terabytes of data and the largest set produced in this work, demonstrated what the code could do to provide global coverage. The program first statistically analyzes input images to determine areas of coverage and data-value distributions. It then transforms the input images from their original universal transverse Mercator coordinates to other geographical coordinates, with scaling. It applies a first-order polynomial brightness correction to each band in each scene. It uses a data-mask image for selecting data and blending of input scenes. Under control by a user, the program can be made to operate on small parts of the output image space, with check-point and restart capabilities. The program runs on SGI IRIX computers. It is capable of parallel processing using shared-memory code, large memories, and tens of central processing units. It can retrieve input data and store output data at locations remote from the processors on which it is executed.

Correlation peak analysis applied to a sequence of images using two different filters for eye tracking model

NASA Astrophysics Data System (ADS)

Patrón, Verónica A.; Álvarez Borrego, Josué; Coronel Beltrán, Ángel

2015-09-01

Eye tracking has many useful applications that range from biometrics to face recognition and human-computer interaction. The analysis of the characteristics of the eyes has become one of the methods to accomplish the location of the eyes and the tracking of the point of gaze. Characteristics such as the contrast between the iris and the sclera, the shape, and distribution of colors and dark/light zones in the area are the starting point for these analyses. In this work, the focus will be on the contrast between the iris and the sclera, performing a correlation in the frequency domain. The images are acquired with an ordinary camera, which with were taken images of thirty-one volunteers. The reference image is an image of the subjects looking to a point in front of them at 0° angle. Then sequences of images are taken with the subject looking at different angles. These images are processed in MATLAB, obtaining the maximum correlation peak for each image, using two different filters. Each filter were analyzed and then one was selected, which is the filter that gives the best performance in terms of the utility of the data, which is displayed in graphs that shows the decay of the correlation peak as the eye moves progressively at different angle. This data will be used to obtain a mathematical model or function that establishes a relationship between the angle of vision (AOV) and the maximum correlation peak (MCP). This model will be tested using different input images from other subject not contained in the initial database, being able to predict angle of vision using the maximum correlation peak data.

Differences in neural responses to ipsilateral stimuli in wide-view fields between face- and house-selective areas

PubMed Central

Li, Ting; Niu, Yan; Xiang, Jie; Cheng, Junjie; Liu, Bo; Zhang, Hui; Yan, Tianyi; Kanazawa, Susumu; Wu, Jinglong

2018-01-01

Category-selective brain areas exhibit varying levels of neural activity to ipsilaterally presented stimuli. However, in face- and house-selective areas, the neural responses evoked by ipsilateral stimuli in the peripheral visual field remain unclear. In this study, we displayed face and house images using a wide-view visual presentation system while performing functional magnetic resonance imaging (fMRI). The face-selective areas (fusiform face area (FFA) and occipital face area (OFA)) exhibited intense neural responses to ipsilaterally presented images, whereas the house-selective areas (parahippocampal place area (PPA) and transverse occipital sulcus (TOS)) exhibited substantially smaller and even negative neural responses to the ipsilaterally presented images. We also found that the category preferences of the contralateral and ipsilateral neural responses were similar. Interestingly, the face- and house-selective areas exhibited neural responses to ipsilateral images that were smaller than the responses to the contralateral images. Multi-voxel pattern analysis (MVPA) was implemented to evaluate the difference between the contralateral and ipsilateral responses. The classification accuracies were much greater than those expected by chance. The classification accuracies in the FFA were smaller than those in the PPA and TOS. The closer eccentricities elicited greater classification accuracies in the PPA and TOS. We propose that these ipsilateral neural responses might be interpreted by interhemispheric communication through intrahemispheric connectivity of white matter connection and interhemispheric connectivity via the corpus callosum and occipital white matter connection. Furthermore, the PPA and TOS likely have weaker interhemispheric communication than the FFA and OFA, particularly in the peripheral visual field. PMID:29451872

En-face optical coherence tomography in the diagnosis and management of age-related macular degeneration and polypoidal choroidal vasculopathy.

PubMed

Lau, Tiffany; Wong, Ian Y; Iu, Lawrence; Chhablani, Jay; Yong, Tao; Hideki, Koizumi; Lee, Jacky; Wong, Raymond

2015-05-01

Optical coherence tomography (OCT) is a noninvasive imaging modality providing high-resolution images of the central retina that has completely transformed the field of ophthalmology. While traditional OCT has produced longitudinal cross-sectional images, advancements in data processing have led to the development of en-face OCT, which produces transverse images of retinal and choroidal layers at any specified depth. This offers additional benefit on top of longitudinal cross-sections because it provides an extensive overview of pathological structures in a single image. The aim of this review was to discuss the utility of en-face OCT in the diagnosis and management of age-related macular degeneration (AMD) and polypoidal choroidal vasculopathy (PCV). En-face imaging of the inner segment/outer segment junction of retinal photoreceptors has been shown to be a useful indicator of visual acuity and a predictor of the extent of progression of geographic atrophy. En-face OCT has also enabled high-resolution analysis and quantification of pathological structures such as reticular pseudodrusen (RPD) and choroidal neovascularization, which have the potential to become useful markers for disease monitoring. En-face Doppler OCT enables subtle changes in the choroidal vasculature to be detected in eyes with RPD and AMD, which has significantly advanced our understanding of their pathogenesis. En-face Doppler OCT has also been shown to be useful for detecting the polypoid lesions and branching vascular networks diagnostic of PCV. It may therefore serve as a noninvasive alternative to fluorescein and indocyanine green angiography for the diagnosis of PCV and other forms of the exudative macular disease.

Technical Management in an Age of Openness: The Political, Public, and Environmental Forest Ranger

ERIC Educational Resources Information Center

Anderson, Sarah E.; Hodges, Heather E.; Anderson, Terry L.

2013-01-01

Modern bureaucracy faces trade-offs between public and congressional input and agency expertise. The U.S. Forest Service offers an opportunity to quantitatively analyze whether an agency that is required to be more open to the public and congressional input will be forced to ignore its technical expertise in managing resources. This study uses…

Development of an Autonomous Face Recognition Machine.

DTIC Science & Technology

1986-12-08

This approach, like Baron’s, would be a very time consuming task. The problem of locating a face in Bromley’s work was the least complex of the three...top level design and the development and design decisions that were made in developing the Autonomous Face Recognition Machine (AFRM). The chapter is...images within a digital image. The second sectio examines the algorithm used in performing face recognition. The decision to divide the development

Local gradient Gabor pattern (LGGP) with applications in face recognition, cross-spectral matching, and soft biometrics

NASA Astrophysics Data System (ADS)

Chen, Cunjian; Ross, Arun

2013-05-01

Researchers in face recognition have been using Gabor filters for image representation due to their robustness to complex variations in expression and illumination. Numerous methods have been proposed to model the output of filter responses by employing either local or global descriptors. In this work, we propose a novel but simple approach for encoding Gradient information on Gabor-transformed images to represent the face, which can be used for identity, gender and ethnicity assessment. Extensive experiments on the standard face benchmark FERET (Visible versus Visible), as well as the heterogeneous face dataset HFB (Near-infrared versus Visible), suggest that the matching performance due to the proposed descriptor is comparable against state-of-the-art descriptor-based approaches in face recognition applications. Furthermore, the same feature set is used in the framework of a Collaborative Representation Classification (CRC) scheme for deducing soft biometric traits such as gender and ethnicity from face images in the AR, Morph and CAS-PEAL databases.

Probabilistic Elastic Part Model: A Pose-Invariant Representation for Real-World Face Verification.

PubMed

Li, Haoxiang; Hua, Gang

2018-04-01

Pose variation remains to be a major challenge for real-world face recognition. We approach this problem through a probabilistic elastic part model. We extract local descriptors (e.g., LBP or SIFT) from densely sampled multi-scale image patches. By augmenting each descriptor with its location, a Gaussian mixture model (GMM) is trained to capture the spatial-appearance distribution of the face parts of all face images in the training corpus, namely the probabilistic elastic part (PEP) model. Each mixture component of the GMM is confined to be a spherical Gaussian to balance the influence of the appearance and the location terms, which naturally defines a part. Given one or multiple face images of the same subject, the PEP-model builds its PEP representation by sequentially concatenating descriptors identified by each Gaussian component in a maximum likelihood sense. We further propose a joint Bayesian adaptation algorithm to adapt the universally trained GMM to better model the pose variations between the target pair of faces/face tracks, which consistently improves face verification accuracy. Our experiments show that we achieve state-of-the-art face verification accuracy with the proposed representations on the Labeled Face in the Wild (LFW) dataset, the YouTube video face database, and the CMU MultiPIE dataset.

Global Binary Continuity for Color Face Detection With Complex Background

NASA Astrophysics Data System (ADS)

Belavadi, Bhaskar; Mahendra Prashanth, K. V.; Joshi, Sujay S.; Suprathik, N.

2017-08-01

In this paper, we propose a method to detect human faces in color images, with complex background. The proposed algorithm makes use of basically two color space models, specifically HSV and YCgCr. The color segmented image is filled uniformly with a single color (binary) and then all unwanted discontinuous lines are removed to get the final image. Experimental results on Caltech database manifests that the purported model is able to accomplish far better segmentation for faces of varying orientations, skin color and background environment.

A comparison of ordinary fuzzy and intuitionistic fuzzy approaches in visualizing the image of flat electroencephalography

NASA Astrophysics Data System (ADS)

Zenian, Suzelawati; Ahmad, Tahir; Idris, Amidora

2017-09-01

Medical imaging is a subfield in image processing that deals with medical images. It is very crucial in visualizing the body parts in non-invasive way by using appropriate image processing techniques. Generally, image processing is used to enhance visual appearance of images for further interpretation. However, the pixel values of an image may not be precise as uncertainty arises within the gray values of an image due to several factors. In this paper, the input and output images of Flat Electroencephalography (fEEG) of an epileptic patient at varied time are presented. Furthermore, ordinary fuzzy and intuitionistic fuzzy approaches are implemented to the input images and the results are compared between these two approaches.

Face aging effect simulation model based on multilayer representation and shearlet transform

NASA Astrophysics Data System (ADS)

Li, Yuancheng; Li, Yan

2017-09-01

In order to extract detailed facial features, we build a face aging effect simulation model based on multilayer representation and shearlet transform. The face is divided into three layers: the global layer of the face, the local features layer, and texture layer, which separately establishes the aging model. First, the training samples are classified according to different age groups, and we use active appearance model (AAM) at the global level to obtain facial features. The regression equations of shape and texture with age are obtained by fitting the support vector machine regression, which is based on the radial basis function. We use AAM to simulate the aging of facial organs. Then, for the texture detail layer, we acquire the significant high-frequency characteristic components of the face by using the multiscale shearlet transform. Finally, we get the last simulated aging images of the human face by the fusion algorithm. Experiments are carried out on the FG-NET dataset, and the experimental results show that the simulated face images have less differences from the original image and have a good face aging simulation effect.

Stable face representations

PubMed Central

Jenkins, Rob; Burton, A. Mike

2011-01-01

Photographs are often used to establish the identity of an individual or to verify that they are who they claim to be. Yet, recent research shows that it is surprisingly difficult to match a photo to a face. Neither humans nor machines can perform this task reliably. Although human perceivers are good at matching familiar faces, performance with unfamiliar faces is strikingly poor. The situation is no better for automatic face recognition systems. In practical settings, automatic systems have been consistently disappointing. In this review, we suggest that failure to distinguish between familiar and unfamiliar face processing has led to unrealistic expectations about face identification in applied settings. We also argue that a photograph is not necessarily a reliable indicator of facial appearance, and develop our proposal that summary statistics can provide more stable face representations. In particular, we show that image averaging stabilizes facial appearance by diluting aspects of the image that vary between snapshots of the same person. We review evidence that the resulting images can outperform photographs in both behavioural experiments and computer simulations, and outline promising directions for future research. PMID:21536553

Relative expertise affects N170 during selective attention to superimposed face-character images.

PubMed

Ip, Chengteng; Wang, Hailing; Fu, Shimin

2017-07-01

It remains unclear whether the N170 of ERPs reflects domain-specific or domain-general visual object processing. In this study, we used superimposed images of a face and a Chinese character such that participants' relative expertise for the two object types was either similar (Experiment 1 and 2) or different (Experiment 3). Experiment 1 showed that N170 amplitude was larger when participants attended to the character instead of the face of a face-character combination. This result was unchanged in Experiment 2, in which task difficulty was selectively increased for the face component of the combined stimuli. Experiment 3 showed that, although this N170 enhancement for attending to characters relative to faces persisted for false characters with recognizable parts, it disappeared for unrecognizable characters. Therefore, N170 amplitude was significantly greater for Chinese characters than for faces presented within a combined image, independent of the relative task difficulty. This result strongly calls N170 face selectivity into question, demonstrating that, contrary to the expectations established by a domain-specific account, N170 is modulated by expertise. © 2017 Society for Psychophysiological Research.

Forming impressions: effects of facial expression and gender stereotypes.

PubMed

Hack, Tay

2014-04-01

The present study of 138 participants explored how facial expressions and gender stereotypes influence impressions. It was predicted that images of smiling women would be evaluated more favorably on traits reflecting warmth, and that images of non-smiling men would be evaluated more favorably on traits reflecting competence. As predicted, smiling female faces were rated as more warm; however, contrary to prediction, perceived competence of male faces was not affected by facial expression. Participants' female stereotype endorsement was a significant predictor for evaluations of female faces; those who ascribed more strongly to traditional female stereotypes reported the most positive impressions of female faces displaying a smiling expression. However, a similar effect was not found for images of men; endorsement of traditional male stereotypes did not predict participants' impressions of male faces.

Photoreceptor counting and montaging of en-face retinal images from an adaptive optics fundus camera

PubMed Central

Xue, Bai; Choi, Stacey S.; Doble, Nathan; Werner, John S.

2008-01-01

A fast and efficient method for quantifying photoreceptor density in images obtained with an en-face flood-illuminated adaptive optics (AO) imaging system is described. To improve accuracy of cone counting, en-face images are analyzed over extended areas. This is achieved with two separate semiautomated algorithms: (1) a montaging algorithm that joins retinal images with overlapping common features without edge effects and (2) a cone density measurement algorithm that counts the individual cones in the montaged image. The accuracy of the cone density measurement algorithm is high, with >97% agreement for a simulated retinal image (of known density, with low contrast) and for AO images from normal eyes when compared with previously reported histological data. Our algorithms do not require spatial regularity in cone packing and are, therefore, useful for counting cones in diseased retinas, as demonstrated for eyes with Stargardt’s macular dystrophy and retinitis pigmentosa. PMID:17429482

Kernel-aligned multi-view canonical correlation analysis for image recognition

NASA Astrophysics Data System (ADS)

Su, Shuzhi; Ge, Hongwei; Yuan, Yun-Hao

2016-09-01

Existing kernel-based correlation analysis methods mainly adopt a single kernel in each view. However, only a single kernel is usually insufficient to characterize nonlinear distribution information of a view. To solve the problem, we transform each original feature vector into a 2-dimensional feature matrix by means of kernel alignment, and then propose a novel kernel-aligned multi-view canonical correlation analysis (KAMCCA) method on the basis of the feature matrices. Our proposed method can simultaneously employ multiple kernels to better capture the nonlinear distribution information of each view, so that correlation features learned by KAMCCA can have well discriminating power in real-world image recognition. Extensive experiments are designed on five real-world image datasets, including NIR face images, thermal face images, visible face images, handwritten digit images, and object images. Promising experimental results on the datasets have manifested the effectiveness of our proposed method.

Photoreceptor counting and montaging of en-face retinal images from an adaptive optics fundus camera

NASA Astrophysics Data System (ADS)

Xue, Bai; Choi, Stacey S.; Doble, Nathan; Werner, John S.

2007-05-01

A fast and efficient method for quantifying photoreceptor density in images obtained with an en-face flood-illuminated adaptive optics (AO) imaging system is described. To improve accuracy of cone counting, en-face images are analyzed over extended areas. This is achieved with two separate semiautomated algorithms: (1) a montaging algorithm that joins retinal images with overlapping common features without edge effects and (2) a cone density measurement algorithm that counts the individual cones in the montaged image. The accuracy of the cone density measurement algorithm is high, with >97% agreement for a simulated retinal image (of known density, with low contrast) and for AO images from normal eyes when compared with previously reported histological data. Our algorithms do not require spatial regularity in cone packing and are, therefore, useful for counting cones in diseased retinas, as demonstrated for eyes with Stargardt's macular dystrophy and retinitis pigmentosa.

Procedure for Tooth Contact Analysis of a Face Gear Meshing With a Spur Gear Using Finite Element Analysis

NASA Technical Reports Server (NTRS)

Bibel, George; Lewicki, David G. (Technical Monitor)

2002-01-01

A procedure was developed to perform tooth contact analysis between a face gear meshing with a spur pinion using finite element analysis. The face gear surface points from a previous analysis were used to create a connected tooth solid model without gaps or overlaps. The face gear surface points were used to create a five tooth face gear Patran model (with rim) using Patran PCL commands. These commands were saved in a series of session files suitable for Patran input. A four tooth spur gear that meshes with the face gear was designed and constructed with Patran PCL commands. These commands were also saved in a session files suitable for Patran input. The orientation of the spur gear required for meshing with the face gear was determined. The required rotations and translations are described and built into the session file for the spur gear. The Abaqus commands for three-dimensional meshing were determined and verified for a simplified model containing one spur tooth and one face gear tooth. The boundary conditions, loads, and weak spring constraints were determined to make the simplified model work. The load steps and load increments to establish contact and obtain a realistic load was determined for the simplified two tooth model. Contact patterns give some insight into required mesh density. Building the two gears in two different local coordinate systems and rotating the local coordinate systems was verified as an easy way to roll the gearset through mesh. Due to limitation of swap space, disk space and time constraints of the summer period, the larger model was not completed.

Crossmodal adaptation in right posterior superior temporal sulcus during face-voice emotional integration.

PubMed

Watson, Rebecca; Latinus, Marianne; Noguchi, Takao; Garrod, Oliver; Crabbe, Frances; Belin, Pascal

2014-05-14

The integration of emotional information from the face and voice of other persons is known to be mediated by a number of "multisensory" cerebral regions, such as the right posterior superior temporal sulcus (pSTS). However, whether multimodal integration in these regions is attributable to interleaved populations of unisensory neurons responding to face or voice or rather by multimodal neurons receiving input from the two modalities is not fully clear. Here, we examine this question using functional magnetic resonance adaptation and dynamic audiovisual stimuli in which emotional information was manipulated parametrically and independently in the face and voice via morphing between angry and happy expressions. Healthy human adult subjects were scanned while performing a happy/angry emotion categorization task on a series of such stimuli included in a fast event-related, continuous carryover design. Subjects integrated both face and voice information when categorizing emotion-although there was a greater weighting of face information-and showed behavioral adaptation effects both within and across modality. Adaptation also occurred at the neural level: in addition to modality-specific adaptation in visual and auditory cortices, we observed for the first time a crossmodal adaptation effect. Specifically, fMRI signal in the right pSTS was reduced in response to a stimulus in which facial emotion was similar to the vocal emotion of the preceding stimulus. These results suggest that the integration of emotional information from face and voice in the pSTS involves a detectable proportion of bimodal neurons that combine inputs from visual and auditory cortices. Copyright © 2014 the authors 0270-6474/14/346813-09$15.00/0.

Input Scanners: A Growing Impact In A Diverse Marketplace

NASA Astrophysics Data System (ADS)

Marks, Kevin E.

1989-08-01

Just as newly invented photographic processes revolutionized the printing industry at the turn of the century, electronic imaging has affected almost every computer application today. To completely emulate traditionally mechanical means of information handling, computer based systems must be able to capture graphic images. Thus, there is a widespread need for the electronic camera, the digitizer, the input scanner. This paper will review how various types of input scanners are being used in many diverse applications. The following topics will be covered: - Historical overview of input scanners - New applications for scanners - Impact of scanning technology on select markets - Scanning systems issues

Scheme of Optical Image Encryption with Digital Information Input and Dynamic Encryption Key based on Two LC SLMs

NASA Astrophysics Data System (ADS)

Bondareva, A. P.; Cheremkhin, P. A.; Evtikhiev, N. N.; Krasnov, V. V.; Starikov, S. N.

Scheme of optical image encryption with digital information input and dynamic encryption key based on two liquid crystal spatial light modulators and operating with spatially-incoherent monochromatic illumination is experimentally implemented. Results of experiments on images optical encryption and numerical decryption are presented. Satisfactory decryption error of 0.20÷0.27 is achieved.

Reconstruction of an input function from a dynamic PET water image using multiple tissue curves

NASA Astrophysics Data System (ADS)

Kudomi, Nobuyuki; Maeda, Yukito; Yamamoto, Yuka; Nishiyama, Yoshihiro

2016-08-01

Quantification of cerebral blood flow (CBF) is important for the understanding of normal and pathologic brain physiology. When CBF is assessed using PET with {{\\text{H}}2} 15O or C15O2, its calculation requires an arterial input function, which generally requires invasive arterial blood sampling. The aim of the present study was to develop a new technique to reconstruct an image derived input function (IDIF) from a dynamic {{\\text{H}}2} 15O PET image as a completely non-invasive approach. Our technique consisted of using a formula to express the input using tissue curve with rate constant parameter. For multiple tissue curves extracted from the dynamic image, the rate constants were estimated so as to minimize the sum of the differences of the reproduced inputs expressed by the extracted tissue curves. The estimated rates were used to express the inputs and the mean of the estimated inputs was used as an IDIF. The method was tested in human subjects (n  =  29) and was compared to the blood sampling method. Simulation studies were performed to examine the magnitude of potential biases in CBF and to optimize the number of multiple tissue curves used for the input reconstruction. In the PET study, the estimated IDIFs were well reproduced against the measured ones. The difference between the calculated CBF values obtained using the two methods was small as around  <8% and the calculated CBF values showed a tight correlation (r  =  0.97). The simulation showed that errors associated with the assumed parameters were  <10%, and that the optimal number of tissue curves to be used was around 500. Our results demonstrate that IDIF can be reconstructed directly from tissue curves obtained through {{\\text{H}}2} 15O PET imaging. This suggests the possibility of using a completely non-invasive technique to assess CBF in patho-physiological studies.

A case of persistent visual hallucinations of faces following LSD abuse: a functional Magnetic Resonance Imaging study.

PubMed

Iaria, Giuseppe; Fox, Christopher J; Scheel, Michael; Stowe, Robert M; Barton, Jason J S

2010-04-01

In this study, we report the case of a patient experiencing hallucinations of faces that could be reliably precipitated by looking at trees. Using functional Magnetic Resonance Imaging (fMRI), we found that face hallucinations were associated with increased and decreased neural activity in a number of cortical regions. Within the same fusiform face area, however, we found significant decreased and increased neural activity according to whether the patient was experiencing hallucinations or veridical perception of faces, respectively. These findings may indicate key differences in how hallucinatory and veridical perceptions lead to the same phenomenological experience of seeing faces.

Training-Induced Recovery of Low-Level Vision Followed by Mid-Level Perceptual Improvements in Developmental Object and Face Agnosia

ERIC Educational Resources Information Center

Lev, Maria; Gilaie-Dotan, Sharon; Gotthilf-Nezri, Dana; Yehezkel, Oren; Brooks, Joseph L.; Perry, Anat; Bentin, Shlomo; Bonneh, Yoram; Polat, Uri

2015-01-01

Long-term deprivation of normal visual inputs can cause perceptual impairments at various levels of visual function, from basic visual acuity deficits, through mid-level deficits such as contour integration and motion coherence, to high-level face and object agnosia. Yet it is unclear whether training during adulthood, at a post-developmental…

Movement cues aid face recognition in developmental prosopagnosia.

PubMed

Bennetts, Rachel J; Butcher, Natalie; Lander, Karen; Udale, Robert; Bate, Sarah

2015-11-01

Seeing a face in motion can improve face recognition in the general population, and studies of face matching indicate that people with face recognition difficulties (developmental prosopagnosia; DP) may be able to use movement cues as a supplementary strategy to help them process faces. However, the use of facial movement cues in DP has not been examined in the context of familiar face recognition. This study examined whether people with DP were better at recognizing famous faces presented in motion, compared to static. Nine participants with DP and 14 age-matched controls completed a famous face recognition task. Each face was presented twice across 2 blocks: once in motion and once as a still image. Discriminability (A) was calculated for each block. Participants with DP showed a significant movement advantage overall. This was driven by a movement advantage in the first block, but not in the second block. Participants with DP were significantly worse than controls at identifying faces from static images, but there was no difference between those with DP and controls for moving images. Seeing a familiar face in motion can improve face recognition in people with DP, at least in some circumstances. The mechanisms behind this effect are unclear, but these results suggest that some people with DP are able to learn and recognize patterns of facial motion, and movement can act as a useful cue when face recognition is impaired. (c) 2015 APA, all rights reserved).

High precision automated face localization in thermal images: oral cancer dataset as test case

NASA Astrophysics Data System (ADS)

Chakraborty, M.; Raman, S. K.; Mukhopadhyay, S.; Patsa, S.; Anjum, N.; Ray, J. G.

2017-02-01

Automated face detection is the pivotal step in computer vision aided facial medical diagnosis and biometrics. This paper presents an automatic, subject adaptive framework for accurate face detection in the long infrared spectrum on our database for oral cancer detection consisting of malignant, precancerous and normal subjects of varied age group. Previous works on oral cancer detection using Digital Infrared Thermal Imaging(DITI) reveals that patients and normal subjects differ significantly in their facial thermal distribution. Therefore, it is a challenging task to formulate a completely adaptive framework to veraciously localize face from such a subject specific modality. Our model consists of first extracting the most probable facial regions by minimum error thresholding followed by ingenious adaptive methods to leverage the horizontal and vertical projections of the segmented thermal image. Additionally, the model incorporates our domain knowledge of exploiting temperature difference between strategic locations of the face. To our best knowledge, this is the pioneering work on detecting faces in thermal facial images comprising both patients and normal subjects. Previous works on face detection have not specifically targeted automated medical diagnosis; face bounding box returned by those algorithms are thus loose and not apt for further medical automation. Our algorithm significantly outperforms contemporary face detection algorithms in terms of commonly used metrics for evaluating face detection accuracy. Since our method has been tested on challenging dataset consisting of both patients and normal subjects of diverse age groups, it can be seamlessly adapted in any DITI guided facial healthcare or biometric applications.

Three-dimensional image display system using stereogram and holographic optical memory techniques

NASA Astrophysics Data System (ADS)

Kim, Cheol S.; Kim, Jung G.; Shin, Chang-Mok; Kim, Soo-Joong

2001-09-01

In this paper, we implemented a three dimensional image display system using stereogram and holographic optical memory techniques which can store many images and reconstruct them automatically. In this system, to store and reconstruct stereo images, incident angle of reference beam must be controlled in real time, so we used BPH (binary phase hologram) and LCD (liquid crystal display) for controlling reference beam. And input images are represented on the LCD without polarizer/analyzer for maintaining uniform beam intensities regardless of the brightness of input images. The input images and BPHs are edited using application software with having the same recording scheduled time interval in storing. The reconstructed stereo images are acquired by capturing the output images with CCD camera at the behind of the analyzer which transforms phase information into brightness information of images. The reference beams are acquired by Fourier transform of BPH which designed with SA (simulated annealing) algorithm, and represented on the LCD with the 0.05 seconds time interval using application software for reconstructing the stereo images. In output plane, we used a LCD shutter that is synchronized to a monitor that displays alternate left and right eye images for depth perception. We demonstrated optical experiment which store and reconstruct four stereo images in BaTiO3 repeatedly using holographic optical memory techniques.

Reconfigurable assembly work station

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Yhu-Tin; Abell, Jeffrey A.; Spicer, John Patrick

A reconfigurable autonomous workstation includes a multi-faced superstructure including a horizontally-arranged frame section supported on a plurality of posts. The posts form a plurality of vertical faces arranged between adjacent pairs of the posts, the faces including first and second faces and a power distribution and position reference face. A controllable robotic arm suspends from the rectangular frame section, and a work table fixedly couples to the power distribution and position reference face. A plurality of conveyor tables are fixedly coupled to the work table including a first conveyor table through the first face and a second conveyor table throughmore » the second face. A vision system monitors the work table and each of the conveyor tables. A programmable controller monitors signal inputs from the vision system to identify and determine orientation of the component on the first conveyor table and control the robotic arm to execute an assembly task.« less

Automatic face naming by learning discriminative affinity matrices from weakly labeled images.

PubMed

Xiao, Shijie; Xu, Dong; Wu, Jianxin

2015-10-01

Given a collection of images, where each image contains several faces and is associated with a few names in the corresponding caption, the goal of face naming is to infer the correct name for each face. In this paper, we propose two new methods to effectively solve this problem by learning two discriminative affinity matrices from these weakly labeled images. We first propose a new method called regularized low-rank representation by effectively utilizing weakly supervised information to learn a low-rank reconstruction coefficient matrix while exploring multiple subspace structures of the data. Specifically, by introducing a specially designed regularizer to the low-rank representation method, we penalize the corresponding reconstruction coefficients related to the situations where a face is reconstructed by using face images from other subjects or by using itself. With the inferred reconstruction coefficient matrix, a discriminative affinity matrix can be obtained. Moreover, we also develop a new distance metric learning method called ambiguously supervised structural metric learning by using weakly supervised information to seek a discriminative distance metric. Hence, another discriminative affinity matrix can be obtained using the similarity matrix (i.e., the kernel matrix) based on the Mahalanobis distances of the data. Observing that these two affinity matrices contain complementary information, we further combine them to obtain a fused affinity matrix, based on which we develop a new iterative scheme to infer the name of each face. Comprehensive experiments demonstrate the effectiveness of our approach.

Expression-dependent susceptibility to face distortions in processing of facial expressions of emotion.

PubMed

Guo, Kun; Soornack, Yoshi; Settle, Rebecca

2018-03-05

Our capability of recognizing facial expressions of emotion under different viewing conditions implies the existence of an invariant expression representation. As natural visual signals are often distorted and our perceptual strategy changes with external noise level, it is essential to understand how expression perception is susceptible to face distortion and whether the same facial cues are used to process high- and low-quality face images. We systematically manipulated face image resolution (experiment 1) and blur (experiment 2), and measured participants' expression categorization accuracy, perceived expression intensity and associated gaze patterns. Our analysis revealed a reasonable tolerance to face distortion in expression perception. Reducing image resolution up to 48 × 64 pixels or increasing image blur up to 15 cycles/image had little impact on expression assessment and associated gaze behaviour. Further distortion led to decreased expression categorization accuracy and intensity rating, increased reaction time and fixation duration, and stronger central fixation bias which was not driven by distortion-induced changes in local image saliency. Interestingly, the observed distortion effects were expression-dependent with less deterioration impact on happy and surprise expressions, suggesting this distortion-invariant facial expression perception might be achieved through the categorical model involving a non-linear configural combination of local facial features. Copyright © 2018 Elsevier Ltd. All rights reserved.

Automated facial acne assessment from smartphone images

NASA Astrophysics Data System (ADS)

Amini, Mohammad; Vasefi, Fartash; Valdebran, Manuel; Huang, Kevin; Zhang, Haomiao; Kemp, William; MacKinnon, Nicholas

2018-02-01

A smartphone mobile medical application is presented, that provides analysis of the health of skin on the face using a smartphone image and cloud-based image processing techniques. The mobile application employs the use of the camera to capture a front face image of a subject, after which the captured image is spatially calibrated based on fiducial points such as position of the iris of the eye. A facial recognition algorithm is used to identify features of the human face image, to normalize the image, and to define facial regions of interest (ROI) for acne assessment. We identify acne lesions and classify them into two categories: those that are papules and those that are pustules. Automated facial acne assessment was validated by performing tests on images of 60 digital human models and 10 real human face images. The application was able to identify 92% of acne lesions within five facial ROIs. The classification accuracy for separating papules from pustules was 98%. Combined with in-app documentation of treatment, lifestyle factors, and automated facial acne assessment, the app can be used in both cosmetic and clinical dermatology. It allows users to quantitatively self-measure acne severity and treatment efficacy on an ongoing basis to help them manage their chronic facial acne.

Focussed Ion Beam Milling and Scanning Electron Microscopy of Brain Tissue

PubMed Central

Knott, Graham; Rosset, Stéphanie; Cantoni, Marco

2011-01-01

This protocol describes how biological samples, like brain tissue, can be imaged in three dimensions using the focussed ion beam/scanning electron microscope (FIB/SEM). The samples are fixed with aldehydes, heavy metal stained using osmium tetroxide and uranyl acetate. They are then dehydrated with alcohol and infiltrated with resin, which is then hardened. Using a light microscope and ultramicrotome with glass knives, a small block containing the region interest close to the surface is made. The block is then placed inside the FIB/SEM, and the ion beam used to roughly mill a vertical face along one side of the block, close to this region. Using backscattered electrons to image the underlying structures, a smaller face is then milled with a finer ion beam and the surface scrutinised more closely to determine the exact area of the face to be imaged and milled. The parameters of the microscope are then set so that the face is repeatedly milled and imaged so that serial images are collected through a volume of the block. The image stack will typically contain isotropic voxels with dimenions as small a 4 nm in each direction. This image quality in any imaging plane enables the user to analyse cell ultrastructure at any viewing angle within the image stack. PMID:21775953

Comparison of different methods for gender estimation from face image of various poses

NASA Astrophysics Data System (ADS)

Ishii, Yohei; Hongo, Hitoshi; Niwa, Yoshinori; Yamamoto, Kazuhiko

2003-04-01

Recently, gender estimation from face images has been studied for frontal facial images. However, it is difficult to obtain such facial images constantly in the case of application systems for security, surveillance and marketing research. In order to build such systems, a method is required to estimate gender from the image of various facial poses. In this paper, three different classifiers are compared in appearance-based gender estimation, which use four directional features (FDF). The classifiers are linear discriminant analysis (LDA), Support Vector Machines (SVMs) and Sparse Network of Winnows (SNoW). Face images used for experiments were obtained from 35 viewpoints. The direction of viewpoints varied +/-45 degrees horizontally, +/-30 degrees vertically at 15 degree intervals respectively. Although LDA showed the best performance for frontal facial images, SVM with Gaussian kernel was found the best performance (86.0%) for the facial images of 35 viewpoints. It is considered that SVM with Gaussian kernel is robust to changes in viewpoint when estimating gender from these results. Furthermore, the estimation rate was quite close to the average estimation rate at 35 viewpoints respectively. It is supposed that the methods are reasonable to estimate gender within the range of experimented viewpoints by learning face images from multiple directions by one class.

Cerebral Cavernous Malformation

MedlinePlus

... and individuals frequently have multiple CCMs found via magnetic resonance imaging. Individuals with CCM are faced with a diagnosis ... and individuals frequently have multiple CCMs found via magnetic resonance imaging. Individuals with CCM are faced with a diagnosis ...

Hybrid Feature Extraction-based Approach for Facial Parts Representation and Recognition

NASA Astrophysics Data System (ADS)

Rouabhia, C.; Tebbikh, H.

2008-06-01

Face recognition is a specialized image processing which has attracted a considerable attention in computer vision. In this article, we develop a new facial recognition system from video sequences images dedicated to person identification whose face is partly occulted. This system is based on a hybrid image feature extraction technique called ACPDL2D (Rouabhia et al. 2007), it combines two-dimensional principal component analysis and two-dimensional linear discriminant analysis with neural network. We performed the feature extraction task on the eyes and the nose images separately then a Multi-Layers Perceptron classifier is used. Compared to the whole face, the results of simulation are in favor of the facial parts in terms of memory capacity and recognition (99.41% for the eyes part, 98.16% for the nose part and 97.25 % for the whole face).

Structured perceptual input imposes an egocentric frame of reference-pointing, imagery, and spatial self-consciousness.

PubMed

Marcel, Anthony; Dobel, Christian

2005-01-01

Perceptual input imposes and maintains an egocentric frame of reference, which enables orientation. When blindfolded, people tended to mistake the assumed intrinsic axes of symmetry of their immediate environment (a room) for their own egocentric relation to features of the room. When asked to point to the door and window, known to be at mid-points of facing (or adjacent) walls, they pointed with their arms at 180 degrees (or 90 degrees) angles, irrespective of where they thought they were in the room. People did the same when requested to imagine the situation. They justified their responses (inappropriately) by logical necessity or a structural description of the room rather than (appropriately) by relative location of themselves and the reference points. In eight experiments, we explored the effect on this in perception and imagery of: perceptual input (without perceptibility of the target reference points); imaging oneself versus another person; aids to explicit spatial self-consciousness; order of questions about self-location; and the relation of targets to the axes of symmetry of the room. The results indicate that, if one is deprived of structured perceptual input, as well as losing one's bearings, (a) one is likely to lose one's egocentric frame of reference itself, and (b) instead of pointing to reference points, one demonstrates their structural relation by adopting the intrinsic axes of the environment as one's own. This is prevented by providing noninformative perceptual input or by inducing subjects to imagine themselves from the outside, which makes explicit the fact of their being located relative to the world. The role of perceptual contact with a structured world is discussed in relation to sensory deprivation and imagery, appeal is made to Gibson's theory of joint egoreception and exteroception, and the data are related to recent theories of spatial memory and navigation.

Flat or curved thin optical display panel

DOEpatents

Veligdan, James T.

1995-01-10

An optical panel 10 includes a plurality of waveguides 12 stacked together, with each waveguide 12 having a first end 12a and an opposite second end 12b. The first ends 12a collectively define a first face 16, and the second ends 12b collectively define a second face 18 of the panel 10. The second face 18 is disposed at an acute face angle relative to the waveguides 12 to provide a panel 10 which is relatively thin compared to the height of the second face. In an exemplary embodiment for use in a projection TV, the first face 16 is substantially smaller in height than the second face 18 and receives a TV image, with the second face 18 defining a screen for viewing the image enlarged.

Directional templates for real-time detection of coronal axis rotated faces

NASA Astrophysics Data System (ADS)

Perez, Claudio A.; Estevez, Pablo A.; Garate, Patricio

2004-10-01

Real-time face and iris detection on video images has gained renewed attention because of multiple possible applications in studying eye function, drowsiness detection, virtual keyboard interfaces, face recognition, video processing and multimedia retrieval. In this paper, a study is presented on using directional templates in the detection of faces rotated in the coronal axis. The templates are built by extracting the directional image information from the regions of the eyes, nose and mouth. The face position is determined by computing a line integral using the templates over the face directional image. The line integral reaches a maximum when it coincides with the face position. It is shown an improvement in localization selectivity by the increased value in the line integral computed with the directional template. Besides, improvements in the line integral value for face size and face rotation angle was also found through the computation of the line integral using the directional template. Based on these results the new templates should improve selectivity and hence provide the means to restrict computations to a fewer number of templates and restrict the region of search during the face and eye tracking procedure. The proposed method is real time, completely non invasive and was applied with no background limitation and normal illumination conditions in an indoor environment.

Face matching impairment in developmental prosopagnosia.

PubMed

White, David; Rivolta, Davide; Burton, A Mike; Al-Janabi, Shahd; Palermo, Romina

2017-02-01

Developmental prosopagnosia (DP) is commonly referred to as 'face blindness', a term that implies a perceptual basis to the condition. However, DP presents as a deficit in face recognition and is diagnosed using memory-based tasks. Here, we test face identification ability in six people with DP, who are severely impaired on face memory tasks, using tasks that do not rely on memory. First, we compared DP to control participants on a standardized test of unfamiliar face matching using facial images taken on the same day and under standardized studio conditions (Glasgow Face Matching Test; GFMT). Scores for DP participants did not differ from normative accuracy scores on the GFMT. Second, we tested face matching performance on a test created using images that were sourced from the Internet and so varied substantially due to changes in viewing conditions and in a person's appearance (Local Heroes Test; LHT). DP participants showed significantly poorer matching accuracy on the LHT than control participants, for both unfamiliar and familiar face matching. Interestingly, this deficit is specific to 'match' trials, suggesting that people with DP may have particular difficulty in matching images of the same person that contain natural day-to-day variations in appearance. We discuss these results in the broader context of individual differences in face matching ability.

Vector generator scan converter

DOEpatents

Moore, J.M.; Leighton, J.F.

1988-02-05

High printing speeds for graphics data are achieved with a laser printer by transmitting compressed graphics data from a main processor over an I/O channel to a vector generator scan converter which reconstructs a full graphics image for input to the laser printer through a raster data input port. The vector generator scan converter includes a microprocessor with associated microcode memory containing a microcode instruction set, a working memory for storing compressed data, vector generator hardware for drawing a full graphic image from vector parameters calculated by the microprocessor, image buffer memory for storing the reconstructed graphics image and an output scanner for reading the graphics image data and inputting the data to the printer. The vector generator scan converter eliminates the bottleneck created by the I/O channel for transmitting graphics data from the main processor to the laser printer, and increases printer speed up to thirty fold. 7 figs.

Sharpening of Hierarchical Visual Feature Representations of Blurred Images.

PubMed

Abdelhack, Mohamed; Kamitani, Yukiyasu

2018-01-01

The robustness of the visual system lies in its ability to perceive degraded images. This is achieved through interacting bottom-up, recurrent, and top-down pathways that process the visual input in concordance with stored prior information. The interaction mechanism by which they integrate visual input and prior information is still enigmatic. We present a new approach using deep neural network (DNN) representation to reveal the effects of such integration on degraded visual inputs. We transformed measured human brain activity resulting from viewing blurred images to the hierarchical representation space derived from a feedforward DNN. Transformed representations were found to veer toward the original nonblurred image and away from the blurred stimulus image. This indicated deblurring or sharpening in the neural representation, and possibly in our perception. We anticipate these results will help unravel the interplay mechanism between bottom-up, recurrent, and top-down pathways, leading to more comprehensive models of vision.

Low-level image properties in facial expressions.

PubMed

Menzel, Claudia; Redies, Christoph; Hayn-Leichsenring, Gregor U

2018-06-04

We studied low-level image properties of face photographs and analyzed whether they change with different emotional expressions displayed by an individual. Differences in image properties were measured in three databases that depicted a total of 167 individuals. Face images were used either in their original form, cut to a standard format or superimposed with a mask. Image properties analyzed were: brightness, redness, yellowness, contrast, spectral slope, overall power and relative power in low, medium and high spatial frequencies. Results showed that image properties differed significantly between expressions within each individual image set. Further, specific facial expressions corresponded to patterns of image properties that were consistent across all three databases. In order to experimentally validate our findings, we equalized the luminance histograms and spectral slopes of three images from a given individual who showed two expressions. Participants were significantly slower in matching the expression in an equalized compared to an original image triad. Thus, existing differences in these image properties (i.e., spectral slope, brightness or contrast) facilitate emotion detection in particular sets of face images. Copyright © 2018. Published by Elsevier B.V.

Morphologic features of basal cell carcinoma using the en-face mode in frequency domain optical coherence tomography.

PubMed

von Braunmühl, T; Hartmann, D; Tietze, J K; Cekovic, D; Kunte, C; Ruzicka, T; Berking, C; Sattler, E C

2016-11-01

Optical coherence tomography (OCT) has become a valuable non-invasive tool in the in vivo diagnosis of non-melanoma skin cancer, especially of basal cell carcinoma (BCC). Due to an updated software-supported algorithm, a new en-face mode - similar to the horizontal en-face mode in high-definition OCT and reflectance confocal microscopy - surface-parallel imaging is possible which, in combination with the established slice mode of frequency domain (FD-)OCT, may offer additional information in the diagnosis of BCC. To define characteristic morphologic features of BCC using the new en-face mode in addition to the conventional cross-sectional imaging mode for three-dimensional imaging of BCC in FD-OCT. A total of 33 BCC were examined preoperatively by imaging in en-face mode as well as cross-sectional mode in FD-OCT. Characteristic features were evaluated and correlated with histopathology findings. Features established in the cross-sectional imaging mode as well as additional features were present in the en-face mode of FD-OCT: lobulated structures (100%), dark peritumoral rim (75%), bright peritumoral stroma (96%), branching vessels (90%), compressed fibrous bundles between lobulated nests ('star shaped') (78%), and intranodular small bright dots (51%). These features were also evaluated according to the histopathological subtype. In the en-face mode, the lobulated structures with compressed fibrous bundles of the BCC were more distinct than in the slice mode. FD-OCT with a new depiction for horizontal and vertical imaging modes offers additional information in the diagnosis of BCC, especially in nodular BCC, and enhances the possibility of the evaluation of morphologic tumour features. © 2016 European Academy of Dermatology and Venereology.

How does a newly encountered face become familiar? The effect of within-person variability on adults' and children's perception of identity.

PubMed

Baker, Kristen A; Laurence, Sarah; Mondloch, Catherine J

2017-04-01

Adults and children aged 6years and older easily recognize multiple images of a familiar face, but often perceive two images of an unfamiliar face as belonging to different identities. Here we examined the process by which a newly encountered face becomes familiar, defined as accurate recognition of multiple images that capture natural within-person variability in appearance. In Experiment 1 we examined whether exposure to within-person variability in appearance helps children learn a new face. Children aged 6-13years watched a 10-min video of a woman reading a story; she was filmed on a single day (low variability) or over three days, across which her appearance and filming conditions (e.g., camera, lighting) varied (high variability). After familiarization, participants sorted a set of images comprising novel images of the target identity intermixed with distractors. Compared to participants who received no familiarization, children showed evidence of learning only in the high-variability condition, in contrast to adults who showed evidence of learning in both the low- and high-variability conditions. Experiment 2 highlighted the efficiency with which adults learn a new face; their accuracy was comparable across training conditions despite variability in duration (1 vs. 10min) and type (video vs. static images) of training. Collectively, our findings show that exposure to variability leads to the formation of a robust representation of facial identity, consistent with perceptual learning in other domains (e.g., language), and that the development of face learning is protracted throughout childhood. We discuss possible underlying mechanisms. Copyright © 2016. Published by Elsevier B.V.

A system for tracking and recognizing pedestrian faces using a network of loosely coupled cameras

NASA Astrophysics Data System (ADS)

Gagnon, L.; Laliberté, F.; Foucher, S.; Branzan Albu, A.; Laurendeau, D.

2006-05-01

A face recognition module has been developed for an intelligent multi-camera video surveillance system. The module can recognize a pedestrian face in terms of six basic emotions and the neutral state. Face and facial features detection (eyes, nasal root, nose and mouth) are first performed using cascades of boosted classifiers. These features are used to normalize the pose and dimension of the face image. Gabor filters are then sampled on a regular grid covering the face image to build a facial feature vector that feeds a nearest neighbor classifier with a cosine distance similarity measure for facial expression interpretation and face model construction. A graphical user interface allows the user to adjust the module parameters.

A computer-generated animated face stimulus set for psychophysiological research

PubMed Central

Naples, Adam; Nguyen-Phuc, Alyssa; Coffman, Marika; Kresse, Anna; Faja, Susan; Bernier, Raphael; McPartland., James

2014-01-01

Human faces are fundamentally dynamic, but experimental investigations of face perception traditionally rely on static images of faces. While naturalistic videos of actors have been used with success in some contexts, much research in neuroscience and psychophysics demands carefully controlled stimuli. In this paper, we describe a novel set of computer generated, dynamic, face stimuli. These grayscale faces are tightly controlled for low- and high-level visual properties. All faces are standardized in terms of size, luminance, and location and size of facial features. Each face begins with a neutral pose and transitions to an expression over the course of 30 frames. Altogether there are 222 stimuli spanning 3 different categories of movement: (1) an affective movement (fearful face); (2) a neutral movement (close-lipped, puffed cheeks with open eyes); and (3) a biologically impossible movement (upward dislocation of eyes and mouth). To determine whether early brain responses sensitive to low-level visual features differed between expressions, we measured the occipital P100 event related potential (ERP), which is known to reflect differences in early stages of visual processing and the N170, which reflects structural encoding of faces. We found no differences between faces at the P100, indicating that different face categories were well matched on low-level image properties. This database provides researchers with a well-controlled set of dynamic faces controlled on low-level image characteristics that are applicable to a range of research questions in social perception. PMID:25028164

Faciotopy—A face-feature map with face-like topology in the human occipital face area

PubMed Central

Henriksson, Linda; Mur, Marieke; Kriegeskorte, Nikolaus

2015-01-01

The occipital face area (OFA) and fusiform face area (FFA) are brain regions thought to be specialized for face perception. However, their intrinsic functional organization and status as cortical areas with well-defined boundaries remains unclear. Here we test these regions for “faciotopy”, a particular hypothesis about their intrinsic functional organisation. A faciotopic area would contain a face-feature map on the cortical surface, where cortical patches represent face features and neighbouring patches represent features that are physically neighbouring in a face. The faciotopy hypothesis is motivated by the idea that face regions might develop from a retinotopic protomap and acquire their selectivity for face features through natural visual experience. Faces have a prototypical configuration of features, are usually perceived in a canonical upright orientation, and are frequently fixated in particular locations. To test the faciotopy hypothesis, we presented images of isolated face features at fixation to subjects during functional magnetic resonance imaging. The responses in V1 were best explained by low-level image properties of the stimuli. OFA, and to a lesser degree FFA, showed evidence for faciotopic organization. When a single patch of cortex was estimated for each face feature, the cortical distances between the feature patches reflected the physical distance between the features in a face. Faciotopy would be the first example, to our knowledge, of a cortical map reflecting the topology, not of a part of the organism itself (its retina in retinotopy, its body in somatotopy), but of an external object of particular perceptual significance. PMID:26235800

Faciotopy-A face-feature map with face-like topology in the human occipital face area.

PubMed

Henriksson, Linda; Mur, Marieke; Kriegeskorte, Nikolaus

2015-11-01

The occipital face area (OFA) and fusiform face area (FFA) are brain regions thought to be specialized for face perception. However, their intrinsic functional organization and status as cortical areas with well-defined boundaries remains unclear. Here we test these regions for "faciotopy", a particular hypothesis about their intrinsic functional organisation. A faciotopic area would contain a face-feature map on the cortical surface, where cortical patches represent face features and neighbouring patches represent features that are physically neighbouring in a face. The faciotopy hypothesis is motivated by the idea that face regions might develop from a retinotopic protomap and acquire their selectivity for face features through natural visual experience. Faces have a prototypical configuration of features, are usually perceived in a canonical upright orientation, and are frequently fixated in particular locations. To test the faciotopy hypothesis, we presented images of isolated face features at fixation to subjects during functional magnetic resonance imaging. The responses in V1 were best explained by low-level image properties of the stimuli. OFA, and to a lesser degree FFA, showed evidence for faciotopic organization. When a single patch of cortex was estimated for each face feature, the cortical distances between the feature patches reflected the physical distance between the features in a face. Faciotopy would be the first example, to our knowledge, of a cortical map reflecting the topology, not of a part of the organism itself (its retina in retinotopy, its body in somatotopy), but of an external object of particular perceptual significance. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Dependence of the appearance-based perception of criminality, suggestibility, and trustworthiness on the level of pixelation of facial images.

PubMed

Nurmoja, Merle; Eamets, Triin; Härma, Hanne-Loore; Bachmann, Talis

2012-10-01

While the dependence of face identification on the level of pixelation-transform of the images of faces has been well studied, similar research on face-based trait perception is underdeveloped. Because depiction formats used for hiding individual identity in visual media and evidential material recorded by surveillance cameras often consist of pixelized images, knowing the effects of pixelation on person perception has practical relevance. Here, the results of two experiments are presented showing the effect of facial image pixelation on the perception of criminality, trustworthiness, and suggestibility. It appears that individuals (N = 46, M age = 21.5 yr., SD = 3.1 for criminality ratings; N = 94, M age = 27.4 yr., SD = 10.1 for other ratings) have the ability to discriminate between facial cues ndicative of these perceived traits from the coarse level of image pixelation (10-12 pixels per face horizontally) and that the discriminability increases with a decrease in the coarseness of pixelation. Perceived criminality and trustworthiness appear to be better carried by the pixelized images than perceived suggestibility.

An efficient method for facial component detection in thermal images

NASA Astrophysics Data System (ADS)

Paul, Michael; Blanik, Nikolai; Blazek, Vladimir; Leonhardt, Steffen

2015-04-01

A method to detect certain regions in thermal images of human faces is presented. In this approach, the following steps are necessary to locate the periorbital and the nose regions: First, the face is segmented from the background by thresholding and morphological filtering. Subsequently, a search region within the face, around its center of mass, is evaluated. Automatically computed temperature thresholds are used per subject and image or image sequence to generate binary images, in which the periorbital regions are located by integral projections. Then, the located positions are used to approximate the nose position. It is possible to track features in the located regions. Therefore, these regions are interesting for different applications like human-machine interaction, biometrics and biomedical imaging. The method is easy to implement and does not rely on any training images or templates. Furthermore, the approach saves processing resources due to simple computations and restricted search regions.

Correction of motion artifacts in endoscopic optical coherence tomography and autofluorescence images based on azimuthal en face image registration.

PubMed

Abouei, Elham; Lee, Anthony M D; Pahlevaninezhad, Hamid; Hohert, Geoffrey; Cua, Michelle; Lane, Pierre; Lam, Stephen; MacAulay, Calum

2018-01-01

We present a method for the correction of motion artifacts present in two- and three-dimensional in vivo endoscopic images produced by rotary-pullback catheters. This method can correct for cardiac/breathing-based motion artifacts and catheter-based motion artifacts such as nonuniform rotational distortion (NURD). This method assumes that en face tissue imaging contains slowly varying structures that are roughly parallel to the pullback axis. The method reduces motion artifacts using a dynamic time warping solution through a cost matrix that measures similarities between adjacent frames in en face images. We optimize and demonstrate the suitability of this method using a real and simulated NURD phantom and in vivo endoscopic pulmonary optical coherence tomography and autofluorescence images. Qualitative and quantitative evaluations of the method show an enhancement of the image quality. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Pharmacokinetics, metabolism, biodistribution, radiation dosimetry, and toxicology of (18)F-fluoroacetate ((18)F-FACE) in non-human primates.

PubMed

Nishii, Ryuichi; Tong, William; Wendt, Richard; Soghomonyan, Suren; Mukhopadhyay, Uday; Balatoni, Julius; Mawlawi, Osama; Bidaut, Luc; Tinkey, Peggy; Borne, Agatha; Alauddin, Mian; Gonzalez-Lepera, Carlos; Yang, Bijun; Gelovani, Juri G

2012-04-01

To facilitate the clinical translation of (18)F-fluoroacetate ((18)F-FACE), the pharmacokinetics, biodistribution, radiolabeled metabolites, radiation dosimetry, and pharmacological safety of diagnostic doses of (18)F-FACE were determined in non-human primates. (18)F-FACE was synthesized using a custom-built automated synthesis module. Six rhesus monkeys (three of each sex) were injected intravenously with (18)F-FACE (165.4 ± 28.5 MBq), followed by dynamic positron emission tomography (PET) imaging of the thoracoabdominal area during 0-30 min post-injection and static whole-body PET imaging at 40, 100, and 170 min. Serial blood samples and a urine sample were obtained from each animal to determine the time course of (18)F-FACE and its radiolabeled metabolites. Electrocardiograms and hematology analyses were obtained to evaluate the acute and delayed toxicity of diagnostic dosages of (18)F-FACE. The time-integrated activity coefficients for individual source organs and the whole body after administration of (18)F-FACE were obtained using quantitative analyses of dynamic and static PET images and were extrapolated to humans. The blood clearance of (18)F-FACE exhibited bi-exponential kinetics with half-times of 4 and 250 min for the fast and slow phases, respectively. A rapid accumulation of (18)F-FACE-derived radioactivity was observed in the liver and kidneys, followed by clearance of the radioactivity into the intestine and the urinary bladder. Radio-HPLC analyses of blood and urine samples demonstrated that (18)F-fluoride was the only detectable radiolabeled metabolite at the level of less than 9% of total radioactivity in blood at 180 min after the (18)F-FACE injection. The uptake of free (18)F-fluoride in the bones was insignificant during the course of the imaging studies. No significant changes in ECG, CBC, liver enzymes, or renal function were observed. The estimated effective dose for an adult human is 3.90-7.81 mSv from the administration of 185-370 MBq of (18)F-FACE. The effective dose and individual organ radiation absorbed doses from administration of a diagnostic dosage of (18)F-FACE are acceptable. From a pharmacologic perspective, diagnostic dosages of (18)F-FACE are non-toxic in primates and, therefore, could be safely administered to human patients for PET imaging.

Correlation based efficient face recognition and color change detection

NASA Astrophysics Data System (ADS)

Elbouz, M.; Alfalou, A.; Brosseau, C.; Alam, M. S.; Qasmi, S.

2013-01-01

Identifying the human face via correlation is a topic attracting widespread interest. At the heart of this technique lies the comparison of an unknown target image to a known reference database of images. However, the color information in the target image remains notoriously difficult to interpret. In this paper, we report a new technique which: (i) is robust against illumination change, (ii) offers discrimination ability to detect color change between faces having similar shape, and (iii) is specifically designed to detect red colored stains (i.e. facial bleeding). We adopt the Vanderlugt correlator (VLC) architecture with a segmented phase filter and we decompose the color target image using normalized red, green, and blue (RGB), and hue, saturation, and value (HSV) scales. We propose a new strategy to effectively utilize color information in signatures for further increasing the discrimination ability. The proposed algorithm has been found to be very efficient for discriminating face subjects with different skin colors, and those having color stains in different areas of the facial image.

Robust Mapping of Incoherent Fiber-Optic Bundles

NASA Technical Reports Server (NTRS)

Roberts, Harry E.; Deason, Brent E.; DePlachett, Charles P.; Pilgrim, Robert A.; Sanford, Harold S.

2007-01-01

A method and apparatus for mapping between the positions of fibers at opposite ends of incoherent fiber-optic bundles have been invented to enable the use of such bundles to transmit images in visible or infrared light. The method is robust in the sense that it provides useful mapping even for a bundle that contains thousands of narrow, irregularly packed fibers, some of which may be defective. In a coherent fiber-optic bundle, the input and output ends of each fiber lie at identical positions in the input and output planes; therefore, the bundle can be used to transmit images without further modification. Unfortunately, the fabrication of coherent fiber-optic bundles is too labor-intensive and expensive for many applications. An incoherent fiber-optic bundle can be fabricated more easily and at lower cost, but it produces a scrambled image because the position of the end of each fiber in the input plane is generally different from the end of the same fiber in the output plane. However, the image transmitted by an incoherent fiber-optic bundle can be unscrambled (or, from a different perspective, decoded) by digital processing of the output image if the mapping between the input and output fiber-end positions is known. Thus, the present invention enables the use of relatively inexpensive fiber-optic bundles to transmit images.

Research of Face Recognition with Fisher Linear Discriminant

NASA Astrophysics Data System (ADS)

Rahim, R.; Afriliansyah, T.; Winata, H.; Nofriansyah, D.; Ratnadewi; Aryza, S.

2018-01-01

Face identification systems are developing rapidly, and these developments drive the advancement of biometric-based identification systems that have high accuracy. However, to develop a good face recognition system and to have high accuracy is something that’s hard to find. Human faces have diverse expressions and attribute changes such as eyeglasses, mustache, beard and others. Fisher Linear Discriminant (FLD) is a class-specific method that distinguishes facial image images into classes and also creates distance between classes and intra classes so as to produce better classification.

Real-time calibration-free C-scan images of the eye fundus using Master Slave swept source optical coherence tomography

NASA Astrophysics Data System (ADS)

Bradu, Adrian; Kapinchev, Konstantin; Barnes, Fred; Garway-Heath, David F.; Rajendram, Ranjan; Keane, Pearce; Podoleanu, Adrian G.

2015-03-01

Recently, we introduced a novel Optical Coherence Tomography (OCT) method, termed as Master Slave OCT (MS-OCT), specialized for delivering en-face images. This method uses principles of spectral domain interfereometry in two stages. MS-OCT operates like a time domain OCT, selecting only signals from a chosen depth only while scanning the laser beam across the eye. Time domain OCT allows real time production of an en-face image, although relatively slowly. As a major advance, the Master Slave method allows collection of signals from any number of depths, as required by the user. The tremendous advantage in terms of parallel provision of data from numerous depths could not be fully employed by using multi core processors only. The data processing required to generate images at multiple depths simultaneously is not achievable with commodity multicore processors only. We compare here the major improvement in processing and display, brought about by using graphic cards. We demonstrate images obtained with a swept source at 100 kHz (which determines an acquisition time [Ta] for a frame of 200×200 pixels2 of Ta =1.6 s). By the end of the acquired frame being scanned, using our computing capacity, 4 simultaneous en-face images could be created in T = 0.8 s. We demonstrate that by using graphic cards, 32 en-face images can be displayed in Td 0.3 s. Other faster swept source engines can be used with no difference in terms of Td. With 32 images (or more), volumes can be created for 3D display, using en-face images, as opposed to the current technology where volumes are created using cross section OCT images.

CLASSIFYING MEDICAL IMAGES USING MORPHOLOGICAL APPEARANCE MANIFOLDS.

PubMed

Varol, Erdem; Gaonkar, Bilwaj; Davatzikos, Christos

2013-12-31

Input features for medical image classification algorithms are extracted from raw images using a series of pre processing steps. One common preprocessing step in computational neuroanatomy and functional brain mapping is the nonlinear registration of raw images to a common template space. Typically, the registration methods used are parametric and their output varies greatly with changes in parameters. Most results reported previously perform registration using a fixed parameter setting and use the results as input to the subsequent classification step. The variation in registration results due to choice of parameters thus translates to variation of performance of the classifiers that depend on the registration step for input. Analogous issues have been investigated in the computer vision literature, where image appearance varies with pose and illumination, thereby making classification vulnerable to these confounding parameters. The proposed methodology addresses this issue by sampling image appearances as registration parameters vary, and shows that better classification accuracies can be obtained this way, compared to the conventional approach.

Not looking yourself: The cost of self-selecting photographs for identity verification.

PubMed

White, David; Burton, Amy L; Kemp, Richard I

2016-05-01

Photo-identification is based on the premise that photographs are representative of facial appearance. However, previous studies show that ratings of likeness vary across different photographs of the same face, suggesting that some images capture identity better than others. Two experiments were designed to examine the relationship between likeness judgments and face matching accuracy. In Experiment 1, we compared unfamiliar face matching accuracy for self-selected and other-selected high-likeness images. Surprisingly, images selected by previously unfamiliar viewers - after very limited exposure to a target face - were more accurately matched than self-selected images chosen by the target identity themselves. Results also revealed extremely low inter-rater agreement in ratings of likeness across participants, suggesting that perceptions of image resemblance are inherently unstable. In Experiment 2, we test whether the cost of self-selection can be explained by this general disagreement in likeness judgments between individual raters. We find that averaging across rankings by multiple raters produces image selections that provide superior identification accuracy. However, benefit of other-selection persisted for single raters, suggesting that inaccurate representations of self interfere with our ability to judge which images faithfully represent our current appearance. © 2015 The British Psychological Society.

Reconstructing Perceived and Retrieved Faces from Activity Patterns in Lateral Parietal Cortex.

PubMed

Lee, Hongmi; Kuhl, Brice A

2016-06-01

Recent findings suggest that the contents of memory encoding and retrieval can be decoded from the angular gyrus (ANG), a subregion of posterior lateral parietal cortex. However, typical decoding approaches provide little insight into the nature of ANG content representations. Here, we tested whether complex, multidimensional stimuli (faces) could be reconstructed from ANG by predicting underlying face components from fMRI activity patterns in humans. Using an approach inspired by computer vision methods for face recognition, we applied principal component analysis to a large set of face images to generate eigenfaces. We then modeled relationships between eigenface values and patterns of fMRI activity. Activity patterns evoked by individual faces were then used to generate predicted eigenface values, which could be transformed into reconstructions of individual faces. We show that visually perceived faces were reliably reconstructed from activity patterns in occipitotemporal cortex and several lateral parietal subregions, including ANG. Subjective assessment of reconstructed faces revealed specific sources of information (e.g., affect and skin color) that were successfully reconstructed in ANG. Strikingly, we also found that a model trained on ANG activity patterns during face perception was able to successfully reconstruct an independent set of face images that were held in memory. Together, these findings provide compelling evidence that ANG forms complex, stimulus-specific representations that are reflected in activity patterns evoked during perception and remembering. Neuroimaging studies have consistently implicated lateral parietal cortex in episodic remembering, but the functional contributions of lateral parietal cortex to memory remain a topic of debate. Here, we used an innovative form of fMRI pattern analysis to test whether lateral parietal cortex actively represents the contents of memory. Using a large set of human face images, we first extracted latent face components (eigenfaces). We then used machine learning algorithms to predict face components from fMRI activity patterns and, ultimately, to reconstruct images of individual faces. We show that activity patterns in a subregion of lateral parietal cortex, the angular gyrus, supported successful reconstruction of perceived and remembered faces, confirming a role for this region in actively representing remembered content. Copyright © 2016 the authors 0270-6474/16/366069-14$15.00/0.

Discriminative Projection Selection Based Face Image Hashing

NASA Astrophysics Data System (ADS)

Karabat, Cagatay; Erdogan, Hakan

Face image hashing is an emerging method used in biometric verification systems. In this paper, we propose a novel face image hashing method based on a new technique called discriminative projection selection. We apply the Fisher criterion for selecting the rows of a random projection matrix in a user-dependent fashion. Moreover, another contribution of this paper is to employ a bimodal Gaussian mixture model at the quantization step. Our simulation results on three different databases demonstrate that the proposed method has superior performance in comparison to previously proposed random projection based methods.

FaceWarehouse: a 3D facial expression database for visual computing.

PubMed

Cao, Chen; Weng, Yanlin; Zhou, Shun; Tong, Yiying; Zhou, Kun

2014-03-01

We present FaceWarehouse, a database of 3D facial expressions for visual computing applications. We use Kinect, an off-the-shelf RGBD camera, to capture 150 individuals aged 7-80 from various ethnic backgrounds. For each person, we captured the RGBD data of her different expressions, including the neutral expression and 19 other expressions such as mouth-opening, smile, kiss, etc. For every RGBD raw data record, a set of facial feature points on the color image such as eye corners, mouth contour, and the nose tip are automatically localized, and manually adjusted if better accuracy is required. We then deform a template facial mesh to fit the depth data as closely as possible while matching the feature points on the color image to their corresponding points on the mesh. Starting from these fitted face meshes, we construct a set of individual-specific expression blendshapes for each person. These meshes with consistent topology are assembled as a rank-3 tensor to build a bilinear face model with two attributes: identity and expression. Compared with previous 3D facial databases, for every person in our database, there is a much richer matching collection of expressions, enabling depiction of most human facial actions. We demonstrate the potential of FaceWarehouse for visual computing with four applications: facial image manipulation, face component transfer, real-time performance-based facial image animation, and facial animation retargeting from video to image.

Novel view synthesis by interpolation over sparse examples

NASA Astrophysics Data System (ADS)

Liang, Bodong; Chung, Ronald C.

2006-01-01

Novel view synthesis (NVS) is an important problem in image rendering. It involves synthesizing an image of a scene at any specified (novel) viewpoint, given some images of the scene at a few sample viewpoints. The general understanding is that the solution should bypass explicit 3-D reconstruction of the scene. As it is, the problem has a natural tie to interpolation, despite that mainstream efforts on the problem have been adopting formulations otherwise. Interpolation is about finding the output of a function f(x) for any specified input x, given a few input-output pairs {(xi,fi):i=1,2,3,...,n} of the function. If the input x is the viewpoint, and f(x) is the image, the interpolation problem becomes exactly NVS. We treat the NVS problem using the interpolation formulation. In particular, we adopt the example-based everything or interpolation (EBI) mechanism-an established mechanism for interpolating or learning functions from examples. EBI has all the desirable properties of a good interpolation: all given input-output examples are satisfied exactly, and the interpolation is smooth with minimum oscillations between the examples. We point out that EBI, however, has difficulty in interpolating certain classes of functions, including the image function in the NVS problem. We propose an extension of the mechanism for overcoming the limitation. We also present how the extended interpolation mechanism could be used to synthesize images at novel viewpoints. Real image results show that the mechanism has promising performance, even with very few example images.

Secret shared multiple-image encryption based on row scanning compressive ghost imaging and phase retrieval in the Fresnel domain

NASA Astrophysics Data System (ADS)

Li, Xianye; Meng, Xiangfeng; Wang, Yurong; Yang, Xiulun; Yin, Yongkai; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

2017-09-01

A multiple-image encryption method is proposed that is based on row scanning compressive ghost imaging, (t, n) threshold secret sharing, and phase retrieval in the Fresnel domain. In the encryption process, after wavelet transform and Arnold transform of the target image, the ciphertext matrix can be first detected using a bucket detector. Based on a (t, n) threshold secret sharing algorithm, the measurement key used in the row scanning compressive ghost imaging can be decomposed and shared into two pairs of sub-keys, which are then reconstructed using two phase-only mask (POM) keys with fixed pixel values, placed in the input plane and transform plane 2 of the phase retrieval scheme, respectively; and the other POM key in the transform plane 1 can be generated and updated by the iterative encoding of each plaintext image. In each iteration, the target image acts as the input amplitude constraint in the input plane. During decryption, each plaintext image possessing all the correct keys can be successfully decrypted by measurement key regeneration, compression algorithm reconstruction, inverse wavelet transformation, and Fresnel transformation. Theoretical analysis and numerical simulations both verify the feasibility of the proposed method.

Brain regions sensitive to the face inversion effect: a functional magnetic resonance imaging study in humans.

PubMed

Leube, Dirk T; Yoon, Hyo Woon; Rapp, Alexander; Erb, Michael; Grodd, Wolfgang; Bartels, Mathias; Kircher, Tilo T J

2003-05-22

Perception of upright faces relies on configural processing. Therefore recognition of inverted, compared to upright faces is impaired. In a functional magnetic resonance imaging experiment we investigated the neural correlate of a face inversion task. Thirteen healthy subjects were presented with a equal number of upright and inverted faces alternating with a low level baseline with an upright and inverted picture of an abstract symbol. Brain activation was calculated for upright minus inverted faces. For this differential contrast, we found a signal change in the right superior temporal sulcus and right insula. Configural properties are processed in a network comprising right superior temporal and insular cortex.

En Face Spectral-Domain Optical Coherence Tomography for the Diagnosis and Evaluation of Polypoidal Choroidal Vasculopathy.

PubMed

Kokame, Gregg T; Shantha, Jessica G; Hirai, Kelsi; Ayabe, Julia

2016-08-01

To evaluate the diagnostic capability of en face spectral-domain optical coherence tomography (SD-OCT) in patients with polypoidal choroidal vasculopathy (PCV) diagnosed by indocyanine green angiography (ICGA). A retrospective, consecutive case series of 100 eyes diagnosed with PCV by ICGA were imaged with en face SD-OCT. Evaluation of the PCV complex on en face SD-OCT was performed on the ability to diagnose PCV by the characteristic configuration of the PCV complex and the extent and size of the PCV lesion. The PCV complex was better visualized on ICGA in 45 eyes, on en face SD-OCT in 44 eyes, and equally well in 11 eyes. The extent of the PCV complex was larger on en face SD-OCT in 65 eyes, larger on ICGA in 23 eyes, and equal in size in 12 eyes. En face SD-OCT images the characteristic findings of PCV and provides a noninvasive way to diagnose and treat PCV when ICGA is not available. [Ophthalmic Surg Lasers Imaging Retina. 2016;47:737-744.]. Copyright 2016, SLACK Incorporated.

Online and unsupervised face recognition for continuous video stream

NASA Astrophysics Data System (ADS)

Huo, Hongwen; Feng, Jufu

2009-10-01

We present a novel online face recognition approach for video stream in this paper. Our method includes two stages: pre-training and online training. In the pre-training phase, our method observes interactions, collects batches of input data, and attempts to estimate their distributions (Box-Cox transformation is adopted here to normalize rough estimates). In the online training phase, our method incrementally improves classifiers' knowledge of the face space and updates it continuously with incremental eigenspace analysis. The performance achieved by our method shows its great potential in video stream processing.

Estimating atmospheric parameters and reducing noise for multispectral imaging

DOEpatents

Conger, James Lynn

2014-02-25

A method and system for estimating atmospheric radiance and transmittance. An atmospheric estimation system is divided into a first phase and a second phase. The first phase inputs an observed multispectral image and an initial estimate of the atmospheric radiance and transmittance for each spectral band and calculates the atmospheric radiance and transmittance for each spectral band, which can be used to generate a "corrected" multispectral image that is an estimate of the surface multispectral image. The second phase inputs the observed multispectral image and the surface multispectral image that was generated by the first phase and removes noise from the surface multispectral image by smoothing out change in average deviations of temperatures.

Do bodily expressions compete with facial expressions? Time course of integration of emotional signals from the face and the body.

PubMed

Gu, Yuanyuan; Mai, Xiaoqin; Luo, Yue-jia

2013-01-01

The decoding of social signals from nonverbal cues plays a vital role in the social interactions of socially gregarious animals such as humans. Because nonverbal emotional signals from the face and body are normally seen together, it is important to investigate the mechanism underlying the integration of emotional signals from these two sources. We conducted a study in which the time course of the integration of facial and bodily expressions was examined via analysis of event-related potentials (ERPs) while the focus of attention was manipulated. Distinctive integrating features were found during multiple stages of processing. In the first stage, threatening information from the body was extracted automatically and rapidly, as evidenced by enhanced P1 amplitudes when the subjects viewed compound face-body images with fearful bodies compared with happy bodies. In the second stage, incongruency between emotional information from the face and the body was detected and captured by N2. Incongruent compound images elicited larger N2s than did congruent compound images. The focus of attention modulated the third stage of integration. When the subjects' attention was focused on the face, images with congruent emotional signals elicited larger P3s than did images with incongruent signals, suggesting more sustained attention and elaboration of congruent emotional information extracted from the face and body. On the other hand, when the subjects' attention was focused on the body, images with fearful bodies elicited larger P3s than did images with happy bodies, indicating more sustained attention and elaboration of threatening information from the body during evaluative processes.

Do Bodily Expressions Compete with Facial Expressions? Time Course of Integration of Emotional Signals from the Face and the Body

PubMed Central

Gu, Yuanyuan; Mai, Xiaoqin; Luo, Yue-jia

2013-01-01

The decoding of social signals from nonverbal cues plays a vital role in the social interactions of socially gregarious animals such as humans. Because nonverbal emotional signals from the face and body are normally seen together, it is important to investigate the mechanism underlying the integration of emotional signals from these two sources. We conducted a study in which the time course of the integration of facial and bodily expressions was examined via analysis of event-related potentials (ERPs) while the focus of attention was manipulated. Distinctive integrating features were found during multiple stages of processing. In the first stage, threatening information from the body was extracted automatically and rapidly, as evidenced by enhanced P1 amplitudes when the subjects viewed compound face-body images with fearful bodies compared with happy bodies. In the second stage, incongruency between emotional information from the face and the body was detected and captured by N2. Incongruent compound images elicited larger N2s than did congruent compound images. The focus of attention modulated the third stage of integration. When the subjects' attention was focused on the face, images with congruent emotional signals elicited larger P3s than did images with incongruent signals, suggesting more sustained attention and elaboration of congruent emotional information extracted from the face and body. On the other hand, when the subjects' attention was focused on the body, images with fearful bodies elicited larger P3s than did images with happy bodies, indicating more sustained attention and elaboration of threatening information from the body during evaluative processes. PMID:23935825

Synaptic plasticity in a cerebellum-like structure depends on temporal order

NASA Astrophysics Data System (ADS)

Bell, Curtis C.; Han, Victor Z.; Sugawara, Yoshiko; Grant, Kirsty

1997-05-01

Cerebellum-like structures in fish appear to act as adaptive sensory processors, in which learned predictions about sensory input are generated and subtracted from actual sensory input, allowing unpredicted inputs to stand out1-3. Pairing sensory input with centrally originating predictive signals, such as corollary discharge signals linked to motor commands, results in neural responses to the predictive signals alone that are Negative images' of the previously paired sensory responses. Adding these 'negative images' to actual sensory inputs minimizes the neural response to predictable sensory features. At the cellular level, sensory input is relayed to the basal region of Purkinje-like cells, whereas predictive signals are relayed by parallel fibres to the apical dendrites of the same cells4. The generation of negative images could be explained by plasticity at parallel fibre synapses5-7. We show here that such plasticity exists in the electrosensory lobe of mormyrid electric fish and that it has the necessary properties for such a model: it is reversible, anti-hebbian (excitatory postsynaptic potentials (EPSPs) are depressed after pairing with a postsynaptic spike) and tightly dependent on the sequence of pre- and postsynaptic events, with depression occurring only if the postsynaptic spike follows EPSP onset within 60 ms.

Fast periodic stimulation (FPS): a highly effective approach in fMRI brain mapping.

PubMed

Gao, Xiaoqing; Gentile, Francesco; Rossion, Bruno

2018-06-01

Defining the neural basis of perceptual categorization in a rapidly changing natural environment with low-temporal resolution methods such as functional magnetic resonance imaging (fMRI) is challenging. Here, we present a novel fast periodic stimulation (FPS)-fMRI approach to define face-selective brain regions with natural images. Human observers are presented with a dynamic stream of widely variable natural object images alternating at a fast rate (6 images/s). Every 9 s, a short burst of variable face images contrasting with object images in pairs induces an objective face-selective neural response at 0.111 Hz. A model-free Fourier analysis achieves a twofold increase in signal-to-noise ratio compared to a conventional block-design approach with identical stimuli and scanning duration, allowing to derive a comprehensive map of face-selective areas in the ventral occipito-temporal cortex, including the anterior temporal lobe (ATL), in all individual brains. Critically, periodicity of the desired category contrast and random variability among widely diverse images effectively eliminates the contribution of low-level visual cues, and lead to the highest values (80-90%) of test-retest reliability in the spatial activation map yet reported in imaging higher level visual functions. FPS-fMRI opens a new avenue for understanding brain function with low-temporal resolution methods.

Age synthesis and estimation via faces: a survey.

PubMed

Fu, Yun; Guo, Guodong; Huang, Thomas S

2010-11-01

Human age, as an important personal trait, can be directly inferred by distinct patterns emerging from the facial appearance. Derived from rapid advances in computer graphics and machine vision, computer-based age synthesis and estimation via faces have become particularly prevalent topics recently because of their explosively emerging real-world applications, such as forensic art, electronic customer relationship management, security control and surveillance monitoring, biometrics, entertainment, and cosmetology. Age synthesis is defined to rerender a face image aesthetically with natural aging and rejuvenating effects on the individual face. Age estimation is defined to label a face image automatically with the exact age (year) or the age group (year range) of the individual face. Because of their particularity and complexity, both problems are attractive yet challenging to computer-based application system designers. Large efforts from both academia and industry have been devoted in the last a few decades. In this paper, we survey the complete state-of-the-art techniques in the face image-based age synthesis and estimation topics. Existing models, popular algorithms, system performances, technical difficulties, popular face aging databases, evaluation protocols, and promising future directions are also provided with systematic discussions.

Effects of exposure to facial expression variation in face learning and recognition.

PubMed

Liu, Chang Hong; Chen, Wenfeng; Ward, James

2015-11-01

Facial expression is a major source of image variation in face images. Linking numerous expressions to the same face can be a huge challenge for face learning and recognition. It remains largely unknown what level of exposure to this image variation is critical for expression-invariant face recognition. We examined this issue in a recognition memory task, where the number of facial expressions of each face being exposed during a training session was manipulated. Faces were either trained with multiple expressions or a single expression, and they were later tested in either the same or different expressions. We found that recognition performance after learning three emotional expressions had no improvement over learning a single emotional expression (Experiments 1 and 2). However, learning three emotional expressions improved recognition compared to learning a single neutral expression (Experiment 3). These findings reveal both the limitation and the benefit of multiple exposures to variations of emotional expression in achieving expression-invariant face recognition. The transfer of expression training to a new type of expression is likely to depend on a relatively extensive level of training and a certain degree of variation across the types of expressions.

Body image and face image in Asian American and white women: Examining associations with surveillance, construal of self, perfectionism, and sociocultural pressures.

PubMed

Frederick, David A; Kelly, Mackenzie C; Latner, Janet D; Sandhu, Gaganjyot; Tsong, Yuying

2016-03-01

Asian American women experience sociocultural pressures that could place them at increased risk for experiencing body and face dissatisfaction. Asian American and White women completed measures of appearance evaluation, overweight preoccupation, face satisfaction, face dissatisfaction frequency, perfectionism, surveillance, interdependent and independent self-construal, and perceived sociocultural pressures. In Study 1 (N=182), Asian American women were more likely than White women to report low appearance evaluation (24% vs. 12%; d=-0.50) and to be sometimes-always dissatisfied with the appearance of their eyes (38% vs. 6%; d=0.90) and face overall (59% vs. 34%; d=0.41). In Study 2 (N=488), they were more likely to report low appearance evaluation (36% vs. 23%; d=-0.31) and were less likely to report high eye appearance satisfaction (59% vs. 88%; d=-0.84). The findings highlight the importance of considering ethnic differences when assessing body and face image. Copyright © 2016 Elsevier Ltd. All rights reserved.

Archetypal-Imaging and Mirror-Gazing

PubMed Central

Caputo, Giovanni B.

2013-01-01

Mirrors have been studied by cognitive psychology in order to understand self-recognition, self-identity, and self-consciousness. Moreover, the relevance of mirrors in spirituality, magic and arts may also suggest that mirrors can be symbols of unconscious contents. Carl G. Jung investigated mirrors in relation to the unconscious, particularly in Psychology and Alchemy. However, the relationship between the conscious behavior in front of a mirror and the unconscious meaning of mirrors has not been clarified. Recently, empirical research found that gazing at one’s own face in the mirror for a few minutes, at a low illumination level, produces the perception of bodily dysmorphic illusions of strange-faces. Healthy observers usually describe huge distortions of their own faces, monstrous beings, prototypical faces, faces of relatives and deceased, and faces of animals. In the psychiatric population, some schizophrenics show a dramatic increase of strange-face illusions. They can also describe the perception of multiple-others that fill the mirror surface surrounding their strange-face. Schizophrenics are usually convinced that strange-face illusions are truly real and identify themselves with strange-face illusions, diversely from healthy individuals who never identify with them. On the contrary, most patients with major depression do not perceive strange-face illusions, or they perceive very faint changes of their immobile faces in the mirror, like death statues. Strange-face illusions may be the psychodynamic projection of the subject’s unconscious archetypal contents into the mirror image. Therefore, strange-face illusions might provide both an ecological setting and an experimental technique for “imaging of the unconscious”. Future researches have been proposed. PMID:25379264

Archetypal-imaging and mirror-gazing.

PubMed

Caputo, Giovanni B

2014-03-01

Mirrors have been studied by cognitive psychology in order to understand self-recognition, self-identity, and self-consciousness. Moreover, the relevance of mirrors in spirituality, magic and arts may also suggest that mirrors can be symbols of unconscious contents. Carl G. Jung investigated mirrors in relation to the unconscious, particularly in Psychology and Alchemy. However, the relationship between the conscious behavior in front of a mirror and the unconscious meaning of mirrors has not been clarified. Recently, empirical research found that gazing at one's own face in the mirror for a few minutes, at a low illumination level, produces the perception of bodily dysmorphic illusions of strange-faces. Healthy observers usually describe huge distortions of their own faces, monstrous beings, prototypical faces, faces of relatives and deceased, and faces of animals. In the psychiatric population, some schizophrenics show a dramatic increase of strange-face illusions. They can also describe the perception of multiple-others that fill the mirror surface surrounding their strange-face. Schizophrenics are usually convinced that strange-face illusions are truly real and identify themselves with strange-face illusions, diversely from healthy individuals who never identify with them. On the contrary, most patients with major depression do not perceive strange-face illusions, or they perceive very faint changes of their immobile faces in the mirror, like death statues. Strange-face illusions may be the psychodynamic projection of the subject's unconscious archetypal contents into the mirror image. Therefore, strange-face illusions might provide both an ecological setting and an experimental technique for "imaging of the unconscious". Future researches have been proposed.

Foveation: an alternative method to simultaneously preserve privacy and information in face images

NASA Astrophysics Data System (ADS)

Alonso, Víctor E.; Enríquez-Caldera, Rogerio; Sucar, Luis Enrique

2017-03-01

This paper presents a real-time foveation technique proposed as an alternative method for image obfuscation while simultaneously preserving privacy in face deidentification. Relevance of the proposed technique is discussed through a comparative study of the most common distortions methods in face images and an assessment on performance and effectiveness of privacy protection. All the different techniques presented here are evaluated when they go through a face recognition software. Evaluating the data utility preservation was carried out under gender and facial expression classification. Results on quantifying the tradeoff between privacy protection and image information preservation at different obfuscation levels are presented. Comparative results using the facial expression subset of the FERET database show that the technique achieves a good tradeoff between privacy and awareness with 30% of recognition rate and a classification accuracy as high as 88% obtained from the common figures of merit using the privacy-awareness map.

Implementation of a high-speed face recognition system that uses an optical parallel correlator.

PubMed

Watanabe, Eriko; Kodate, Kashiko

2005-02-10

We implement a fully automatic fast face recognition system by using a 1000 frame/s optical parallel correlator designed and assembled by us. The operational speed for the 1:N (i.e., matching one image against N, where N refers to the number of images in the database) identification experiment (4000 face images) amounts to less than 1.5 s, including the preprocessing and postprocessing times. The binary real-only matched filter is devised for the sake of face recognition, and the system is optimized by the false-rejection rate (FRR) and the false-acceptance rate (FAR), according to 300 samples selected by the biometrics guideline. From trial 1:N identification experiments with the optical parallel correlator, we acquired low error rates of 2.6% FRR and 1.3% FAR. Facial images of people wearing thin glasses or heavy makeup that rendered identification difficult were identified with this system.

Visual imagery of famous faces: effects of memory and attention revealed by fMRI.

PubMed

Ishai, Alumit; Haxby, James V; Ungerleider, Leslie G

2002-12-01

Complex pictorial information can be represented and retrieved from memory as mental visual images. Functional brain imaging studies have shown that visual perception and visual imagery share common neural substrates. The type of memory (short- or long-term) that mediates the generation of mental images, however, has not been addressed previously. The purpose of this study was to investigate the neural correlates underlying imagery generated from short- and long-term memory (STM and LTM). We used famous faces to localize the visual response during perception and to compare the responses during visual imagery generated from STM (subjects memorized specific pictures of celebrities before the imagery task) and imagery from LTM (subjects imagined famous faces without seeing specific pictures during the experimental session). We found that visual perception of famous faces activated the inferior occipital gyri, lateral fusiform gyri, the superior temporal sulcus, and the amygdala. Small subsets of these face-selective regions were activated during imagery. Additionally, visual imagery of famous faces activated a network of regions composed of bilateral calcarine, hippocampus, precuneus, intraparietal sulcus (IPS), and the inferior frontal gyrus (IFG). In all these regions, imagery generated from STM evoked more activation than imagery from LTM. Regardless of memory type, focusing attention on features of the imagined faces (e.g., eyes, lips, or nose) resulted in increased activation in the right IPS and right IFG. Our results suggest differential effects of memory and attention during the generation and maintenance of mental images of faces.

Face identity matching is selectively impaired in developmental prosopagnosia.

PubMed

Fisher, Katie; Towler, John; Eimer, Martin

2017-04-01

Individuals with developmental prosopagnosia (DP) have severe face recognition deficits, but the mechanisms that are responsible for these deficits have not yet been fully identified. We assessed whether the activation of visual working memory for individual faces is selectively impaired in DP. Twelve DPs and twelve age-matched control participants were tested in a task where they reported whether successively presented faces showed the same or two different individuals, and another task where they judged whether the faces showed the same or different facial expressions. Repetitions versus changes of the other currently irrelevant attribute were varied independently. DPs showed impaired performance in the identity task, but performed at the same level as controls in the expression task. An electrophysiological marker for the activation of visual face memory by identity matches (N250r component) was strongly attenuated in the DP group, and the size of this attenuation was correlated with poor performance in a standardized face recognition test. Results demonstrate an identity-specific deficit of visual face memory in DPs. Their reduced sensitivity to identity matches in the presence of other image changes could result from earlier deficits in the perceptual extraction of image-invariant visual identity cues from face images. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Clustering Millions of Faces by Identity.

PubMed

Otto, Charles; Wang, Dayong; Jain, Anil K

2018-02-01

Given a large collection of unlabeled face images, we address the problem of clustering faces into an unknown number of identities. This problem is of interest in social media, law enforcement, and other applications, where the number of faces can be of the order of hundreds of million, while the number of identities (clusters) can range from a few thousand to millions. To address the challenges of run-time complexity and cluster quality, we present an approximate Rank-Order clustering algorithm that performs better than popular clustering algorithms (k-Means and Spectral). Our experiments include clustering up to 123 million face images into over 10 million clusters. Clustering results are analyzed in terms of external (known face labels) and internal (unknown face labels) quality measures, and run-time. Our algorithm achieves an F-measure of 0.87 on the LFW benchmark (13 K faces of 5,749 individuals), which drops to 0.27 on the largest dataset considered (13 K faces in LFW + 123M distractor images). Additionally, we show that frames in the YouTube benchmark can be clustered with an F-measure of 0.71. An internal per-cluster quality measure is developed to rank individual clusters for manual exploration of high quality clusters that are compact and isolated.

Face processing in different brain areas, and critical band masking.

PubMed

Rolls, Edmund T

2008-09-01

Neurophysiological evidence is described showing that some neurons in the macaque inferior temporal visual cortex have responses that are invariant with respect to the position, size, view, and spatial frequency of faces and objects, and that these neurons show rapid processing and rapid learning. Critical band spatial frequency masking is shown to be a property of these face-selective neurons and of the human visual perception of faces. Which face or object is present is encoded using a distributed representation in which each neuron conveys independent information in its firing rate, with little information evident in the relative time of firing of different neurons. This ensemble encoding has the advantages of maximizing the information in the representation useful for discrimination between stimuli using a simple weighted sum of the neuronal firing by the receiving neurons, generalization, and graceful degradation. These invariant representations are ideally suited to provide the inputs to brain regions such as the orbitofrontal cortex and amygdala that learn the reinforcement associations of an individual's face, for then the learning, and the appropriate social and emotional responses generalize to other views of the same face. A theory is described of how such invariant representations may be produced by self-organizing learning in a hierarchically organized set of visual cortical areas with convergent connectivity. The theory utilizes either temporal or spatial continuity with an associative synaptic modification rule. Another population of neurons in the cortex in the superior temporal sulcus encodes other aspects of faces such as face expression, eye-gaze, face view, and whether the head is moving. These neurons thus provide important additional inputs to parts of the brain such as the orbitofrontal cortex and amygdala that are involved in social communication and emotional behaviour. Outputs of these systems reach the amygdala, in which face-selective neurons are found, and also the orbitofrontal cortex, in which some neurons are tuned to face identity and others to face expression. In humans, activation of the orbitofrontal cortex is found when a change of face expression acts as a social signal that behaviour should change; and damage to the human orbitofrontal and pregenual cingulate cortex can impair face and voice expression identification, and also the reversal of emotional behaviour that normally occurs when reinforcers are reversed.

Automatic Boosted Flood Mapping from Satellite Data

NASA Technical Reports Server (NTRS)

Coltin, Brian; McMichael, Scott; Smith, Trey; Fong, Terrence

2016-01-01

Numerous algorithms have been proposed to map floods from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. However, most require human input to succeed, either to specify a threshold value or to manually annotate training data. We introduce a new algorithm based on Adaboost which effectively maps floods without any human input, allowing for a truly rapid and automatic response. The Adaboost algorithm combines multiple thresholds to achieve results comparable to state-of-the-art algorithms which do require human input. We evaluate Adaboost, as well as numerous previously proposed flood mapping algorithms, on multiple MODIS flood images, as well as on hundreds of non-flood MODIS lake images, demonstrating its effectiveness across a wide variety of conditions.

Discriminating Projections for Estimating Face Age in Wild Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tokola, Ryan A; Bolme, David S; Ricanek, Karl

2014-01-01

We introduce a novel approach to estimating the age of a human from a single uncontrolled image. Current face age estimation algorithms work well in highly controlled images, and some are robust to changes in illumination, but it is usually assumed that images are close to frontal. This bias is clearly seen in the datasets that are commonly used to evaluate age estimation, which either entirely or mostly consist of frontal images. Using pose-specific projections, our algorithm maps image features into a pose-insensitive latent space that is discriminative with respect to age. Age estimation is then performed using a multi-classmore » SVM. We show that our approach outperforms other published results on the Images of Groups dataset, which is the only age-related dataset with a non-trivial number of off-axis face images, and that we are competitive with recent age estimation algorithms on the mostly-frontal FG-NET dataset. We also experimentally demonstrate that our feature projections introduce insensitivity to pose.« less

Perceptual Asymmetries Are Preserved in Memory for Highly Familiar Faces of Self and Friend

ERIC Educational Resources Information Center

Brady, N.; Campbell, M.; Flaherty, M.

2005-01-01

We investigated the effect of familiarity on people's perception of facial likeness by asking participants to choose which of two mirror-symmetric chimeric images (made from the left or right half of a photograph of a face) looked more like an original image. In separate trials the participants made this judgment for their own face and for the…

Hybrid Speaker Recognition Using Universal Acoustic Model

NASA Astrophysics Data System (ADS)

Nishimura, Jun; Kuroda, Tadahiro

We propose a novel speaker recognition approach using a speaker-independent universal acoustic model (UAM) for sensornet applications. In sensornet applications such as “Business Microscope”, interactions among knowledge workers in an organization can be visualized by sensing face-to-face communication using wearable sensor nodes. In conventional studies, speakers are detected by comparing energy of input speech signals among the nodes. However, there are often synchronization errors among the nodes which degrade the speaker recognition performance. By focusing on property of the speaker's acoustic channel, UAM can provide robustness against the synchronization error. The overall speaker recognition accuracy is improved by combining UAM with the energy-based approach. For 0.1s speech inputs and 4 subjects, speaker recognition accuracy of 94% is achieved at the synchronization error less than 100ms.

The role of the right prefrontal cortex in self-evaluation of the face: a functional magnetic resonance imaging study.

PubMed

Morita, Tomoyo; Itakura, Shoji; Saito, Daisuke N; Nakashita, Satoshi; Harada, Tokiko; Kochiyama, Takanori; Sadato, Norihiro

2008-02-01

Individuals can experience negative emotions (e.g., embarrassment) accompanying self-evaluation immediately after recognizing their own facial image, especially if it deviates strongly from their mental representation of ideals or standards. The aim of this study was to identify the cortical regions involved in self-recognition and self-evaluation along with self-conscious emotions. To increase the range of emotions accompanying self-evaluation, we used facial feedback images chosen from a video recording, some of which deviated significantly from normal images. In total, 19 participants were asked to rate images of their own face (SELF) and those of others (OTHERS) according to how photogenic they appeared to be. After scanning the images, the participants rated how embarrassed they felt upon viewing each face. As the photogenic scores decreased, the embarrassment ratings dramatically increased for the participant's own face compared with those of others. The SELF versus OTHERS contrast significantly increased the activation of the right prefrontal cortex, bilateral insular cortex, anterior cingulate cortex, and bilateral occipital cortex. Within the right prefrontal cortex, activity in the right precentral gyrus reflected the trait of awareness of observable aspects of the self; this provided strong evidence that the right precentral gyrus is specifically involved in self-face recognition. By contrast, activity in the anterior region, which is located in the right middle inferior frontal gyrus, was modulated by the extent of embarrassment. This finding suggests that the right middle inferior frontal gyrus is engaged in self-evaluation preceded by self-face recognition based on the relevance to a standard self.

Quantitative Analysis of En Face Spectral-Domain Optical Coherence Tomography Imaging in Polypoidal Choroidal Vasculopathy.

PubMed

Simonett, Joseph M; Chan, Errol W; Chou, Jonathan; Skondra, Dimitra; Colon, Daniel; Chee, Caroline K; Lingam, Gopal; Fawzi, Amani A

2017-02-01

Spectral-domain optical coherence tomography (SD-OCT) imaging can be used to visualize polypoidal choroidal vasculopathy (PCV) lesions in the en face plane. Here, the authors describe a novel lesion quantification technique and compare PCV lesion area measurements and morphology before and after anti-vascular endothelial growth factor (VEGF) treatment. Volumetric SD-OCT scans in eyes with PCV before and after induction anti-VEGF therapy were retrospectively analyzed. En face SD-OCT images were generated and a pixel intensity thresholding process was used to quantify total lesion area. Thirteen eyes with PCV were analyzed. En face SD-OCT PCV lesion area quantification showed good intergrader reliability (intraclass correlation coefficient = 0.944). Total PCV lesion area was significantly reduced after anti-VEGF therapy (2.22 mm 2 vs. 2.73 mm 2 ; P = .02). The overall geographic pattern of the branching vascular network was typically preserved. PCV lesion area analysis using en face SD-OCT is a reproducible tool that can quantify treatment related changes. [Ophthalmic Surg Lasers Imaging Retina. 2017;48:126-133.]. Copyright 2017, SLACK Incorporated.

A 3D camera for improved facial recognition

NASA Astrophysics Data System (ADS)

Lewin, Andrew; Orchard, David A.; Scott, Andrew M.; Walton, Nicholas A.; Austin, Jim

2004-12-01

We describe a camera capable of recording 3D images of objects. It does this by projecting thousands of spots onto an object and then measuring the range to each spot by determining the parallax from a single frame. A second frame can be captured to record a conventional image, which can then be projected onto the surface mesh to form a rendered skin. The camera is able of locating the images of the spots to a precision of better than one tenth of a pixel, and from this it can determine range to an accuracy of less than 1 mm at 1 meter. The data can be recorded as a set of two images, and is reconstructed by forming a 'wire mesh' of range points and morphing the 2 D image over this structure. The camera can be used to record the images of faces and reconstruct the shape of the face, which allows viewing of the face from various angles. This allows images to be more critically inspected for the purpose of identifying individuals. Multiple images can be stitched together to create full panoramic images of head sized objects that can be viewed from any direction. The system is being tested with a graph matching system capable of fast and accurate shape comparisons for facial recognition. It can also be used with "models" of heads and faces to provide a means of obtaining biometric data.

A comparative study on generating simulated Landsat NDVI images using data fusion and regression method-the case of the Korean Peninsula.

PubMed

Lee, Mi Hee; Lee, Soo Bong; Eo, Yang Dam; Kim, Sun Woong; Woo, Jung-Hun; Han, Soo Hee

2017-07-01

Landsat optical images have enough spatial and spectral resolution to analyze vegetation growth characteristics. But, the clouds and water vapor degrade the image quality quite often, which limits the availability of usable images for the time series vegetation vitality measurement. To overcome this shortcoming, simulated images are used as an alternative. In this study, weighted average method, spatial and temporal adaptive reflectance fusion model (STARFM) method, and multilinear regression analysis method have been tested to produce simulated Landsat normalized difference vegetation index (NDVI) images of the Korean Peninsula. The test results showed that the weighted average method produced the images most similar to the actual images, provided that the images were available within 1 month before and after the target date. The STARFM method gives good results when the input image date is close to the target date. Careful regional and seasonal consideration is required in selecting input images. During summer season, due to clouds, it is very difficult to get the images close enough to the target date. Multilinear regression analysis gives meaningful results even when the input image date is not so close to the target date. Average R 2 values for weighted average method, STARFM, and multilinear regression analysis were 0.741, 0.70, and 0.61, respectively.

The occipital face area is causally involved in the formation of identity-specific face representations.

PubMed

Ambrus, Géza Gergely; Dotzer, Maria; Schweinberger, Stefan R; Kovács, Gyula

2017-12-01

Transcranial magnetic stimulation (TMS) and neuroimaging studies suggest a role of the right occipital face area (rOFA) in early facial feature processing. However, the degree to which rOFA is necessary for the encoding of facial identity has been less clear. Here we used a state-dependent TMS paradigm, where stimulation preferentially facilitates attributes encoded by less active neural populations, to investigate the role of the rOFA in face perception and specifically in image-independent identity processing. Participants performed a familiarity decision task for famous and unknown target faces, preceded by brief (200 ms) or longer (3500 ms) exposures to primes which were either an image of a different identity (DiffID), another image of the same identity (SameID), the same image (SameIMG), or a Fourier-randomized noise pattern (NOISE) while either the rOFA or the vertex as control was stimulated by single-pulse TMS. Strikingly, TMS to the rOFA eliminated the advantage of SameID over DiffID condition, thereby disrupting identity-specific priming, while leaving image-specific priming (better performance for SameIMG vs. SameID) unaffected. Our results suggest that the role of rOFA is not limited to low-level feature processing, and emphasize its role in image-independent facial identity processing and the formation of identity-specific memory traces.

Automatic Detection of Lung and Liver Lesions in 3-D Positron Emission Tomography Images: A Pilot Study

NASA Astrophysics Data System (ADS)

Lartizien, Carole; Marache-Francisco, Simon; Prost, Rémy

2012-02-01

Positron emission tomography (PET) using fluorine-18 deoxyglucose (18F-FDG) has become an increasingly recommended tool in clinical whole-body oncology imaging for the detection, diagnosis, and follow-up of many cancers. One way to improve the diagnostic utility of PET oncology imaging is to assist physicians facing difficult cases of residual or low-contrast lesions. This study aimed at evaluating different schemes of computer-aided detection (CADe) systems for the guided detection and localization of small and low-contrast lesions in PET. These systems are based on two supervised classifiers, linear discriminant analysis (LDA) and the nonlinear support vector machine (SVM). The image feature sets that serve as input data consisted of the coefficients of an undecimated wavelet transform. An optimization study was conducted to select the best combination of parameters for both the SVM and the LDA. Different false-positive reduction (FPR) methods were evaluated to reduce the number of false-positive detections per image (FPI). This includes the removal of small detected clusters and the combination of the LDA and SVM detection maps. The different CAD schemes were trained and evaluated based on a simulated whole-body PET image database containing 250 abnormal cases with 1230 lesions and 250 normal cases with no lesion. The detection performance was measured on a separate series of 25 testing images with 131 lesions. The combination of the LDA and SVM score maps was shown to produce very encouraging detection performance for both the lung lesions, with 91% sensitivity and 18 FPIs, and the liver lesions, with 94% sensitivity and 10 FPIs. Comparison with human performance indicated that the different CAD schemes significantly outperformed human detection sensitivities, especially regarding the low-contrast lesions.

Real-time edge-enhanced optical correlator

NASA Technical Reports Server (NTRS)

Liu, Tsuen-Hsi (Inventor); Cheng, Li-Jen (Inventor)

1992-01-01

Edge enhancement of an input image by four-wave mixing a first write beam with a second write beam in a photorefractive crystal, GaAs, was achieved for VanderLugt optical correlation with an edge enhanced reference image by optimizing the power ratio of a second write beam to the first write beam (70:1) and optimizing the power ratio of a read beam, which carries the reference image to the first write beam (100:701). Liquid crystal TV panels are employed as spatial light modulators to change the input and reference images in real time.

Stepped inlet optical panel

DOEpatents

Veligdan, James T.

2001-01-01

An optical panel includes stacked optical waveguides having stepped inlet facets collectively defining an inlet face for receiving image light, and having beveled outlet faces collectively defining a display screen for displaying the image light channeled through the waveguides by internal reflection.

Event-related potentials of self-face recognition in children with pervasive developmental disorders.

PubMed

Gunji, Atsuko; Inagaki, Masumi; Inoue, Yuki; Takeshima, Yasuyuki; Kaga, Makiko

2009-02-01

Patients with pervasive developmental disorders (PDD) often have difficulty reading facial expressions and deciphering their implied meaning. We focused on semantic encoding related to face cognition to investigate event-related potentials (ERPs) to the subject's own face and familiar faces in children with and without PDD. Eight children with PDD (seven boys and one girl; aged 10.8+/-2.9 years; one left-handed) and nine age-matched typically developing children (four boys and five girls; aged 11.3+/-2.3 years; one left-handed) participated in this study. The stimuli consisted of three face images (self, familiar, and unfamiliar faces), one scrambled face image, and one object image (e.g., cup) with gray scale. We confirmed three major components: N170 and early posterior negativity (EPN) in the occipito-temporal regions (T5 and T6) and P300 in the parietal region (Pz). An enhanced N170 was observed as a face-specific response in all subjects. However, semantic encoding of each face might be unrelated to N170 because the amplitude and latency were not significantly different among the face conditions. On the other hand, an additional component after N170, EPN which was calculated in each subtracted waveform (self vs. familiar and familiar vs. unfamiliar), indicated self-awareness and familiarity with respect to face cognition in the control adults and children. Furthermore, the P300 amplitude in the control adults was significantly greater in the self-face condition than in the familiar-face condition. However, no significant differences in the EPN and P300 components were observed among the self-, familiar-, and unfamiliar-face conditions in the PDD children. The results suggest a deficit of semantic encoding of faces in children with PDD, which may be implicated in their delay in social communication.

Interactive optical panel

DOEpatents

Veligdan, J.T.

1995-10-03

An interactive optical panel assembly includes an optical panel having a plurality of ribbon optical waveguides stacked together with opposite ends thereof defining panel first and second faces. A light source provides an image beam to the panel first face for being channeled through the waveguides and emitted from the panel second face in the form of a viewable light image. A remote device produces a response beam over a discrete selection area of the panel second face for being channeled through at least one of the waveguides toward the panel first face. A light sensor is disposed across a plurality of the waveguides for detecting the response beam therein for providing interactive capability. 10 figs.

Dynamic Photorefractive Memory and its Application for Opto-Electronic Neural Networks.

NASA Astrophysics Data System (ADS)

Sasaki, Hironori

This dissertation describes the analysis of the photorefractive crystal dynamics and its application for opto-electronic neural network systems. The realization of the dynamic photorefractive memory is investigated in terms of the following aspects: fast memory update, uniform grating multiplexing schedules and the prevention of the partial erasure of existing gratings. The fast memory update is realized by the selective erasure process that superimposes a new grating on the original one with an appropriate phase shift. The dynamics of the selective erasure process is analyzed using the first-order photorefractive material equations and experimentally confirmed. The effects of beam coupling and fringe bending on the selective erasure dynamics are also analyzed by numerically solving a combination of coupled wave equations and the photorefractive material equation. Incremental recording technique is proposed as a uniform grating multiplexing schedule and compared with the conventional scheduled recording technique in terms of phase distribution in the presence of an external dc electric field, as well as the image gray scale dependence. The theoretical analysis and experimental results proved the superiority of the incremental recording technique over the scheduled recording. Novel recirculating information memory architecture is proposed and experimentally demonstrated to prevent partial degradation of the existing gratings by accessing the memory. Gratings are circulated through a memory feed back loop based on the incremental recording dynamics and demonstrate robust read/write/erase capabilities. The dynamic photorefractive memory is applied to opto-electronic neural network systems. Module architecture based on the page-oriented dynamic photorefractive memory is proposed. This module architecture can implement two complementary interconnection organizations, fan-in and fan-out. The module system scalability and the learning capabilities are theoretically investigated using the photorefractive dynamics described in previous chapters of the dissertation. The implementation of the feed-forward image compression network with 900 input and 9 output neurons with 6-bit interconnection accuracy is experimentally demonstrated. Learning of the Perceptron network that determines sex based on input face images of 900 pixels is also successfully demonstrated.

Computer vision research with new imaging technology

NASA Astrophysics Data System (ADS)

Hou, Guangqi; Liu, Fei; Sun, Zhenan

2015-12-01

Light field imaging is capable of capturing dense multi-view 2D images in one snapshot, which record both intensity values and directions of rays simultaneously. As an emerging 3D device, the light field camera has been widely used in digital refocusing, depth estimation, stereoscopic display, etc. Traditional multi-view stereo (MVS) methods only perform well on strongly texture surfaces, but the depth map contains numerous holes and large ambiguities on textureless or low-textured regions. In this paper, we exploit the light field imaging technology on 3D face modeling in computer vision. Based on a 3D morphable model, we estimate the pose parameters from facial feature points. Then the depth map is estimated through the epipolar plane images (EPIs) method. At last, the high quality 3D face model is exactly recovered via the fusing strategy. We evaluate the effectiveness and robustness on face images captured by a light field camera with different poses.

Modified-hybrid optical neural network filter for multiple object recognition within cluttered scenes

NASA Astrophysics Data System (ADS)

Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.

2009-08-01

Motivated by the non-linear interpolation and generalization abilities of the hybrid optical neural network filter between the reference and non-reference images of the true-class object we designed the modifiedhybrid optical neural network filter. We applied an optical mask to the hybrid optical neural network's filter input. The mask was built with the constant weight connections of a randomly chosen image included in the training set. The resulted design of the modified-hybrid optical neural network filter is optimized for performing best in cluttered scenes of the true-class object. Due to the shift invariance properties inherited by its correlator unit the filter can accommodate multiple objects of the same class to be detected within an input cluttered image. Additionally, the architecture of the neural network unit of the general hybrid optical neural network filter allows the recognition of multiple objects of different classes within the input cluttered image by modifying the output layer of the unit. We test the modified-hybrid optical neural network filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. The filter is shown to exhibit with a single pass over the input data simultaneously out-of-plane rotation, shift invariance and good clutter tolerance. It is able to successfully detect and classify correctly the true-class objects within background clutter for which there has been no previous training.

Acute Solar Retinopathy Imaged With Adaptive Optics, Optical Coherence Tomography Angiography, and En Face Optical Coherence Tomography.

PubMed

Wu, Chris Y; Jansen, Michael E; Andrade, Jorge; Chui, Toco Y P; Do, Anna T; Rosen, Richard B; Deobhakta, Avnish

2018-01-01

Solar retinopathy is a rare form of retinal injury that occurs after direct sungazing. To enhance understanding of the structural changes that occur in solar retinopathy by obtaining high-resolution in vivo en face images. Case report of a young adult woman who presented to the New York Eye and Ear Infirmary with symptoms of acute solar retinopathy after viewing the solar eclipse on August 21, 2017. Results of comprehensive ophthalmic examination and images obtained by fundus photography, microperimetry, spectral-domain optical coherence tomography (OCT), adaptive optics scanning light ophthalmoscopy, OCT angiography, and en face OCT. The patient was examined after viewing the solar eclipse. Visual acuity was 20/20 OD and 20/25 OS. The patient was left-eye dominant. Spectral-domain OCT images were consistent with mild and severe acute solar retinopathy in the right and left eye, respectively. Microperimetry was normal in the right eye but showed paracentral decreased retinal sensitivity in the left eye with a central absolute scotoma. Adaptive optics images of the right eye showed a small region of nonwaveguiding photoreceptors, while images of the left eye showed a large area of abnormal and nonwaveguiding photoreceptors. Optical coherence tomography angiography images were normal in both eyes. En face OCT images of the right eye showed a small circular hyperreflective area, with central hyporeflectivity in the outer retina of the right eye. The left eye showed a hyperreflective lesion that intensified in area from inner to middle retina and became mostly hyporeflective in the outer retina. The shape of the lesion on adaptive optics and en face OCT images of the left eye corresponded to the shape of the scotoma drawn by the patient on Amsler grid. Acute solar retinopathy can present with foveal cone photoreceptor mosaic disturbances on adaptive optics scanning light ophthalmoscopy imaging. Corresponding reflectivity changes can be seen on en face OCT, especially in the middle and outer retina. Young adults may be especially vulnerable and need to be better informed of the risks of viewing the sun with inadequate protective eyewear.

False match elimination for face recognition based on SIFT algorithm

NASA Astrophysics Data System (ADS)

Gu, Xuyuan; Shi, Ping; Shao, Meide

2011-06-01

The SIFT (Scale Invariant Feature Transform) is a well known algorithm used to detect and describe local features in images. It is invariant to image scale, rotation and robust to the noise and illumination. In this paper, a novel method used for face recognition based on SIFT is proposed, which combines the optimization of SIFT, mutual matching and Progressive Sample Consensus (PROSAC) together and can eliminate the false matches of face recognition effectively. Experiments on ORL face database show that many false matches can be eliminated and better recognition rate is achieved.

Crossmodal Adaptation in Right Posterior Superior Temporal Sulcus during Face–Voice Emotional Integration

PubMed Central

Latinus, Marianne; Noguchi, Takao; Garrod, Oliver; Crabbe, Frances; Belin, Pascal

2014-01-01

The integration of emotional information from the face and voice of other persons is known to be mediated by a number of “multisensory” cerebral regions, such as the right posterior superior temporal sulcus (pSTS). However, whether multimodal integration in these regions is attributable to interleaved populations of unisensory neurons responding to face or voice or rather by multimodal neurons receiving input from the two modalities is not fully clear. Here, we examine this question using functional magnetic resonance adaptation and dynamic audiovisual stimuli in which emotional information was manipulated parametrically and independently in the face and voice via morphing between angry and happy expressions. Healthy human adult subjects were scanned while performing a happy/angry emotion categorization task on a series of such stimuli included in a fast event-related, continuous carryover design. Subjects integrated both face and voice information when categorizing emotion—although there was a greater weighting of face information—and showed behavioral adaptation effects both within and across modality. Adaptation also occurred at the neural level: in addition to modality-specific adaptation in visual and auditory cortices, we observed for the first time a crossmodal adaptation effect. Specifically, fMRI signal in the right pSTS was reduced in response to a stimulus in which facial emotion was similar to the vocal emotion of the preceding stimulus. These results suggest that the integration of emotional information from face and voice in the pSTS involves a detectable proportion of bimodal neurons that combine inputs from visual and auditory cortices. PMID:24828635

Local linear discriminant analysis framework using sample neighbors.

PubMed

Fan, Zizhu; Xu, Yong; Zhang, David

2011-07-01

The linear discriminant analysis (LDA) is a very popular linear feature extraction approach. The algorithms of LDA usually perform well under the following two assumptions. The first assumption is that the global data structure is consistent with the local data structure. The second assumption is that the input data classes are Gaussian distributions. However, in real-world applications, these assumptions are not always satisfied. In this paper, we propose an improved LDA framework, the local LDA (LLDA), which can perform well without needing to satisfy the above two assumptions. Our LLDA framework can effectively capture the local structure of samples. According to different types of local data structure, our LLDA framework incorporates several different forms of linear feature extraction approaches, such as the classical LDA and principal component analysis. The proposed framework includes two LLDA algorithms: a vector-based LLDA algorithm and a matrix-based LLDA (MLLDA) algorithm. MLLDA is directly applicable to image recognition, such as face recognition. Our algorithms need to train only a small portion of the whole training set before testing a sample. They are suitable for learning large-scale databases especially when the input data dimensions are very high and can achieve high classification accuracy. Extensive experiments show that the proposed algorithms can obtain good classification results.

The different faces of one’s self: an fMRI study into the recognition of current and past self-facial appearances

PubMed Central

Apps, Matthew A. J.; Tajadura-Jiménez, Ana; Turley, Grainne; Tsakiris, Manos

2013-01-01

Mirror self-recognition is often considered as an index of self-awareness. Neuroimaging studies have identified a neural circuit specialised for the recognition of one’s own current facial appearance. However, faces change considerably over a lifespan, highlighting the necessity for representations of one’s face to continually be updated. We used fMRI to investigate the different neural circuits involved in the recognition of the childhood and current, adult, faces of one’s self. Participants viewed images of either their own face as it currently looks morphed with the face of a familiar other or their childhood face morphed with the childhood face of the familiar other. Activity in areas which have a generalised selectivity for faces, including the inferior occipital gyrus, the superior parietal lobule and the inferior temporal gyrus, varied with the amount of current self in an image. Activity in areas involved in memory encoding and retrieval, including the hippocampus and the posterior cingulate gyrus, and areas involved in creating a sense of body ownership, including the temporo-parietal junction and the inferior parietal lobule, varied with the amount of childhood self in an image. We suggest that the recognition of one’s own past or present face is underpinned by different cognitive processes in distinct neural circuits. Current self-recognition engages areas involved in perceptual face processing, whereas childhood self-recognition recruits networks involved in body ownership and memory processing. PMID:22940117

The different faces of one's self: an fMRI study into the recognition of current and past self-facial appearances.

PubMed

Apps, Matthew A J; Tajadura-Jiménez, Ana; Turley, Grainne; Tsakiris, Manos

2012-11-15

Mirror self-recognition is often considered as an index of self-awareness. Neuroimaging studies have identified a neural circuit specialised for the recognition of one's own current facial appearance. However, faces change considerably over a lifespan, highlighting the necessity for representations of one's face to continually be updated. We used fMRI to investigate the different neural circuits involved in the recognition of the childhood and current, adult, faces of one's self. Participants viewed images of either their own face as it currently looks morphed with the face of a familiar other or their childhood face morphed with the childhood face of the familiar other. Activity in areas which have a generalised selectivity for faces, including the inferior occipital gyrus, the superior parietal lobule and the inferior temporal gyrus, varied with the amount of current self in an image. Activity in areas involved in memory encoding and retrieval, including the hippocampus and the posterior cingulate gyrus, and areas involved in creating a sense of body ownership, including the temporo-parietal junction and the inferior parietal lobule, varied with the amount of childhood self in an image. We suggest that the recognition of one's own past or present face is underpinned by different cognitive processes in distinct neural circuits. Current self-recognition engages areas involved in perceptual face processing, whereas childhood self-recognition recruits networks involved in body ownership and memory processing. Copyright © 2012 Elsevier Inc. All rights reserved.

Iterative pixelwise approach applied to computer-generated holograms and diffractive optical elements.

PubMed

Hsu, Wei-Feng; Lin, Shih-Chih

2018-01-01

This paper presents a novel approach to optimizing the design of phase-only computer-generated holograms (CGH) for the creation of binary images in an optical Fourier transform system. Optimization begins by selecting an image pixel with a temporal change in amplitude. The modulated image function undergoes an inverse Fourier transform followed by the imposition of a CGH constraint and the Fourier transform to yield an image function associated with the change in amplitude of the selected pixel. In iterations where the quality of the image is improved, that image function is adopted as the input for the next iteration. In cases where the image quality is not improved, the image function before the pixel changed is used as the input. Thus, the proposed approach is referred to as the pixelwise hybrid input-output (PHIO) algorithm. The PHIO algorithm was shown to achieve image quality far exceeding that of the Gerchberg-Saxton (GS) algorithm. The benefits were particularly evident when the PHIO algorithm was equipped with a dynamic range of image intensities equivalent to the amplitude freedom of the image signal. The signal variation of images reconstructed from the GS algorithm was 1.0223, but only 0.2537 when using PHIO, i.e., a 75% improvement. Nonetheless, the proposed scheme resulted in a 10% degradation in diffraction efficiency and signal-to-noise ratio.

Cross sectional: perception of children from public and private schools regarding the esthetic impact of different types of face masks.

PubMed

Pithon, Matheus Melo; Ferraz, Caio Sousa; de Oliveira, Gabriel Couto; Dos Santos, Adrielle Mangabeira; Couto, Felipe Santos; da Silva Coqueiro, Raildo; Dos Santos, Rogério Lacerda

2013-01-01

The purpose was to evaluate the esthetic perception among children from public and private schools regarding the use of different types of face masks. Six different types of orthopedic face masks made from images of the same patient were evaluated. Initially, the images were standardized with the help of Adobe Photoshop software. The variable considered was type of mask: (A) Delaire with facebow; (B) Petit; (C) Delaire; (D)Turley; (E) Hickham; and (F) Sky Hook. The images were printed on photographic paper and incorporated into a specific personalized questionnaire that was distributed to 7- to 10-year-olds attending public and private schools (n=120). The data obtained were compared via chi-square, Fisher's exact tests, Mann-Whitney and Spearman's tests. The proportion of participants who chose image A as the best was significantly higher (P<.05) compared to the other masks. Images B and F were chosen as the worst, without a significant difference between them (P>.05). The mean scores between groups were not significantly correlated between private vs public schoolchildren (r=0.32) and between boys and girls (r=0.41). Delaire face mask with facebow was chosen as the most attractive, and the Petit and Sky Hook face masks were voted the least attractive.

Locating faces in color photographs using neural networks

NASA Astrophysics Data System (ADS)

Brown, Joe R.; Talley, Jim

1994-03-01

This paper summarizes a research effort in finding the locations and sizes of faces in color images (photographs, video stills, etc.) if, in fact, faces are presented. Scenarios for using such a system include serving as the means of localizing skin for automatic color balancing during photo processing or it could be used as a front-end in a customs port of energy context for a system which identified persona non grata given a database of known faces. The approach presented here is a hybrid system including: a neural pre-processor, some conventional image processing steps, and a neural classifier as the final face/non-face discriminator. Neither the training (containing 17,655 faces) nor the test (containing 1829 faces) imagery databases were constrained in their content or quality. The results for the pilot system are reported along with a discussion for improving the current system.

Distance Metric Learning Using Privileged Information for Face Verification and Person Re-Identification.

PubMed

Xu, Xinxing; Li, Wen; Xu, Dong

2015-12-01

In this paper, we propose a new approach to improve face verification and person re-identification in the RGB images by leveraging a set of RGB-D data, in which we have additional depth images in the training data captured using depth cameras such as Kinect. In particular, we extract visual features and depth features from the RGB images and depth images, respectively. As the depth features are available only in the training data, we treat the depth features as privileged information, and we formulate this task as a distance metric learning with privileged information problem. Unlike the traditional face verification and person re-identification tasks that only use visual features, we further employ the extra depth features in the training data to improve the learning of distance metric in the training process. Based on the information-theoretic metric learning (ITML) method, we propose a new formulation called ITML with privileged information (ITML+) for this task. We also present an efficient algorithm based on the cyclic projection method for solving the proposed ITML+ formulation. Extensive experiments on the challenging faces data sets EUROCOM and CurtinFaces for face verification as well as the BIWI RGBD-ID data set for person re-identification demonstrate the effectiveness of our proposed approach.

Faces forming traces: neurophysiological correlates of learning naturally distinctive and caricatured faces.

PubMed

Schulz, Claudia; Kaufmann, Jürgen M; Kurt, Alexander; Schweinberger, Stefan R

2012-10-15

Distinctive faces are easier to learn and recognise than typical faces. We investigated effects of natural vs. artificial distinctiveness on performance and neural correlates of face learning. Spatial caricatures of initially non-distinctive faces were created such that their rated distinctiveness matched a set of naturally distinctive faces. During learning, we presented naturally distinctive, caricatured, and non-distinctive faces for later recognition among novel faces, using different images of the same identities at learning and test. For learned faces, an advantage in performance was observed for naturally distinctive and caricatured over non-distinctive faces, with larger benefits for naturally distinctive faces. Distinctive and caricatured faces elicited more negative occipitotemporal ERPs (P200, N250) and larger centroparietal positivity (LPC) during learning. At test, earliest distinctiveness effects were again seen in the P200. In line with recent research, N250 and LPC were larger for learned than for novel faces overall. Importantly, whereas left hemispheric N250 was increased for learned naturally distinctive faces, right hemispheric N250 responded particularly to caricatured novel faces. We conclude that natural distinctiveness induces benefits to face recognition beyond those induced by exaggeration of a face's idiosyncratic shape, and that the left hemisphere in particular may mediate recognition across different images. Copyright © 2012 Elsevier Inc. All rights reserved.

Pre-Flight Radiometric Model of Linear Imager on LAPAN-IPB Satellite

NASA Astrophysics Data System (ADS)

Hadi Syafrudin, A.; Salaswati, Sartika; Hasbi, Wahyudi

2018-05-01

LAPAN-IPB Satellite is Microsatellite class with mission of remote sensing experiment. This satellite carrying Multispectral Line Imager for captured of radiometric reflectance value from earth to space. Radiometric quality of image is important factor to classification object on remote sensing process. Before satellite launch in orbit or pre-flight, Line Imager have been tested by Monochromator and integrating sphere to get spectral and every pixel radiometric response characteristic. Pre-flight test data with variety setting of line imager instrument used to see correlation radiance input and digital number of images output. Output input correlation is described by the radiance conversion model with imager setting and radiometric characteristics. Modelling process from hardware level until normalize radiance formula are presented and discussed in this paper.

DaCHS: Data Center Helper Suite

NASA Astrophysics Data System (ADS)

Demleitner, Markus

2018-04-01

DaCHS, the Data Center Helper Suite, is an integrated package for publishing astronomical data sets to the Virtual Observatory. Network-facing, it speaks the major VO protocols (SCS, SIAP, SSAP, TAP, Datalink, etc). Operator-facing, many input formats, including FITS/WCS, ASCII files, and VOTable, can be processed to publication-ready data. DaCHS puts particular emphasis on integrated metadata handling, which facilitates a tight integration with the VO's Registry

A study on facial expressions recognition

NASA Astrophysics Data System (ADS)

Xu, Jingjing

2017-09-01

In terms of communication, postures and facial expressions of such feelings like happiness, anger and sadness play important roles in conveying information. With the development of the technology, recently a number of algorithms dealing with face alignment, face landmark detection, classification, facial landmark localization and pose estimation have been put forward. However, there are a lot of challenges and problems need to be fixed. In this paper, a few technologies have been concluded and analyzed, and they all relate to handling facial expressions recognition and poses like pose-indexed based multi-view method for face alignment, robust facial landmark detection under significant head pose and occlusion, partitioning the input domain for classification, robust statistics face formalization.

Neural network diagnosis of avascular necrosis from magnetic resonance images

NASA Astrophysics Data System (ADS)

Manduca, Armando; Christy, Paul S.; Ehman, Richard L.

1993-09-01

We have explored the use of artificial neural networks to diagnose avascular necrosis (AVN) of the femoral head from magnetic resonance images. We have developed multi-layer perceptron networks, trained with conjugate gradient optimization, which diagnose AVN from single sagittal images of the femoral head with 100% accuracy on the training data and 97% accuracy on test data. These networks use only the raw image as input (with minimal preprocessing to average the images down to 32 X 32 size and to scale the input data values) and learn to extract their own features for the diagnosis decision. Various experiments with these networks are described.

Image Display and Manipulation System (IDAMS) program documentation, Appendixes A-D. [including routines, convolution filtering, image expansion, and fast Fourier transformation

NASA Technical Reports Server (NTRS)

Cecil, R. W.; White, R. A.; Szczur, M. R.

1972-01-01

The IDAMS Processor is a package of task routines and support software that performs convolution filtering, image expansion, fast Fourier transformation, and other operations on a digital image tape. A unique task control card for that program, together with any necessary parameter cards, selects each processing technique to be applied to the input image. A variable number of tasks can be selected for execution by including the proper task and parameter cards in the input deck. An executive maintains control of the run; it initiates execution of each task in turn and handles any necessary error processing.

Implementation of an RBF neural network on embedded systems: real-time face tracking and identity verification.

PubMed

Yang, Fan; Paindavoine, M

2003-01-01

This paper describes a real time vision system that allows us to localize faces in video sequences and verify their identity. These processes are image processing techniques based on the radial basis function (RBF) neural network approach. The robustness of this system has been evaluated quantitatively on eight video sequences. We have adapted our model for an application of face recognition using the Olivetti Research Laboratory (ORL), Cambridge, UK, database so as to compare the performance against other systems. We also describe three hardware implementations of our model on embedded systems based on the field programmable gate array (FPGA), zero instruction set computer (ZISC) chips, and digital signal processor (DSP) TMS320C62, respectively. We analyze the algorithm complexity and present results of hardware implementations in terms of the resources used and processing speed. The success rates of face tracking and identity verification are 92% (FPGA), 85% (ZISC), and 98.2% (DSP), respectively. For the three embedded systems, the processing speeds for images size of 288 /spl times/ 352 are 14 images/s, 25 images/s, and 4.8 images/s, respectively.

The utility of multiple synthesized views in the recognition of unfamiliar faces.

PubMed

Jones, Scott P; Dwyer, Dominic M; Lewis, Michael B

2017-05-01

The ability to recognize an unfamiliar individual on the basis of prior exposure to a photograph is notoriously poor and prone to errors, but recognition accuracy is improved when multiple photographs are available. In applied situations, when only limited real images are available (e.g., from a mugshot or CCTV image), the generation of new images might provide a technological prosthesis for otherwise fallible human recognition. We report two experiments examining the effects of providing computer-generated additional views of a target face. In Experiment 1, provision of computer-generated views supported better target face recognition than exposure to the target image alone and equivalent performance to that for exposure of multiple photograph views. Experiment 2 replicated the advantage of providing generated views, but also indicated an advantage for multiple viewings of the single target photograph. These results strengthen the claim that identifying a target face can be improved by providing multiple synthesized views based on a single target image. In addition, our results suggest that the degree of advantage provided by synthesized views may be affected by the quality of synthesized material.

Detection and segmentation of multiple touching product inspection items

NASA Astrophysics Data System (ADS)

Casasent, David P.; Talukder, Ashit; Cox, Westley; Chang, Hsuan-Ting; Weber, David

1996-12-01

X-ray images of pistachio nuts on conveyor trays for product inspection are considered. The first step in such a processor is to locate each individual item and place it in a separate file for input to a classifier to determine the quality of each nut. This paper considers new techniques to: detect each item (each nut can be in any orientation, we employ new rotation-invariant filters to locate each item independent of its orientation), produce separate image files for each item [a new blob coloring algorithm provides this for isolated (non-touching) input items], segmentation to provide separate image files for touching or overlapping input items (we use a morphological watershed transform to achieve this), and morphological processing to remove the shell and produce an image of only the nutmeat. Each of these operations and algorithms are detailed and quantitative data for each are presented for the x-ray image nut inspection problem noted. These techniques are of general use in many different product inspection problems in agriculture and other areas.

Expertise with unfamiliar objects is flexible to changes in task but not changes in class

PubMed Central

Tangen, Jason M.

2017-01-01

Perceptual expertise is notoriously specific and bound by familiarity; generalizing to novel or unfamiliar images, objects, identities, and categories often comes at some cost to performance. In forensic and security settings, however, examiners are faced with the task of discriminating unfamiliar images of unfamiliar objects within their general domain of expertise (e.g., fingerprints, faces, or firearms). The job of a fingerprint expert, for instance, is to decide whether two unfamiliar fingerprint images were left by the same unfamiliar finger (e.g., Smith’s left thumb), or two different unfamiliar fingers (e.g., Smith and Jones’s left thumb). Little is known about the limits of this kind of perceptual expertise. Here, we examine fingerprint experts’ and novices’ ability to distinguish fingerprints compared to inverted faces in two different tasks. Inverted face images serve as an ideal comparison because they vary naturally between and within identities, as do fingerprints, and people tend to be less accurate or more novice-like at distinguishing faces when they are presented in an inverted or unfamiliar orientation. In Experiment 1, fingerprint experts outperformed novices in locating categorical fingerprint outliers (i.e., a loop pattern in an array of whorls), but not inverted face outliers (i.e., an inverted male face in an array of inverted female faces). In Experiment 2, fingerprint experts were more accurate than novices at discriminating matching and mismatching fingerprints that were presented very briefly, but not so for inverted faces. Our data show that perceptual expertise with fingerprints can be flexible to changing task demands, but there can also be abrupt limits: fingerprint expertise did not generalize to an unfamiliar class of stimuli. We interpret these findings as evidence that perceptual expertise with unfamiliar objects is highly constrained by one’s experience. PMID:28574998

Self-compassion in the face of shame and body image dissatisfaction: implications for eating disorders.

PubMed

Ferreira, Cláudia; Pinto-Gouveia, José; Duarte, Cristiana

2013-04-01

The current study examines the role of self-compassion in face of shame and body image dissatisfaction, in 102 female eating disorders' patients, and 123 women from general population. Self-compassion was negatively associated with external shame, general psychopathology, and eating disorders' symptomatology. In women from the general population increased external shame predicted drive for thinness partially through lower self-compassion; also, body image dissatisfaction directly predicted drive for thinness. However, in the patients' sample increased shame and body image dissatisfaction predicted increased drive for thinness through decreased self-compassion. These results highlight the importance of the affiliative emotion dimensions of self-compassion in face of external shame, body image dissatisfaction and drive for thinness, emphasising the relevance of cultivating a self-compassionate relationship in eating disorders' patients. Copyright © 2013. Published by Elsevier Ltd.

The Other-Race Effect Develops During Infancy

PubMed Central

Quinn, Paul C.; Slater, Alan M.; Lee, Kang; Ge, Liezhong; Pascalis, Olivier

2008-01-01

Experience plays a crucial role in the development of face processing. In the study reported here, we investigated how faces observed within the visual environment affect the development of the face-processing system during the 1st year of life. We assessed 3-, 6-, and 9-month-old Caucasian infants' ability to discriminate faces within their own racial group and within three other-race groups (African, Middle Eastern, and Chinese). The 3-month-old infants demonstrated recognition in all conditions, the 6-month-old infants were able to recognize Caucasian and Chinese faces only, and the 9-month-old infants' recognition was restricted to own-race faces. The pattern of preferences indicates that the other-race effect is emerging by 6 months of age and is present at 9 months of age. The findings suggest that facial input from the infant's visual environment is crucial for shaping the face-processing system early in infancy, resulting in differential recognition accuracy for faces of different races in adulthood. PMID:18031416

Neuronal integration in visual cortex elevates face category tuning to conscious face perception

PubMed Central

Fahrenfort, Johannes J.; Snijders, Tineke M.; Heinen, Klaartje; van Gaal, Simon; Scholte, H. Steven; Lamme, Victor A. F.

2012-01-01

The human brain has the extraordinary capability to transform cluttered sensory input into distinct object representations. For example, it is able to rapidly and seemingly without effort detect object categories in complex natural scenes. Surprisingly, category tuning is not sufficient to achieve conscious recognition of objects. What neural process beyond category extraction might elevate neural representations to the level where objects are consciously perceived? Here we show that visible and invisible faces produce similar category-selective responses in the ventral visual cortex. The pattern of neural activity evoked by visible faces could be used to decode the presence of invisible faces and vice versa. However, only visible faces caused extensive response enhancements and changes in neural oscillatory synchronization, as well as increased functional connectivity between higher and lower visual areas. We conclude that conscious face perception is more tightly linked to neural processes of sustained information integration and binding than to processes accommodating face category tuning. PMID:23236162

Consumer perceptions on sustainable practices implemented in foodservice organizations in Korea

PubMed Central

Ju, Seyoung

2016-01-01

BACKGROUND/OBJECTIVES Sustainable practices in foodservice organizations including commercial and noncommercial ones are critical to ensure the protection of the environment for the future. With the rapid growth of the foodservice industry, wiser usage of input sources such as food, utilities, and single use packaging should be reconsidered for future generations. Therefore, this study aims to investigate the customer's perceptions on sustainable practices and to identify the relationship among sustainable practices, social contribution and purchase intention. SUBJECTS/METHODS The study was conducted using content analyses by reviewing articles on sustainable food service practices published domestically and abroad. Thereafter, data were collected with a face-to-face survey using a questionnaire and analyzed with factor analyses and multiple regressions. RESULTS Sustainable practices classified with factor analysis consisted of 6 dimensions of green food material procurement, sustainable food preparation, green packaging, preservation of energy, waste management, and public relations on green activity, with a total of 25 green activities in foodservice operations. Consumers were not very familiar with the green activities implemented in the foodservice unit, with the lowest awareness of "green food material procurement (2.46 out of 5 points)", and the highest awareness of "green packaging (3.74)" and "waste management (3.28). The factors influencing the perception of social contribution by foodservice organizations among 6 sustainable practice dimensions were found to be public relations on green activity (β = 0.154), waste management (β = 0.204) and sustainable food preparation (β = 0.183). Green packaging (β = 0.107) and the social contribution of the foodservice organization (β = 0.761) had strong relationships with the image of the organization. The purchase intentions of customers was affected only by the foodservice image (β = 0.775). CONCLUSIONS The results of this study suggest that sustainable practices by foodservice organization present a good image to customers and increase the awareness of valuable contributions that benefit the customer as well as the community. PMID:26865923

Consumer perceptions on sustainable practices implemented in foodservice organizations in Korea.

PubMed

Ju, Seyoung; Chang, Hyeja

2016-02-01

Sustainable practices in foodservice organizations including commercial and noncommercial ones are critical to ensure the protection of the environment for the future. With the rapid growth of the foodservice industry, wiser usage of input sources such as food, utilities, and single use packaging should be reconsidered for future generations. Therefore, this study aims to investigate the customer's perceptions on sustainable practices and to identify the relationship among sustainable practices, social contribution and purchase intention. The study was conducted using content analyses by reviewing articles on sustainable food service practices published domestically and abroad. Thereafter, data were collected with a face-to-face survey using a questionnaire and analyzed with factor analyses and multiple regressions. Sustainable practices classified with factor analysis consisted of 6 dimensions of green food material procurement, sustainable food preparation, green packaging, preservation of energy, waste management, and public relations on green activity, with a total of 25 green activities in foodservice operations. Consumers were not very familiar with the green activities implemented in the foodservice unit, with the lowest awareness of "green food material procurement (2.46 out of 5 points)", and the highest awareness of "green packaging (3.74)" and "waste management (3.28). The factors influencing the perception of social contribution by foodservice organizations among 6 sustainable practice dimensions were found to be public relations on green activity (β = 0.154), waste management (β = 0.204) and sustainable food preparation (β = 0.183). Green packaging (β = 0.107) and the social contribution of the foodservice organization (β = 0.761) had strong relationships with the image of the organization. The purchase intentions of customers was affected only by the foodservice image (β = 0.775). The results of this study suggest that sustainable practices by foodservice organization present a good image to customers and increase the awareness of valuable contributions that benefit the customer as well as the community.

Deep Learning-Based Banknote Fitness Classification Using the Reflection Images by a Visible-Light One-Dimensional Line Image Sensor

PubMed Central

Pham, Tuyen Danh; Nguyen, Dat Tien; Kim, Wan; Park, Sung Ho; Park, Kang Ryoung

2018-01-01

In automatic paper currency sorting, fitness classification is a technique that assesses the quality of banknotes to determine whether a banknote is suitable for recirculation or should be replaced. Studies on using visible-light reflection images of banknotes for evaluating their usability have been reported. However, most of them were conducted under the assumption that the denomination and input direction of the banknote are predetermined. In other words, a pre-classification of the type of input banknote is required. To address this problem, we proposed a deep learning-based fitness-classification method that recognizes the fitness level of a banknote regardless of the denomination and input direction of the banknote to the system, using the reflection images of banknotes by visible-light one-dimensional line image sensor and a convolutional neural network (CNN). Experimental results on the banknote image databases of the Korean won (KRW) and the Indian rupee (INR) with three fitness levels, and the Unites States dollar (USD) with two fitness levels, showed that our method gives better classification accuracy than other methods. PMID:29415447

SPM analysis of parametric (R)-[11C]PK11195 binding images: plasma input versus reference tissue parametric methods.

PubMed

Schuitemaker, Alie; van Berckel, Bart N M; Kropholler, Marc A; Veltman, Dick J; Scheltens, Philip; Jonker, Cees; Lammertsma, Adriaan A; Boellaard, Ronald

2007-05-01

(R)-[11C]PK11195 has been used for quantifying cerebral microglial activation in vivo. In previous studies, both plasma input and reference tissue methods have been used, usually in combination with a region of interest (ROI) approach. Definition of ROIs, however, can be labourious and prone to interobserver variation. In addition, results are only obtained for predefined areas and (unexpected) signals in undefined areas may be missed. On the other hand, standard pharmacokinetic models are too sensitive to noise to calculate (R)-[11C]PK11195 binding on a voxel-by-voxel basis. Linearised versions of both plasma input and reference tissue models have been described, and these are more suitable for parametric imaging. The purpose of this study was to compare the performance of these plasma input and reference tissue parametric methods on the outcome of statistical parametric mapping (SPM) analysis of (R)-[11C]PK11195 binding. Dynamic (R)-[11C]PK11195 PET scans with arterial blood sampling were performed in 7 younger and 11 elderly healthy subjects. Parametric images of volume of distribution (Vd) and binding potential (BP) were generated using linearised versions of plasma input (Logan) and reference tissue (Reference Parametric Mapping) models. Images were compared at the group level using SPM with a two-sample t-test per voxel, both with and without proportional scaling. Parametric BP images without scaling provided the most sensitive framework for determining differences in (R)-[11C]PK11195 binding between younger and elderly subjects. Vd images could only demonstrate differences in (R)-[11C]PK11195 binding when analysed with proportional scaling due to intersubject variation in K1/k2 (blood-brain barrier transport and non-specific binding).

Expectations about person identity modulate the face-sensitive N170.

PubMed

Johnston, Patrick; Overell, Anne; Kaufman, Jordy; Robinson, Jonathan; Young, Andrew W

2016-12-01

Identifying familiar faces is a fundamentally important aspect of social perception that requires the ability to assign very different (ambient) images of a face to a common identity. The current consensus is that the brain processes face identity at approximately 250-300 msec following stimulus onset, as indexed by the N250 event related potential. However, using two experiments we show compelling evidence that where experimental paradigms induce expectations about person identity, changes in famous face identity are in fact detected at an earlier latency corresponding to the face-sensitive N170. In Experiment 1, using a rapid periodic stimulation paradigm presenting highly variable ambient images, we demonstrate robust effects of low frequency, periodic face-identity changes in N170 amplitude. In Experiment 2, we added infrequent aperiodic identity changes to show that the N170 was larger to both infrequent periodic and infrequent aperiodic identity changes than to high frequency identities. Our use of ambient stimulus images makes it unlikely that these effects are due to adaptation of low-level stimulus features. In line with current ideas about predictive coding, we therefore suggest that when expectations about the identity of a face exist, the visual system is capable of detecting identity mismatches at a latency consistent with the N170. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multi-Directional Multi-Level Dual-Cross Patterns for Robust Face Recognition.

PubMed

Ding, Changxing; Choi, Jonghyun; Tao, Dacheng; Davis, Larry S

2016-03-01

To perform unconstrained face recognition robust to variations in illumination, pose and expression, this paper presents a new scheme to extract "Multi-Directional Multi-Level Dual-Cross Patterns" (MDML-DCPs) from face images. Specifically, the MDML-DCPs scheme exploits the first derivative of Gaussian operator to reduce the impact of differences in illumination and then computes the DCP feature at both the holistic and component levels. DCP is a novel face image descriptor inspired by the unique textural structure of human faces. It is computationally efficient and only doubles the cost of computing local binary patterns, yet is extremely robust to pose and expression variations. MDML-DCPs comprehensively yet efficiently encodes the invariant characteristics of a face image from multiple levels into patterns that are highly discriminative of inter-personal differences but robust to intra-personal variations. Experimental results on the FERET, CAS-PERL-R1, FRGC 2.0, and LFW databases indicate that DCP outperforms the state-of-the-art local descriptors (e.g., LBP, LTP, LPQ, POEM, tLBP, and LGXP) for both face identification and face verification tasks. More impressively, the best performance is achieved on the challenging LFW and FRGC 2.0 databases by deploying MDML-DCPs in a simple recognition scheme.

The importance of internal facial features in learning new faces.

PubMed

Longmore, Christopher A; Liu, Chang Hong; Young, Andrew W

2015-01-01

For familiar faces, the internal features (eyes, nose, and mouth) are known to be differentially salient for recognition compared to external features such as hairstyle. Two experiments are reported that investigate how this internal feature advantage accrues as a face becomes familiar. In Experiment 1, we tested the contribution of internal and external features to the ability to generalize from a single studied photograph to different views of the same face. A recognition advantage for the internal features over the external features was found after a change of viewpoint, whereas there was no internal feature advantage when the same image was used at study and test. In Experiment 2, we removed the most salient external feature (hairstyle) from studied photographs and looked at how this affected generalization to a novel viewpoint. Removing the hair from images of the face assisted generalization to novel viewpoints, and this was especially the case when photographs showing more than one viewpoint were studied. The results suggest that the internal features play an important role in the generalization between different images of an individual's face by enabling the viewer to detect the common identity-diagnostic elements across non-identical instances of the face.

Reference frames for spatial frequency in face representation differ in the temporal visual cortex and amygdala.

PubMed

Inagaki, Mikio; Fujita, Ichiro

2011-07-13

Social communication in nonhuman primates and humans is strongly affected by facial information from other individuals. Many cortical and subcortical brain areas are known to be involved in processing facial information. However, how the neural representation of faces differs across different brain areas remains unclear. Here, we demonstrate that the reference frame for spatial frequency (SF) tuning of face-responsive neurons differs in the temporal visual cortex and amygdala in monkeys. Consistent with psychophysical properties for face recognition, temporal cortex neurons were tuned to image-based SFs (cycles/image) and showed viewing distance-invariant representation of face patterns. On the other hand, many amygdala neurons were influenced by retina-based SFs (cycles/degree), a characteristic that is useful for social distance computation. The two brain areas also differed in the luminance contrast sensitivity of face-responsive neurons; amygdala neurons sharply reduced their responses to low luminance contrast images, while temporal cortex neurons maintained the level of their responses. From these results, we conclude that different types of visual processing in the temporal visual cortex and the amygdala contribute to the construction of the neural representations of faces.

Phase and amplitude beam shaping with two deformable mirrors implementing input plane and Fourier plane phase modifications.

PubMed

Wu, Chensheng; Ko, Jonathan; Rzasa, John R; Paulson, Daniel A; Davis, Christopher C

2018-03-20

We find that ideas in optical image encryption can be very useful for adaptive optics in achieving simultaneous phase and amplitude shaping of a laser beam. An adaptive optics system with simultaneous phase and amplitude shaping ability is very desirable for atmospheric turbulence compensation. Atmospheric turbulence-induced beam distortions can jeopardize the effectiveness of optical power delivery for directed-energy systems and optical information delivery for free-space optical communication systems. In this paper, a prototype adaptive optics system is proposed based on a famous image encryption structure. The major change is to replace the two random phase plates at the input plane and Fourier plane of the encryption system, respectively, with two deformable mirrors that perform on-demand phase modulations. A Gaussian beam is used as an input to replace the conventional image input. We show through theory, simulation, and experiments that the slightly modified image encryption system can be used to achieve arbitrary phase and amplitude beam shaping within the limits of stroke range and influence function of the deformable mirrors. In application, the proposed technique can be used to perform mode conversion between optical beams, generate structured light signals for imaging and scanning, and compensate atmospheric turbulence-induced phase and amplitude beam distortions.

A New Sparse Representation Framework for Reconstruction of an Isotropic High Spatial Resolution MR Volume From Orthogonal Anisotropic Resolution Scans.

PubMed

Jia, Yuanyuan; Gholipour, Ali; He, Zhongshi; Warfield, Simon K

2017-05-01

In magnetic resonance (MR), hardware limitations, scan time constraints, and patient movement often result in the acquisition of anisotropic 3-D MR images with limited spatial resolution in the out-of-plane views. Our goal is to construct an isotropic high-resolution (HR) 3-D MR image through upsampling and fusion of orthogonal anisotropic input scans. We propose a multiframe super-resolution (SR) reconstruction technique based on sparse representation of MR images. Our proposed algorithm exploits the correspondence between the HR slices and the low-resolution (LR) sections of the orthogonal input scans as well as the self-similarity of each input scan to train pairs of overcomplete dictionaries that are used in a sparse-land local model to upsample the input scans. The upsampled images are then combined using wavelet fusion and error backprojection to reconstruct an image. Features are learned from the data and no extra training set is needed. Qualitative and quantitative analyses were conducted to evaluate the proposed algorithm using simulated and clinical MR scans. Experimental results show that the proposed algorithm achieves promising results in terms of peak signal-to-noise ratio, structural similarity image index, intensity profiles, and visualization of small structures obscured in the LR imaging process due to partial volume effects. Our novel SR algorithm outperforms the nonlocal means (NLM) method using self-similarity, NLM method using self-similarity and image prior, self-training dictionary learning-based SR method, averaging of upsampled scans, and the wavelet fusion method. Our SR algorithm can reduce through-plane partial volume artifact by combining multiple orthogonal MR scans, and thus can potentially improve medical image analysis, research, and clinical diagnosis.

Intraretinal Correlates of Reticular Pseudodrusen Revealed by Autofluorescence and En Face OCT.

PubMed

Paavo, Maarjaliis; Lee, Winston; Merriam, John; Bearelly, Srilaxmi; Tsang, Stephen; Chang, Stanley; Sparrow, Janet R

2017-09-01

We sought to determine whether information revealed from the reflectance, autofluorescence, and absorption properties of RPE cells situated posterior to reticular pseudodrusen (RPD) could provide insight into the origins and structure of RPD. RPD were studied qualitatively by near-infrared fundus autofluorescence (NIR-AF), short-wavelength fundus autofluorescence (SW-AF), and infrared reflectance (IR-R) images, and the presentation was compared to horizontal and en face spectral domain optical coherence tomographic (SD-OCT) images. Images were acquired from 23 patients (39 eyes) diagnosed with RPD (mean age 80.7 ± 7.1 [SD]; 16 female; 4 Hispanics, 19 non-Hispanic whites). In SW-AF, NIR-AF, and IR-R images, fundus RPD were recognized as interlacing networks of small scale variations in IR-R and fluorescence (SW-AF, NIR-AF) intensities. Darkened foci of RPD colocalized in SW-AF and NIR-AF images, and in SD-OCT images corresponded to disturbances of the interdigitation (IZ) and ellipsoid (EZ) zones and to more pronounced hyperreflective lesions traversing photoreceptor-attributable bands in SD-OCT images. Qualitative assessment of the outer nuclear layer (ONL) revealed thinning as RPD extended radially from the outer to inner retina. In en face OCT, hyperreflective areas in the EZ band correlated topographically with hyporeflective foci at the level of the RPE. The hyperreflective lesions corresponding to RPD in SD-OCT scans are likely indicative of degenerating photoreceptor cells. The darkened foci at positions of RPD in NIR-AF and en face OCT images indicate changes in the RPE monolayer with the reduced NIR-AF and en face OCT signal suggesting a reduction in melanin that could be accounted for by RPE thinning.

High-accuracy and robust face recognition system based on optical parallel correlator using a temporal image sequence

NASA Astrophysics Data System (ADS)

Watanabe, Eriko; Ishikawa, Mami; Ohta, Maiko; Kodate, Kashiko

2005-09-01

Face recognition is used in a wide range of security systems, such as monitoring credit card use, searching for individuals with street cameras via Internet and maintaining immigration control. There are still many technical subjects under study. For instance, the number of images that can be stored is limited under the current system, and the rate of recognition must be improved to account for photo shots taken at different angles under various conditions. We implemented a fully automatic Fast Face Recognition Optical Correlator (FARCO) system by using a 1000 frame/s optical parallel correlator designed and assembled by us. Operational speed for the 1: N (i.e. matching a pair of images among N, where N refers to the number of images in the database) identification experiment (4000 face images) amounts to less than 1.5 seconds, including the pre/post processing. From trial 1: N identification experiments using FARCO, we acquired low error rates of 2.6% False Reject Rate and 1.3% False Accept Rate. By making the most of the high-speed data-processing capability of this system, much more robustness can be achieved for various recognition conditions when large-category data are registered for a single person. We propose a face recognition algorithm for the FARCO while employing a temporal image sequence of moving images. Applying this algorithm to a natural posture, a two times higher recognition rate scored compared with our conventional system. The system has high potential for future use in a variety of purposes such as search for criminal suspects by use of street and airport video cameras, registration of babies at hospitals or handling of an immeasurable number of images in a database.

Effects of Orientation on Recognition of Facial Affect

NASA Technical Reports Server (NTRS)

Cohen, M. M.; Mealey, J. B.; Hargens, Alan R. (Technical Monitor)

1997-01-01

The ability to discriminate facial features is often degraded when the orientation of the face and/or the observer is altered. Previous studies have shown that gross distortions of facial features can go unrecognized when the image of the face is inverted, as exemplified by the 'Margaret Thatcher' effect. This study examines how quickly erect and supine observers can distinguish between smiling and frowning faces that are presented at various orientations. The effects of orientation are of particular interest in space, where astronauts frequently view one another in orientations other than the upright. Sixteen observers viewed individual facial images of six people on a computer screen; on a given trial, the image was either smiling or frowning. Each image was viewed when it was erect and when it was rotated (rolled) by 45 degrees, 90 degrees, 135 degrees, 180 degrees, 225 degrees and 270 degrees about the line of sight. The observers were required to respond as rapidly and accurately as possible to identify if the face presented was smiling or frowning. Measures of reaction time were obtained when the observers were both upright and supine. Analyses of variance revealed that mean reaction time, which increased with stimulus rotation (F=18.54, df 7/15, p (is less than) 0.001), was 22% longer when the faces were inverted than when they were erect, but that the orientation of the observer had no significant effect on reaction time (F=1.07, df 1/15, p (is greater than) .30). These data strongly suggest that the orientation of the image of a face on the observer's retina, but not its orientation with respect to gravity, is important in identifying the expression on the face.

Phase II Final Report on an Intelligent Tutoring System for Teaching Battlefield Command Reasoning Skills

DTIC Science & Technology

2004-03-01

and current work is that most developers see unstructured language input as a useful complement to a Socratic tutoring approach. The general...demonstrating the possibility of Socratic tactical tutoring, led us , during the second half of our Phase II effort, away from unrestricted natural language ... language use . This often leads to faster, more useful processing, that is robust in the face of real-world input (ungrammatical, misspelled, or

Imaging assessment of penetrating injury of the neck and face.

PubMed

Offiah, Curtis; Hall, Edward

2012-10-01

Penetrating trauma of the neck and face is a frequent presentation to acute emergency, trauma and critical care units. There remains a steady incidence of both gunshot penetrating injury to the neck and face as well as non-missile penetrating injury-largely, but not solely, knife-related. Optimal imaging assessment of such injuries therefore remains an on-going requirement of the general and specialised radiologist. The anatomy of the neck and face-in particular, vascular, pharyngo-oesophageal, laryngo-tracheal and neural anatomy-demands a more specialised and selective management plan which incorporates specific imaging techniques. The current treatment protocol of injuries of the neck and face has seen a radical shift away from expectant surgical exploration in the management of such injuries, largely as a result of advances in the diagnostic capabilities of multi-detector computed tomography angiography (MDCTA), which is now the first-line imaging modality of choice in such cases. This review aims to highlight ballistic considerations, differing imaging modalities, including MDCTA, that might be utilised to assist in the accurate assessment of these injuries as well as the specific radiological features and patterns of specific organ-system injuries that should be considered and communicated to surgical and critical care teams. TEACHING POINTS : • MDCTA is the first-line imaging modality in penetrating trauma of the neck and, often, of the face • The inherent deformability of a bullet is a significant factor in its tissue-damaging capabilities • MDCTA can provide accurate assessment of visceral injury of the neck as well as vascular injury • Penetrating facial trauma warrants radiological assessment of key adjacent anatomical structures • In-driven fragments of native bone potentiate tissue damage in projectile penetrating facial trauma.

Automated grading of lumbar disc degeneration via supervised distance metric learning

NASA Astrophysics Data System (ADS)

He, Xiaoxu; Landis, Mark; Leung, Stephanie; Warrington, James; Shmuilovich, Olga; Li, Shuo

2017-03-01

Lumbar disc degeneration (LDD) is a commonly age-associated condition related to low back pain, while its consequences are responsible for over 90% of spine surgical procedures. In clinical practice, grading of LDD by inspecting MRI is a necessary step to make a suitable treatment plan. This step purely relies on physicians manual inspection so that it brings the unbearable tediousness and inefficiency. An automated method for grading of LDD is highly desirable. However, the technical implementation faces a big challenge from class ambiguity, which is typical in medical image classification problems with a large number of classes. This typical challenge is derived from the complexity and diversity of medical images, which lead to a serious class overlapping and brings a great challenge in discriminating different classes. To solve this problem, we proposed an automated grading approach, which is based on supervised distance metric learning to classify the input discs into four class labels (0: normal, 1: slight, 2: marked, 3: severe). By learning distance metrics from labeled instances, an optimal distance metric is modeled and with two attractive advantages: (1) keeps images from the same classes close, and (2) keeps images from different classes far apart. The experiments, performed in 93 subjects, demonstrated the superiority of our method with accuracy 0.9226, sensitivity 0.9655, specificity 0.9083, F-score 0.8615. With our approach, physicians will be free from the tediousness and patients will be provided an effective treatment.

Human face processing is tuned to sexual age preferences

PubMed Central

Ponseti, J.; Granert, O.; van Eimeren, T.; Jansen, O.; Wolff, S.; Beier, K.; Deuschl, G.; Bosinski, H.; Siebner, H.

2014-01-01

Human faces can motivate nurturing behaviour or sexual behaviour when adults see a child or an adult face, respectively. This suggests that face processing is tuned to detecting age cues of sexual maturity to stimulate the appropriate reproductive behaviour: either caretaking or mating. In paedophilia, sexual attraction is directed to sexually immature children. Therefore, we hypothesized that brain networks that normally are tuned to mature faces of the preferred gender show an abnormal tuning to sexual immature faces in paedophilia. Here, we use functional magnetic resonance imaging (fMRI) to test directly for the existence of a network which is tuned to face cues of sexual maturity. During fMRI, participants sexually attracted to either adults or children were exposed to various face images. In individuals attracted to adults, adult faces activated several brain regions significantly more than child faces. These brain regions comprised areas known to be implicated in face processing, and sexual processing, including occipital areas, the ventrolateral prefrontal cortex and, subcortically, the putamen and nucleus caudatus. The same regions were activated in paedophiles, but with a reversed preferential response pattern. PMID:24850896

Adaptation effects to attractiveness of face photographs and art portraits are domain-specific

PubMed Central

Hayn-Leichsenring, Gregor U.; Kloth, Nadine; Schweinberger, Stefan R.; Redies, Christoph

2013-01-01

We studied the neural coding of facial attractiveness by investigating effects of adaptation to attractive and unattractive human faces on the perceived attractiveness of veridical human face pictures (Experiment 1) and art portraits (Experiment 2). Experiment 1 revealed a clear pattern of contrastive aftereffects. Relative to a pre-adaptation baseline, the perceived attractiveness of faces was increased after adaptation to unattractive faces, and was decreased after adaptation to attractive faces. Experiment 2 revealed similar aftereffects when art portraits rather than face photographs were used as adaptors and test stimuli, suggesting that effects of adaptation to attractiveness are not restricted to facial photographs. Additionally, we found similar aftereffects in art portraits for beauty, another aesthetic feature that, unlike attractiveness, relates to the properties of the image (rather than to the face displayed). Importantly, Experiment 3 showed that aftereffects were abolished when adaptors were art portraits and face photographs were test stimuli. These results suggest that adaptation to facial attractiveness elicits aftereffects in the perception of subsequently presented faces, for both face photographs and art portraits, and that these effects do not cross image domains. PMID:24349690

Face averages enhance user recognition for smartphone security.

PubMed

Robertson, David J; Kramer, Robin S S; Burton, A Mike

2015-01-01

Our recognition of familiar faces is excellent, and generalises across viewing conditions. However, unfamiliar face recognition is much poorer. For this reason, automatic face recognition systems might benefit from incorporating the advantages of familiarity. Here we put this to the test using the face verification system available on a popular smartphone (the Samsung Galaxy). In two experiments we tested the recognition performance of the smartphone when it was encoded with an individual's 'face-average'--a representation derived from theories of human face perception. This technique significantly improved performance for both unconstrained celebrity images (Experiment 1) and for real faces (Experiment 2): users could unlock their phones more reliably when the device stored an average of the user's face than when they stored a single image. This advantage was consistent across a wide variety of everyday viewing conditions. Furthermore, the benefit did not reduce the rejection of imposter faces. This benefit is brought about solely by consideration of suitable representations for automatic face recognition, and we argue that this is just as important as development of matching algorithms themselves. We propose that this representation could significantly improve recognition rates in everyday settings.

Investigating the Role of Global Histogram Equalization Technique for 99mTechnetium-Methylene diphosphonate Bone Scan Image Enhancement.

PubMed

Pandey, Anil Kumar; Sharma, Param Dev; Dheer, Pankaj; Parida, Girish Kumar; Goyal, Harish; Patel, Chetan; Bal, Chandrashekhar; Kumar, Rakesh

2017-01-01

99m Technetium-methylene diphosphonate ( 99m Tc-MDP) bone scan images have limited number of counts per pixel, and hence, they have inferior image quality compared to X-rays. Theoretically, global histogram equalization (GHE) technique can improve the contrast of a given image though practical benefits of doing so have only limited acceptance. In this study, we have investigated the effect of GHE technique for 99m Tc-MDP-bone scan images. A set of 89 low contrast 99m Tc-MDP whole-body bone scan images were included in this study. These images were acquired with parallel hole collimation on Symbia E gamma camera. The images were then processed with histogram equalization technique. The image quality of input and processed images were reviewed by two nuclear medicine physicians on a 5-point scale where score of 1 is for very poor and 5 is for the best image quality. A statistical test was applied to find the significance of difference between the mean scores assigned to input and processed images. This technique improves the contrast of the images; however, oversaturation was noticed in the processed images. Student's t -test was applied, and a statistically significant difference in the input and processed image quality was found at P < 0.001 (with α = 0.05). However, further improvement in image quality is needed as per requirements of nuclear medicine physicians. GHE techniques can be used on low contrast bone scan images. In some of the cases, a histogram equalization technique in combination with some other postprocessing technique is useful.

The representation of information about faces in the temporal and frontal lobes.

PubMed

Rolls, Edmund T

2007-01-07

Neurophysiological evidence is described showing that some neurons in the macaque inferior temporal visual cortex have responses that are invariant with respect to the position, size and view of faces and objects, and that these neurons show rapid processing and rapid learning. Which face or object is present is encoded using a distributed representation in which each neuron conveys independent information in its firing rate, with little information evident in the relative time of firing of different neurons. This ensemble encoding has the advantages of maximising the information in the representation useful for discrimination between stimuli using a simple weighted sum of the neuronal firing by the receiving neurons, generalisation and graceful degradation. These invariant representations are ideally suited to provide the inputs to brain regions such as the orbitofrontal cortex and amygdala that learn the reinforcement associations of an individual's face, for then the learning, and the appropriate social and emotional responses, generalise to other views of the same face. A theory is described of how such invariant representations may be produced in a hierarchically organised set of visual cortical areas with convergent connectivity. The theory proposes that neurons in these visual areas use a modified Hebb synaptic modification rule with a short-term memory trace to capture whatever can be captured at each stage that is invariant about objects as the objects change in retinal view, position, size and rotation. Another population of neurons in the cortex in the superior temporal sulcus encodes other aspects of faces such as face expression, eye gaze, face view and whether the head is moving. These neurons thus provide important additional inputs to parts of the brain such as the orbitofrontal cortex and amygdala that are involved in social communication and emotional behaviour. Outputs of these systems reach the amygdala, in which face-selective neurons are found, and also the orbitofrontal cortex, in which some neurons are tuned to face identity and others to face expression. In humans, activation of the orbitofrontal cortex is found when a change of face expression acts as a social signal that behaviour should change; and damage to the orbitofrontal cortex can impair face and voice expression identification, and also the reversal of emotional behaviour that normally occurs when reinforcers are reversed.

Tensor discriminant color space for face recognition.

PubMed

Wang, Su-Jing; Yang, Jian; Zhang, Na; Zhou, Chun-Guang

2011-09-01

Recent research efforts reveal that color may provide useful information for face recognition. For different visual tasks, the choice of a color space is generally different. How can a color space be sought for the specific face recognition problem? To address this problem, this paper represents a color image as a third-order tensor and presents the tensor discriminant color space (TDCS) model. The model can keep the underlying spatial structure of color images. With the definition of n-mode between-class scatter matrices and within-class scatter matrices, TDCS constructs an iterative procedure to obtain one color space transformation matrix and two discriminant projection matrices by maximizing the ratio of these two scatter matrices. The experiments are conducted on two color face databases, AR and Georgia Tech face databases, and the results show that both the performance and the efficiency of the proposed method are better than those of the state-of-the-art color image discriminant model, which involve one color space transformation matrix and one discriminant projection matrix, specifically in a complicated face database with various pose variations.

Adaptive 3D Face Reconstruction from Unconstrained Photo Collections.

PubMed

Roth, Joseph; Tong, Yiying; Liu, Xiaoming

2016-12-07

Given a photo collection of "unconstrained" face images of one individual captured under a variety of unknown pose, expression, and illumination conditions, this paper presents a method for reconstructing a 3D face surface model of the individual along with albedo information. Unlike prior work on face reconstruction that requires large photo collections, we formulate an approach to adapt to photo collections with a high diversity in both the number of images and the image quality. To achieve this, we incorporate prior knowledge about face shape by fitting a 3D morphable model to form a personalized template, following by using a novel photometric stereo formulation to complete the fine details, under a coarse-to-fine scheme. Our scheme incorporates a structural similarity-based local selection step to help identify a common expression for reconstruction while discarding occluded portions of faces. The evaluation of reconstruction performance is through a novel quality measure, in the absence of ground truth 3D scans. Superior large-scale experimental results are reported on synthetic, Internet, and personal photo collections.

Facial recognition from volume-rendered magnetic resonance imaging data.

PubMed

Prior, Fred W; Brunsden, Barry; Hildebolt, Charles; Nolan, Tracy S; Pringle, Michael; Vaishnavi, S Neil; Larson-Prior, Linda J

2009-01-01

Three-dimensional (3-D) reconstructions of computed tomography (CT) and magnetic resonance (MR) brain imaging studies are a routine component of both clinical practice and clinical and translational research. A side effect of such reconstructions is the creation of a potentially recognizable face. The Health Insurance Portability and Accountability Act of 1996 (HIPAA) Privacy Rule requires that individually identifiable health information may not be used for research unless identifiers that may be associated with the health information including "Full face photographic images and other comparable images ..." are removed (de-identification). Thus, a key question is: Are reconstructed facial images comparable to full-face photographs for the purpose of identification? To address this question, MR images were selected from existing research repositories and subjects were asked to pair an MR reconstruction with one of 40 photographs. The chance probability that an observer could match a photograph with its 3-D MR image was 1 in 40 (0.025), and we considered 4 successes out of 40 (4/40, 0.1) to indicate that a subject could identify persons' faces from their 3-D MR images. Forty percent of the subjects were able to successfully match photographs with MR images with success rates higher than the null hypothesis success rate. The Blyth-Still-Casella 95% confidence interval for the 40% success rate was 29%-52%, and the 40% success rate was significantly higher ( P < 0.001) than our null hypothesis success rate of 1 in 10 (0.10).

Arsia Mons by Day and Night

NASA Image and Video Library

2004-06-22

Released 22 June 2004 This pair of images shows part of Arsia Mons. Day/Night Infrared Pairs The image pairs presented focus on a single surface feature as seen in both the daytime and nighttime by the infrared THEMIS camera. The nighttime image (right) has been rotated 180 degrees to place north at the top. Infrared image interpretation Daytime: Infrared images taken during the daytime exhibit both the morphological and thermophysical properties of the surface of Mars. Morphologic details are visible due to the effect of sun-facing slopes receiving more energy than antisun-facing slopes. This creates a warm (bright) slope and cool (dark) slope appearance that mimics the light and shadows of a visible wavelength image. Thermophysical properties are seen in that dust heats up more quickly than rocks. Thus dusty areas are bright and rocky areas are dark. Nighttime: Infrared images taken during the nighttime exhibit only the thermophysical properties of the surface of Mars. The effect of sun-facing versus non-sun-facing energy dissipates quickly at night. Thermophysical effects dominate as different surfaces cool at different rates through the nighttime hours. Rocks cool slowly, and are therefore relatively bright at night (remember that rocks are dark during the day). Dust and other fine grained materials cool very quickly and are dark in nighttime infrared images. Image information: IR instrument. Latitude -19.6, Longitude 241.9 East (118.1 West). 100 meter/pixel resolution. http://photojournal.jpl.nasa.gov/catalog/PIA06399

Crater Ejecta by Day and Night

NASA Image and Video Library

2004-06-24

Released 24 June 2004 This pair of images shows a crater and its ejecta. Day/Night Infrared Pairs The image pairs presented focus on a single surface feature as seen in both the daytime and nighttime by the infrared THEMIS camera. The nighttime image (right) has been rotated 180 degrees to place north at the top. Infrared image interpretation Daytime: Infrared images taken during the daytime exhibit both the morphological and thermophysical properties of the surface of Mars. Morphologic details are visible due to the effect of sun-facing slopes receiving more energy than antisun-facing slopes. This creates a warm (bright) slope and cool (dark) slope appearance that mimics the light and shadows of a visible wavelength image. Thermophysical properties are seen in that dust heats up more quickly than rocks. Thus dusty areas are bright and rocky areas are dark. Nighttime: Infrared images taken during the nighttime exhibit only the thermophysical properties of the surface of Mars. The effect of sun-facing versus non-sun-facing energy dissipates quickly at night. Thermophysical effects dominate as different surfaces cool at different rates through the nighttime hours. Rocks cool slowly, and are therefore relatively bright at night (remember that rocks are dark during the day). Dust and other fine grained materials cool very quickly and are dark in nighttime infrared images. Image information: IR instrument. Latitude -9, Longitude 164.2 East (195.8 West). 100 meter/pixel resolution. http://photojournal.jpl.nasa.gov/catalog/PIA06445

Bone marrow cavity segmentation using graph-cuts with wavelet-based texture feature.

PubMed

Shigeta, Hironori; Mashita, Tomohiro; Kikuta, Junichi; Seno, Shigeto; Takemura, Haruo; Ishii, Masaru; Matsuda, Hideo

2017-10-01

Emerging bioimaging technologies enable us to capture various dynamic cellular activities [Formula: see text]. As large amounts of data are obtained these days and it is becoming unrealistic to manually process massive number of images, automatic analysis methods are required. One of the issues for automatic image segmentation is that image-taking conditions are variable. Thus, commonly, many manual inputs are required according to each image. In this paper, we propose a bone marrow cavity (BMC) segmentation method for bone images as BMC is considered to be related to the mechanism of bone remodeling, osteoporosis, and so on. To reduce manual inputs to segment BMC, we classified the texture pattern using wavelet transformation and support vector machine. We also integrated the result of texture pattern classification into the graph-cuts-based image segmentation method because texture analysis does not consider spatial continuity. Our method is applicable to a particular frame in an image sequence in which the condition of fluorescent material is variable. In the experiment, we evaluated our method with nine types of mother wavelets and several sets of scale parameters. The proposed method with graph-cuts and texture pattern classification performs well without manual inputs by a user.

Accelerating object detection via a visual-feature-directed search cascade: algorithm and field programmable gate array implementation

NASA Astrophysics Data System (ADS)

Kyrkou, Christos; Theocharides, Theocharis

2016-07-01

Object detection is a major step in several computer vision applications and a requirement for most smart camera systems. Recent advances in hardware acceleration for real-time object detection feature extensive use of reconfigurable hardware [field programmable gate arrays (FPGAs)], and relevant research has produced quite fascinating results, in both the accuracy of the detection algorithms as well as the performance in terms of frames per second (fps) for use in embedded smart camera systems. Detecting objects in images, however, is a daunting task and often involves hardware-inefficient steps, both in terms of the datapath design and in terms of input/output and memory access patterns. We present how a visual-feature-directed search cascade composed of motion detection, depth computation, and edge detection, can have a significant impact in reducing the data that needs to be examined by the classification engine for the presence of an object of interest. Experimental results on a Spartan 6 FPGA platform for face detection indicate data search reduction of up to 95%, which results in the system being able to process up to 50 1024×768 pixels images per second with a significantly reduced number of false positives.

Browsing Through Closed Books: Evaluation of Preprocessing Methods for Page Extraction of a 3-D CT Book Volume

NASA Astrophysics Data System (ADS)

Stromer, D.; Christlein, V.; Schön, T.; Holub, W.; Maier, A.

2017-09-01

It is often the case that a document can not be opened, page-turned or touched anymore due to damages caused by aging processes, moisture or fire. To counter this, special imaging systems can be used. One of our earlier work revealed that a common 3-D X-ray micro-CT scanner is well suited for imaging and reconstructing historical documents written with iron gall ink - an ink consisting of metallic particles. We acquired a volume of a self-made book without opening or page-turning with a single 3-D scan. However, when investigating the reconstructed volume, we faced the problem of a proper automatic extraction of single pages within the volume in an acceptable time without losing information of the writings. Within this work, we evaluate different appropriate pre-processing methods with respect to computation time and accuracy which are decisive for a proper extraction of book pages from the reconstructed X-ray volume and the subsequent ink identification. The different methods were tested for an extreme case with low resolution, noisy input data and wavy pages. Finally, we present results of the page extraction after applying the evaluated methods.

Mask-to-wafer alignment system

DOEpatents

Sweatt, William C.; Tichenor, Daniel A.; Haney, Steven J.

2003-11-04

A modified beam splitter that has a hole pattern that is symmetric in one axis and anti-symmetric in the other can be employed in a mask-to-wafer alignment device. The device is particularly suited for rough alignment using visible light. The modified beam splitter transmits and reflects light from a source of electromagnetic radiation and it includes a substrate that has a first surface facing the source of electromagnetic radiation and second surface that is reflective of said electromagnetic radiation. The substrate defines a hole pattern about a central line of the substrate. In operation, an input beam from a camera is directed toward the modified beam splitter and the light from the camera that passes through the holes illuminates the reticle on the wafer. The light beam from the camera also projects an image of a corresponding reticle pattern that is formed on the mask surface of the that is positioned downstream from the camera. Alignment can be accomplished by detecting the radiation that is reflected from the second surface of the modified beam splitter since the reflected radiation contains both the image of the pattern from the mask and a corresponding pattern on the wafer.

Hand motion segmentation against skin colour background in breast awareness applications.

PubMed

Hu, Yuqin; Naguib, Raouf N G; Todman, Alison G; Amin, Saad A; Al-Omishy, Hassanein; Oikonomou, Andreas; Tucker, Nick

2004-01-01

Skin colour modelling and classification play significant roles in face and hand detection, recognition and tracking. A hand is an essential tool used in breast self-examination, which needs to be detected and analysed during the process of breast palpation. However, the background of a woman's moving hand is her breast that has the same or similar colour as the hand. Additionally, colour images recorded by a web camera are strongly affected by the lighting or brightness conditions. Hence, it is a challenging task to segment and track the hand against the breast without utilising any artificial markers, such as coloured nail polish. In this paper, a two-dimensional Gaussian skin colour model is employed in a particular way to identify a breast but not a hand. First, an input image is transformed to YCbCr colour space, which is less sensitive to the lighting conditions and more tolerant of skin tone. The breast, thus detected by the Gaussian skin model, is used as the baseline or framework for the hand motion. Secondly, motion cues are used to segment the hand motion against the detected baseline. Desired segmentation results have been achieved and the robustness of this algorithm is demonstrated in this paper.

Electrophysiological evidence for separation between human face and non-face object processing only in the right hemisphere.

PubMed

Niina, Megumi; Okamura, Jun-ya; Wang, Gang

2015-10-01

Scalp event-related potential (ERP) studies have demonstrated larger N170 amplitudes when subjects view faces compared to items from object categories. Extensive attempts have been made to clarify face selectivity and hemispheric dominance for face processing. The purpose of this study was to investigate hemispheric differences in N170s activated by human faces and non-face objects, as well as the extent of overlap of their sources. ERP was recorded from 20 subjects while they viewed human face and non-face images. N170s obtained during the presentation of human faces appeared earlier and with larger amplitude than for other category images. Further source analysis with a two-dipole model revealed that the locations of face and object processing largely overlapped in the left hemisphere. Conversely, the source for face processing in the right hemisphere located more anterior than the source for object processing. The results suggest that the neuronal circuits for face and object processing are largely shared in the left hemisphere, with more distinct circuits in the right hemisphere. Copyright © 2015 Elsevier B.V. All rights reserved.

Strength and coherence of binocular rivalry depends on shared stimulus complexity.

PubMed

Alais, David; Melcher, David

2007-01-01

Presenting incompatible images to the eyes results in alternations of conscious perception, a phenomenon known as binocular rivalry. We examined rivalry using either simple stimuli (oriented gratings) or coherent visual objects (faces, houses etc). Two rivalry characteristics were measured: Depth of rivalry suppression and coherence of alternations. Rivalry between coherent visual objects exhibits deep suppression and coherent rivalry, whereas rivalry between gratings exhibits shallow suppression and piecemeal rivalry. Interestingly, rivalry between a simple and a complex stimulus displays the same characteristics (shallow and piecemeal) as rivalry between two simple stimuli. Thus, complex stimuli fail to rival globally unless the fellow stimulus is also global. We also conducted a face adaptation experiment. Adaptation to rivaling faces improved subsequent face discrimination (as expected), but adaptation to a rivaling face/grating pair did not. To explain this, we suggest rivalry must be an early and local process (at least initially), instigated by the failure of binocular fusion, which can then become globally organized by feedback from higher-level areas when both rivalry stimuli are global, so that rivalry tends to oscillate coherently. These globally assembled images then flow through object processing areas, with the dominant image gaining in relative strength in a form of 'biased competition', therefore accounting for the deeper suppression of global images. In contrast, when only one eye receives a global image, local piecemeal suppression from the fellow eye overrides the organizing effects of global feedback to prevent coherent image formation. This indicates the primacy of local over global processes in rivalry.

Model, analysis, and evaluation of the effects of analog VLSI arithmetic on linear subspace-based image recognition.

PubMed

Carvajal, Gonzalo; Figueroa, Miguel

2014-07-01

Typical image recognition systems operate in two stages: feature extraction to reduce the dimensionality of the input space, and classification based on the extracted features. Analog Very Large Scale Integration (VLSI) is an attractive technology to achieve compact and low-power implementations of these computationally intensive tasks for portable embedded devices. However, device mismatch limits the resolution of the circuits fabricated with this technology. Traditional layout techniques to reduce the mismatch aim to increase the resolution at the transistor level, without considering the intended application. Relating mismatch parameters to specific effects in the application level would allow designers to apply focalized mismatch compensation techniques according to predefined performance/cost tradeoffs. This paper models, analyzes, and evaluates the effects of mismatched analog arithmetic in both feature extraction and classification circuits. For the feature extraction, we propose analog adaptive linear combiners with on-chip learning for both Least Mean Square (LMS) and Generalized Hebbian Algorithm (GHA). Using mathematical abstractions of analog circuits, we identify mismatch parameters that are naturally compensated during the learning process, and propose cost-effective guidelines to reduce the effect of the rest. For the classification, we derive analog models for the circuits necessary to implement Nearest Neighbor (NN) approach and Radial Basis Function (RBF) networks, and use them to emulate analog classifiers with standard databases of face and hand-writing digits. Formal analysis and experiments show how we can exploit adaptive structures and properties of the input space to compensate the effects of device mismatch at the application level, thus reducing the design overhead of traditional layout techniques. Results are also directly extensible to multiple application domains using linear subspace methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

Using pattern recognition to automatically localize reflection hyperbolas in data from ground penetrating radar

NASA Astrophysics Data System (ADS)

Maas, Christian; Schmalzl, Jörg

2013-08-01

Ground Penetrating Radar (GPR) is used for the localization of supply lines, land mines, pipes and many other buried objects. These objects can be recognized in the recorded data as reflection hyperbolas with a typical shape depending on depth and material of the object and the surrounding material. To obtain the parameters, the shape of the hyperbola has to be fitted. In the last years several methods were developed to automate this task during post-processing. In this paper we show another approach for the automated localization of reflection hyperbolas in GPR data by solving a pattern recognition problem in grayscale images. In contrast to other methods our detection program is also able to immediately mark potential objects in real-time. For this task we use a version of the Viola-Jones learning algorithm, which is part of the open source library "OpenCV". This algorithm was initially developed for face recognition, but can be adapted to any other simple shape. In our program it is used to narrow down the location of reflection hyperbolas to certain areas in the GPR data. In order to extract the exact location and the velocity of the hyperbolas we apply a simple Hough Transform for hyperbolas. Because the Viola-Jones Algorithm reduces the input for the computational expensive Hough Transform dramatically the detection system can also be implemented on normal field computers, so on-site application is possible. The developed detection system shows promising results and detection rates in unprocessed radargrams. In order to improve the detection results and apply the program to noisy radar images more data of different GPR systems as input for the learning algorithm is necessary.

Real-time face and gesture analysis for human-robot interaction

NASA Astrophysics Data System (ADS)

Wallhoff, Frank; Rehrl, Tobias; Mayer, Christoph; Radig, Bernd

2010-05-01

Human communication relies on a large number of different communication mechanisms like spoken language, facial expressions, or gestures. Facial expressions and gestures are one of the main nonverbal communication mechanisms and pass large amounts of information between human dialog partners. Therefore, to allow for intuitive human-machine interaction, a real-time capable processing and recognition of facial expressions, hand and head gestures are of great importance. We present a system that is tackling these challenges. The input features for the dynamic head gestures and facial expressions are obtained from a sophisticated three-dimensional model, which is fitted to the user in a real-time capable manner. Applying this model different kinds of information are extracted from the image data and afterwards handed over to a real-time capable data-transferring framework, the so-called Real-Time DataBase (RTDB). In addition to the head and facial-related features, also low-level image features regarding the human hand - optical flow, Hu-moments are stored into the RTDB for the evaluation process of hand gestures. In general, the input of a single camera is sufficient for the parallel evaluation of the different gestures and facial expressions. The real-time capable recognition of the dynamic hand and head gestures are performed via different Hidden Markov Models, which have proven to be a quick and real-time capable classification method. On the other hand, for the facial expressions classical decision trees or more sophisticated support vector machines are used for the classification process. These obtained results of the classification processes are again handed over to the RTDB, where other processes (like a Dialog Management Unit) can easily access them without any blocking effects. In addition, an adjustable amount of history can be stored by the RTDB buffer unit.

Identification of optimal mask size parameter for noise filtering in 99mTc-methylene diphosphonate bone scintigraphy images.

PubMed

Pandey, Anil K; Bisht, Chandan S; Sharma, Param D; ArunRaj, Sreedharan Thankarajan; Taywade, Sameer; Patel, Chetan; Bal, Chandrashekhar; Kumar, Rakesh

2017-11-01

Tc-methylene diphosphonate (Tc-MDP) bone scintigraphy images have limited number of counts per pixel. A noise filtering method based on local statistics of the image produces better results than a linear filter. However, the mask size has a significant effect on image quality. In this study, we have identified the optimal mask size that yields a good smooth bone scan image. Forty four bone scan images were processed using mask sizes 3, 5, 7, 9, 11, 13, and 15 pixels. The input and processed images were reviewed in two steps. In the first step, the images were inspected and the mask sizes that produced images with significant loss of clinical details in comparison with the input image were excluded. In the second step, the image quality of the 40 sets of images (each set had input image, and its corresponding three processed images with 3, 5, and 7-pixel masks) was assessed by two nuclear medicine physicians. They selected one good smooth image from each set of images. The image quality was also assessed quantitatively with a line profile. Fisher's exact test was used to find statistically significant differences in image quality processed with 5 and 7-pixel mask at a 5% cut-off. A statistically significant difference was found between the image quality processed with 5 and 7-pixel mask at P=0.00528. The identified optimal mask size to produce a good smooth image was found to be 7 pixels. The best mask size for the John-Sen Lee filter was found to be 7×7 pixels, which yielded Tc-methylene diphosphonate bone scan images with the highest acceptable smoothness.