Web-based, GPU-accelerated, Monte Carlo simulation and visualization of indirect radiation imaging detector performance

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

Dong, Han; Sharma, Diksha; Badano, Aldo, E-mail: aldo.badano@fda.hhs.gov

2014-12-15

Purpose: Monte Carlo simulations play a vital role in the understanding of the fundamental limitations, design, and optimization of existing and emerging medical imaging systems. Efforts in this area have resulted in the development of a wide variety of open-source software packages. One such package, hybridMANTIS, uses a novel hybrid concept to model indirect scintillator detectors by balancing the computational load using dual CPU and graphics processing unit (GPU) processors, obtaining computational efficiency with reasonable accuracy. In this work, the authors describe two open-source visualization interfaces, webMANTIS and visualMANTIS to facilitate the setup of computational experiments via hybridMANTIS. Methods: Themore » visualization tools visualMANTIS and webMANTIS enable the user to control simulation properties through a user interface. In the case of webMANTIS, control via a web browser allows access through mobile devices such as smartphones or tablets. webMANTIS acts as a server back-end and communicates with an NVIDIA GPU computing cluster that can support multiuser environments where users can execute different experiments in parallel. Results: The output consists of point response and pulse-height spectrum, and optical transport statistics generated by hybridMANTIS. The users can download the output images and statistics through a zip file for future reference. In addition, webMANTIS provides a visualization window that displays a few selected optical photon path as they get transported through the detector columns and allows the user to trace the history of the optical photons. Conclusions: The visualization tools visualMANTIS and webMANTIS provide features such as on the fly generation of pulse-height spectra and response functions for microcolumnar x-ray imagers while allowing users to save simulation parameters and results from prior experiments. The graphical interfaces simplify the simulation setup and allow the user to go directly from specifying input parameters to receiving visual feedback for the model predictions.« less

Web-based, GPU-accelerated, Monte Carlo simulation and visualization of indirect radiation imaging detector performance.

PubMed

Dong, Han; Sharma, Diksha; Badano, Aldo

2014-12-01

Monte Carlo simulations play a vital role in the understanding of the fundamental limitations, design, and optimization of existing and emerging medical imaging systems. Efforts in this area have resulted in the development of a wide variety of open-source software packages. One such package, hybridmantis, uses a novel hybrid concept to model indirect scintillator detectors by balancing the computational load using dual CPU and graphics processing unit (GPU) processors, obtaining computational efficiency with reasonable accuracy. In this work, the authors describe two open-source visualization interfaces, webmantis and visualmantis to facilitate the setup of computational experiments via hybridmantis. The visualization tools visualmantis and webmantis enable the user to control simulation properties through a user interface. In the case of webmantis, control via a web browser allows access through mobile devices such as smartphones or tablets. webmantis acts as a server back-end and communicates with an NVIDIA GPU computing cluster that can support multiuser environments where users can execute different experiments in parallel. The output consists of point response and pulse-height spectrum, and optical transport statistics generated by hybridmantis. The users can download the output images and statistics through a zip file for future reference. In addition, webmantis provides a visualization window that displays a few selected optical photon path as they get transported through the detector columns and allows the user to trace the history of the optical photons. The visualization tools visualmantis and webmantis provide features such as on the fly generation of pulse-height spectra and response functions for microcolumnar x-ray imagers while allowing users to save simulation parameters and results from prior experiments. The graphical interfaces simplify the simulation setup and allow the user to go directly from specifying input parameters to receiving visual feedback for the model predictions.

A visual tracking method based on deep learning without online model updating

NASA Astrophysics Data System (ADS)

Tang, Cong; Wang, Yicheng; Feng, Yunsong; Zheng, Chao; Jin, Wei

2018-02-01

The paper proposes a visual tracking method based on deep learning without online model updating. In consideration of the advantages of deep learning in feature representation, deep model SSD (Single Shot Multibox Detector) is used as the object extractor in the tracking model. Simultaneously, the color histogram feature and HOG (Histogram of Oriented Gradient) feature are combined to select the tracking object. In the process of tracking, multi-scale object searching map is built to improve the detection performance of deep detection model and the tracking efficiency. In the experiment of eight respective tracking video sequences in the baseline dataset, compared with six state-of-the-art methods, the method in the paper has better robustness in the tracking challenging factors, such as deformation, scale variation, rotation variation, illumination variation, and background clutters, moreover, its general performance is better than other six tracking methods.

A method for the topographical identification and quantification of high frequency oscillations in intracranial electroencephalography recordings

PubMed Central

Waldman, Zachary J.; Shimamoto, Shoichi; Song, Inkyung; Orosz, Iren; Bragin, Anatol; Fried, Itzhak; Engel, Jerome; Staba, Richard; Sperling, Michael R.; Weiss, Shennan A.

2018-01-01

Objective To develop a reliable software method using a topographic analysis of time-frequency plots to distinguish ripple (80–200 Hz) oscillations that are often associated with EEG sharp waves or spikes (RonS) from sinusoid-like waveforms that appear as ripples but correspond with digital filtering of sharp transients contained in the wide bandwidth EEG. Methods A custom algorithm distinguished true from false ripples in one second intracranial EEG (iEEG) recordings using wavelet convolution, identifying contours of isopower, and categorizing these contours into sets of open or closed loop groups. The spectral and temporal features of candidate groups were used to classify the ripple, and determine its duration, frequency, and power. Verification of detector accuracy was performed on the basis of simulations, and visual inspection of the original and band-pass filtered signals. Results The detector could distinguish simulated true from false ripple on spikes (RonS). Among 2934 visually verified trials of iEEG recordings and spectrograms exhibiting RonS the accuracy of the detector was 88.5% with a sensitivity of 81.8% and a specificity of 95.2%. The precision was 94.5% and the negative predictive value was 84.0% (N = 12). Among, 1,370 trials of iEEG recording exhibiting RonS that were reviewed blindly without spectrograms the accuracy of the detector was 68.0%, with kappa equal to 0.01 ± 0.03. The detector successfully distinguished ripple from high spectral frequency ‘fast ripple’ oscillations (200–600 Hz), and characterize ripple duration and spectral frequency and power. The detector was confounded by brief bursts of gamma (30–80 Hz) activity in 7.31 ± 6.09% of trials, and in 30.2 ± 14.4% of the true RonS detections ripple duration was underestimated. Conclusions Characterizing the topographic features of a time-frequency plot generated by wavelet convolution is useful for distinguishing true oscillations from false oscillations generated by filter ringing. Significance Categorizing ripple oscillations and characterizing their properties can improve the clinical utility of the biomarker. PMID:29122445

Learning invariance from natural images inspired by observations in the primary visual cortex.

PubMed

Teichmann, Michael; Wiltschut, Jan; Hamker, Fred

2012-05-01

The human visual system has the remarkable ability to largely recognize objects invariant of their position, rotation, and scale. A good interpretation of neurobiological findings involves a computational model that simulates signal processing of the visual cortex. In part, this is likely achieved step by step from early to late areas of visual perception. While several algorithms have been proposed for learning feature detectors, only few studies at hand cover the issue of biologically plausible learning of such invariance. In this study, a set of Hebbian learning rules based on calcium dynamics and homeostatic regulations of single neurons is proposed. Their performance is verified within a simple model of the primary visual cortex to learn so-called complex cells, based on a sequence of static images. As a result, the learned complex-cell responses are largely invariant to phase and position.

SigWin-detector: a Grid-enabled workflow for discovering enriched windows of genomic features related to DNA sequences.

PubMed

Inda, Márcia A; van Batenburg, Marinus F; Roos, Marco; Belloum, Adam S Z; Vasunin, Dmitry; Wibisono, Adianto; van Kampen, Antoine H C; Breit, Timo M

2008-08-08

Chromosome location is often used as a scaffold to organize genomic information in both the living cell and molecular biological research. Thus, ever-increasing amounts of data about genomic features are stored in public databases and can be readily visualized by genome browsers. To perform in silico experimentation conveniently with this genomics data, biologists need tools to process and compare datasets routinely and explore the obtained results interactively. The complexity of such experimentation requires these tools to be based on an e-Science approach, hence generic, modular, and reusable. A virtual laboratory environment with workflows, workflow management systems, and Grid computation are therefore essential. Here we apply an e-Science approach to develop SigWin-detector, a workflow-based tool that can detect significantly enriched windows of (genomic) features in a (DNA) sequence in a fast and reproducible way. For proof-of-principle, we utilize a biological use case to detect regions of increased and decreased gene expression (RIDGEs and anti-RIDGEs) in human transcriptome maps. We improved the original method for RIDGE detection by replacing the costly step of estimation by random sampling with a faster analytical formula for computing the distribution of the null hypothesis being tested and by developing a new algorithm for computing moving medians. SigWin-detector was developed using the WS-VLAM workflow management system and consists of several reusable modules that are linked together in a basic workflow. The configuration of this basic workflow can be adapted to satisfy the requirements of the specific in silico experiment. As we show with the results from analyses in the biological use case on RIDGEs, SigWin-detector is an efficient and reusable Grid-based tool for discovering windows enriched for features of a particular type in any sequence of values. Thus, SigWin-detector provides the proof-of-principle for the modular e-Science based concept of integrative bioinformatics experimentation.

Using the shortwave infrared to image middle ear pathologies

PubMed Central

Valdez, Tulio A.; Bruns, Oliver T.; Bawendi, Moungi G.

2016-01-01

Visualizing structures deep inside opaque biological tissues is one of the central challenges in biomedical imaging. Optical imaging with visible light provides high resolution and sensitivity; however, scattering and absorption of light by tissue limits the imaging depth to superficial features. Imaging with shortwave infrared light (SWIR, 1–2 μm) shares many advantages of visible imaging, but light scattering in tissue is reduced, providing sufficient optical penetration depth to noninvasively interrogate subsurface tissue features. However, the clinical potential of this approach has been largely unexplored because suitable detectors, until recently, have been either unavailable or cost prohibitive. Here, taking advantage of newly available detector technology, we demonstrate the potential of SWIR light to improve diagnostics through the development of a medical otoscope for determining middle ear pathologies. We show that SWIR otoscopy has the potential to provide valuable diagnostic information complementary to that provided by visible pneumotoscopy. We show that in healthy adult human ears, deeper tissue penetration of SWIR light allows better visualization of middle ear structures through the tympanic membrane, including the ossicular chain, promontory, round window niche, and chorda tympani. In addition, we investigate the potential for detection of middle ear fluid, which has significant implications for diagnosing otitis media, the overdiagnosis of which is a primary factor in increased antibiotic resistance. Middle ear fluid shows strong light absorption between 1,400 and 1,550 nm, enabling straightforward fluid detection in a model using the SWIR otoscope. Moreover, our device is easily translatable to the clinic, as the ergonomics, visual output, and operation are similar to a conventional otoscope. PMID:27551085

Do Convolutional Neural Networks Learn Class Hierarchy?

PubMed

Bilal, Alsallakh; Jourabloo, Amin; Ye, Mao; Liu, Xiaoming; Ren, Liu

2018-01-01

Convolutional Neural Networks (CNNs) currently achieve state-of-the-art accuracy in image classification. With a growing number of classes, the accuracy usually drops as the possibilities of confusion increase. Interestingly, the class confusion patterns follow a hierarchical structure over the classes. We present visual-analytics methods to reveal and analyze this hierarchy of similar classes in relation with CNN-internal data. We found that this hierarchy not only dictates the confusion patterns between the classes, it furthermore dictates the learning behavior of CNNs. In particular, the early layers in these networks develop feature detectors that can separate high-level groups of classes quite well, even after a few training epochs. In contrast, the latter layers require substantially more epochs to develop specialized feature detectors that can separate individual classes. We demonstrate how these insights are key to significant improvement in accuracy by designing hierarchy-aware CNNs that accelerate model convergence and alleviate overfitting. We further demonstrate how our methods help in identifying various quality issues in the training data.

Quantitative comparison using Generalized Relative Object Detectability (G-ROD) metrics of an amorphous selenium detector with high resolution Microangiographic Fluoroscopes (MAF) and standard flat panel detectors (FPD).

PubMed

Russ, M; Shankar, A; Jain, A; Setlur Nagesh, S V; Ionita, C N; Scott, C; Karim, K S; Bednarek, D R; Rudin, S

2016-02-27

A novel amorphous selenium (a-Se) direct detector with CMOS readout has been designed, and relative detector performance investigated. The detector features include a 25 μ m pixel pitch, and 1000 μ m thick a-Se layer operating at 10V/ μ m bias field. A simulated detector DQE was determined, and used in comparative calculations of the Relative Object Detectability (ROD) family of prewhitening matched-filter (PWMF) observer and non-prewhitening matched filter (NPWMF) observer model metrics to gauge a-Se detector performance against existing high resolution micro-angiographic fluoroscopic (MAF) detectors and a standard flat panel detector (FPD). The PWMF-ROD or ROD metric compares two x-ray imaging detectors in their relative abilities in imaging a given object by taking the integral over spatial frequencies of the Fourier transform of the detector DQE weighted by an object function, divided by the comparable integral for a different detector. The generalized-ROD (G-ROD) metric incorporates clinically relevant parameters (focal-spot size, magnification, and scatter) to show the degradation in imaging performance for detectors that are part of an imaging chain. Preliminary ROD calculations using simulated spheres as the object predicted superior imaging performance by the a-Se detector as compared to existing detectors. New PWMF-G-ROD and NPWMF-G-ROD results still indicate better performance by the a-Se detector in an imaging chain over all sphere sizes for various focal spot sizes and magnifications, although a-Se performance advantages were degraded by focal spot blurring. Nevertheless, the a-Se technology has great potential to provide breakthrough abilities such as visualization of fine details including of neuro-vascular perforator vessels and of small vascular devices.

Quantitative comparison using generalized relative object detectability (G-ROD) metrics of an amorphous selenium detector with high resolution microangiographic fluoroscopes (MAF) and standard flat panel detectors (FPD)

NASA Astrophysics Data System (ADS)

Russ, M.; Shankar, A.; Jain, A.; Setlur Nagesh, S. V.; Ionita, C. N.; Scott, C.; Karim, K. S.; Bednarek, D. R.; Rudin, S.

2016-03-01

A novel amorphous selenium (a-Se) direct detector with CMOS readout has been designed, and relative detector performance investigated. The detector features include a 25μm pixel pitch, and 1000μm thick a-Se layer operating at 10V/μm bias field. A simulated detector DQE was determined, and used in comparative calculations of the Relative Object Detectability (ROD) family of prewhitening matched-filter (PWMF) observer and non-pre-whitening matched filter (NPWMF) observer model metrics to gauge a-Se detector performance against existing high resolution micro-angiographic fluoroscopic (MAF) detectors and a standard flat panel detector (FPD). The PWMF-ROD or ROD metric compares two x-ray imaging detectors in their relative abilities in imaging a given object by taking the integral over spatial frequencies of the Fourier transform of the detector DQE weighted by an object function, divided by the comparable integral for a different detector. The generalized-ROD (G-ROD) metric incorporates clinically relevant parameters (focal- spot size, magnification, and scatter) to show the degradation in imaging performance for detectors that are part of an imaging chain. Preliminary ROD calculations using simulated spheres as the object predicted superior imaging performance by the a-Se detector as compared to existing detectors. New PWMF-G-ROD and NPWMF-G-ROD results still indicate better performance by the a-Se detector in an imaging chain over all sphere sizes for various focal spot sizes and magnifications, although a-Se performance advantages were degraded by focal spot blurring. Nevertheless, the a-Se technology has great potential to provide break- through abilities such as visualization of fine details including of neuro-vascular perforator vessels and of small vascular devices.

Quantitative comparison using Generalized Relative Object Detectability (G-ROD) metrics of an amorphous selenium detector with high resolution Microangiographic Fluoroscopes (MAF) and standard flat panel detectors (FPD)

PubMed Central

Russ, M.; Shankar, A.; Jain, A.; Setlur Nagesh, S. V.; Ionita, C. N.; Scott, C.; Karim, K. S.; Bednarek, D. R.; Rudin, S.

2017-01-01

A novel amorphous selenium (a-Se) direct detector with CMOS readout has been designed, and relative detector performance investigated. The detector features include a 25μm pixel pitch, and 1000μm thick a-Se layer operating at 10V/μm bias field. A simulated detector DQE was determined, and used in comparative calculations of the Relative Object Detectability (ROD) family of prewhitening matched-filter (PWMF) observer and non-prewhitening matched filter (NPWMF) observer model metrics to gauge a-Se detector performance against existing high resolution micro-angiographic fluoroscopic (MAF) detectors and a standard flat panel detector (FPD). The PWMF-ROD or ROD metric compares two x-ray imaging detectors in their relative abilities in imaging a given object by taking the integral over spatial frequencies of the Fourier transform of the detector DQE weighted by an object function, divided by the comparable integral for a different detector. The generalized-ROD (G-ROD) metric incorporates clinically relevant parameters (focal-spot size, magnification, and scatter) to show the degradation in imaging performance for detectors that are part of an imaging chain. Preliminary ROD calculations using simulated spheres as the object predicted superior imaging performance by the a-Se detector as compared to existing detectors. New PWMF-G-ROD and NPWMF-G-ROD results still indicate better performance by the a-Se detector in an imaging chain over all sphere sizes for various focal spot sizes and magnifications, although a-Se performance advantages were degraded by focal spot blurring. Nevertheless, the a-Se technology has great potential to provide breakthrough abilities such as visualization of fine details including of neuro-vascular perforator vessels and of small vascular devices. PMID:28615795

A semi-automated method for rapid detection of ripple events on interictal voltage discharges in the scalp electroencephalogram.

PubMed

Chu, Catherine J; Chan, Arthur; Song, Dan; Staley, Kevin J; Stufflebeam, Steven M; Kramer, Mark A

2017-02-01

High frequency oscillations are emerging as a clinically important indicator of epileptic networks. However, manual detection of these high frequency oscillations is difficult, time consuming, and subjective, especially in the scalp EEG, thus hindering further clinical exploration and application. Semi-automated detection methods augment manual detection by reducing inspection to a subset of time intervals. We propose a new method to detect high frequency oscillations that co-occur with interictal epileptiform discharges. The new method proceeds in two steps. The first step identifies candidate time intervals during which high frequency activity is increased. The second step computes a set of seven features for each candidate interval. These features require that the candidate event contain a high frequency oscillation approximately sinusoidal in shape, with at least three cycles, that co-occurs with a large amplitude discharge. Candidate events that satisfy these features are stored for validation through visual analysis. We evaluate the detector performance in simulation and on ten examples of scalp EEG data, and show that the proposed method successfully detects spike-ripple events, with high positive predictive value, low false positive rate, and high intra-rater reliability. The proposed method is less sensitive than the existing method of visual inspection, but much faster and much more reliable. Accurate and rapid detection of high frequency activity increases the clinical viability of this rhythmic biomarker of epilepsy. The proposed spike-ripple detector rapidly identifies candidate spike-ripple events, thus making clinical analysis of prolonged, multielectrode scalp EEG recordings tractable. Copyright © 2016 Elsevier B.V. All rights reserved.

A semi-automated method for rapid detection of ripple events on interictal voltage discharges in the scalp electroencephalogram

PubMed Central

Chu, Catherine. J.; Chan, Arthur; Song, Dan; Staley, Kevin J.; Stufflebeam, Steven M.; Kramer, Mark A.

2017-01-01

Summary Background High frequency oscillations are emerging as a clinically important indicator of epileptic networks. However, manual detection of these high frequency oscillations is difficult, time consuming, and subjective, especially in the scalp EEG, thus hindering further clinical exploration and application. Semi-automated detection methods augment manual detection by reducing inspection to a subset of time intervals. We propose a new method to detect high frequency oscillations that co-occur with interictal epileptiform discharges. New Method The new method proceeds in two steps. The first step identifies candidate time intervals during which high frequency activity is increased. The second step computes a set of seven features for each candidate interval. These features require that the candidate event contain a high frequency oscillation approximately sinusoidal in shape, with at least three cycles, that co-occurs with a large amplitude discharge. Candidate events that satisfy these features are stored for validation through visual analysis. Results We evaluate the detector performance in simulation and on ten examples of scalp EEG data, and show that the proposed method successfully detects spike-ripple events, with high positive predictive value, low false positive rate, and high intra-rater reliability. Comparison with Existing Method The proposed method is less sensitive than the existing method of visual inspection, but much faster and much more reliable. Conclusions Accurate and rapid detection of high frequency activity increases the clinical viability of this rhythmic biomarker of epilepsy. The proposed spike-ripple detector rapidly identifies candidate spike-ripple events, thus making clinical analysis of prolonged, multielectrode scalp EEG recordings tractable. PMID:27988323

Learned filters for object detection in multi-object visual tracking

NASA Astrophysics Data System (ADS)

Stamatescu, Victor; Wong, Sebastien; McDonnell, Mark D.; Kearney, David

2016-05-01

We investigate the application of learned convolutional filters in multi-object visual tracking. The filters were learned in both a supervised and unsupervised manner from image data using artificial neural networks. This work follows recent results in the field of machine learning that demonstrate the use learned filters for enhanced object detection and classification. Here we employ a track-before-detect approach to multi-object tracking, where tracking guides the detection process. The object detection provides a probabilistic input image calculated by selecting from features obtained using banks of generative or discriminative learned filters. We present a systematic evaluation of these convolutional filters using a real-world data set that examines their performance as generic object detectors.

Validation of Harris Detector and Eigen Features Detector

NASA Astrophysics Data System (ADS)

Kok, K. Y.; Rajendran, P.

2018-05-01

Harris detector is one of the most common features detection for applications such as object recognition, stereo matching and target tracking. In this paper, a similar Harris detector algorithm is written using MATLAB and the performance is compared with MATLAB built in Harris detector for validation. This is to ensure that rewritten version of Harris detector can be used for Unmanned Aerial Vehicle (UAV) application research purpose yet can be further improvised. Another corner detector close to Harris detector, which is Eigen features detector is rewritten and compared as well using same procedures with same purpose. The simulation results have shown that rewritten version for both Harris and Eigen features detectors have the same performance with MATLAB built in detectors with not more than 0.4% coordination deviation, less than 4% & 5% response deviation respectively, and maximum 3% computational cost error.

Neural network tracking and extension of positive tracking periods

NASA Technical Reports Server (NTRS)

Hanan, Jay C.; Chao, Tien-Hsin; Moreels, Pierre

2004-01-01

Feature detectors have been considered for the role of supplying additional information to a neural network tracker. The feature detector focuses on areas of the image with significant information. Basically, if a picture says a thousand words, the feature detectors are looking for the key phrases (keypoints). These keypoints are rotationally invariant and may be matched across frames. Application of these advanced feature detectors to the neural network tracking system at JPL has promising potential. As part of an ongoing program, an advanced feature detector was tested for augmentation of a neural network based tracker. The advance feature detector extended tracking periods in test sequences including aircraft tracking, rover tracking, and simulated Martian landing. Future directions of research are also discussed.

Neural network tracking and extension of positive tracking periods

NASA Astrophysics Data System (ADS)

Hanan, Jay C.; Chao, Tien-Hsin; Moreels, Pierre

2004-04-01

Feature detectors have been considered for the role of supplying additional information to a neural network tracker. The feature detector focuses on areas of the image with significant information. Basically, if a picture says a thousand words, the feature detectors are looking for the key phrases (keypoints). These keypoints are rotationally invariant and may be matched across frames. Application of these advanced feature detectors to the neural network tracking system at JPL has promising potential. As part of an ongoing program, an advanced feature detector was tested for augmentation of a neural network based tracker. The advance feature detector extended tracking periods in test sequences including aircraft tracking, rover tracking, and simulated Martian landing. Future directions of research are also discussed.

Jet-images — deep learning edition

DOE PAGES

de Oliveira, Luke; Kagan, Michael; Mackey, Lester; ...

2016-07-13

Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning architectures to identify highly boosted W bosons. Modern deep learning algorithms trained on jet images can out-perform standard physically-motivated feature driven approaches to jet tagging. We develop techniques for visualizing how these features are learned by the network and what additional information is used to improve performance. Finally, this interplay between physically-motivated feature driven tools and supervised learning algorithms is generalmore » and can be used to significantly increase the sensitivity to discover new particles and new forces, and gain a deeper understanding of the physics within jets.« less

Jet-images — deep learning edition

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

de Oliveira, Luke; Kagan, Michael; Mackey, Lester

Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning architectures to identify highly boosted W bosons. Modern deep learning algorithms trained on jet images can out-perform standard physically-motivated feature driven approaches to jet tagging. We develop techniques for visualizing how these features are learned by the network and what additional information is used to improve performance. Finally, this interplay between physically-motivated feature driven tools and supervised learning algorithms is generalmore » and can be used to significantly increase the sensitivity to discover new particles and new forces, and gain a deeper understanding of the physics within jets.« less

Time-frequency feature representation using multi-resolution texture analysis and acoustic activity detector for real-life speech emotion recognition.

PubMed

Wang, Kun-Ching

2015-01-14

The classification of emotional speech is mostly considered in speech-related research on human-computer interaction (HCI). In this paper, the purpose is to present a novel feature extraction based on multi-resolutions texture image information (MRTII). The MRTII feature set is derived from multi-resolution texture analysis for characterization and classification of different emotions in a speech signal. The motivation is that we have to consider emotions have different intensity values in different frequency bands. In terms of human visual perceptual, the texture property on multi-resolution of emotional speech spectrogram should be a good feature set for emotion classification in speech. Furthermore, the multi-resolution analysis on texture can give a clearer discrimination between each emotion than uniform-resolution analysis on texture. In order to provide high accuracy of emotional discrimination especially in real-life, an acoustic activity detection (AAD) algorithm must be applied into the MRTII-based feature extraction. Considering the presence of many blended emotions in real life, in this paper make use of two corpora of naturally-occurring dialogs recorded in real-life call centers. Compared with the traditional Mel-scale Frequency Cepstral Coefficients (MFCC) and the state-of-the-art features, the MRTII features also can improve the correct classification rates of proposed systems among different language databases. Experimental results show that the proposed MRTII-based feature information inspired by human visual perception of the spectrogram image can provide significant classification for real-life emotional recognition in speech.

Up-conversion of MMW radiation to visual band using glow discharge detector and silicon detector

NASA Astrophysics Data System (ADS)

Aharon Akram, Avihai; Rozban, Daniel; Abramovich, Amir; Yitzhaky, Yitzhak; Kopeika, Natan S.

2016-10-01

In this work we describe and demonstrate a method for up-conversion of millimeter wave (MMW) radiation to the visual band using a very inexpensive miniature Glow Discharge Detector (GDD), and a silicon detector (photodetector). Here we present 100 GHz up-conversion images based on measuring the visual light emitting from the GDD rather than its electrical current. The results showed better response time of 480 ns and better sensitivity compared to the electronic detection that was performed in our previous work. In this work we performed MMW imaging based on this method using a GDD lamp, and a photodetector to measure GDD light emission.

ADJUST: An automatic EEG artifact detector based on the joint use of spatial and temporal features.

PubMed

Mognon, Andrea; Jovicich, Jorge; Bruzzone, Lorenzo; Buiatti, Marco

2011-02-01

A successful method for removing artifacts from electroencephalogram (EEG) recordings is Independent Component Analysis (ICA), but its implementation remains largely user-dependent. Here, we propose a completely automatic algorithm (ADJUST) that identifies artifacted independent components by combining stereotyped artifact-specific spatial and temporal features. Features were optimized to capture blinks, eye movements, and generic discontinuities on a feature selection dataset. Validation on a totally different EEG dataset shows that (1) ADJUST's classification of independent components largely matches a manual one by experts (agreement on 95.2% of the data variance), and (2) Removal of the artifacted components detected by ADJUST leads to neat reconstruction of visual and auditory event-related potentials from heavily artifacted data. These results demonstrate that ADJUST provides a fast, efficient, and automatic way to use ICA for artifact removal. Copyright © 2010 Society for Psychophysiological Research.

Automatic Detection and Classification of Audio Events for Road Surveillance Applications.

PubMed

Almaadeed, Noor; Asim, Muhammad; Al-Maadeed, Somaya; Bouridane, Ahmed; Beghdadi, Azeddine

2018-06-06

This work investigates the problem of detecting hazardous events on roads by designing an audio surveillance system that automatically detects perilous situations such as car crashes and tire skidding. In recent years, research has shown several visual surveillance systems that have been proposed for road monitoring to detect accidents with an aim to improve safety procedures in emergency cases. However, the visual information alone cannot detect certain events such as car crashes and tire skidding, especially under adverse and visually cluttered weather conditions such as snowfall, rain, and fog. Consequently, the incorporation of microphones and audio event detectors based on audio processing can significantly enhance the detection accuracy of such surveillance systems. This paper proposes to combine time-domain, frequency-domain, and joint time-frequency features extracted from a class of quadratic time-frequency distributions (QTFDs) to detect events on roads through audio analysis and processing. Experiments were carried out using a publicly available dataset. The experimental results conform the effectiveness of the proposed approach for detecting hazardous events on roads as demonstrated by 7% improvement of accuracy rate when compared against methods that use individual temporal and spectral features.

Orientation selectivity sharpens motion detection in Drosophila

PubMed Central

Fisher, Yvette E.; Silies, Marion; Clandinin, Thomas R.

2015-01-01

SUMMARY Detecting the orientation and movement of edges in a scene is critical to visually guided behaviors of many animals. What are the circuit algorithms that allow the brain to extract such behaviorally vital visual cues? Using in vivo two-photon calcium imaging in Drosophila, we describe direction selective signals in the dendrites of T4 and T5 neurons, detectors of local motion. We demonstrate that this circuit performs selective amplification of local light inputs, an observation that constrains motion detection models and confirms a core prediction of the Hassenstein-Reichardt Correlator (HRC). These neurons are also orientation selective, responding strongly to static features that are orthogonal to their preferred axis of motion, a tuning property not predicted by the HRC. This coincident extraction of orientation and direction sharpens directional tuning through surround inhibition and reveals a striking parallel between visual processing in flies and vertebrate cortex, suggesting a universal strategy for motion processing. PMID:26456048

Automatic feature learning using multichannel ROI based on deep structured algorithms for computerized lung cancer diagnosis.

PubMed

Sun, Wenqing; Zheng, Bin; Qian, Wei

2017-10-01

This study aimed to analyze the ability of extracting automatically generated features using deep structured algorithms in lung nodule CT image diagnosis, and compare its performance with traditional computer aided diagnosis (CADx) systems using hand-crafted features. All of the 1018 cases were acquired from Lung Image Database Consortium (LIDC) public lung cancer database. The nodules were segmented according to four radiologists' markings, and 13,668 samples were generated by rotating every slice of nodule images. Three multichannel ROI based deep structured algorithms were designed and implemented in this study: convolutional neural network (CNN), deep belief network (DBN), and stacked denoising autoencoder (SDAE). For the comparison purpose, we also implemented a CADx system using hand-crafted features including density features, texture features and morphological features. The performance of every scheme was evaluated by using a 10-fold cross-validation method and an assessment index of the area under the receiver operating characteristic curve (AUC). The observed highest area under the curve (AUC) was 0.899±0.018 achieved by CNN, which was significantly higher than traditional CADx with the AUC=0.848±0.026. The results from DBN was also slightly higher than CADx, while SDAE was slightly lower. By visualizing the automatic generated features, we found some meaningful detectors like curvy stroke detectors from deep structured schemes. The study results showed the deep structured algorithms with automatically generated features can achieve desirable performance in lung nodule diagnosis. With well-tuned parameters and large enough dataset, the deep learning algorithms can have better performance than current popular CADx. We believe the deep learning algorithms with similar data preprocessing procedure can be used in other medical image analysis areas as well. Copyright © 2017. Published by Elsevier Ltd.

Assessment of a simple obstacle detection device for the visually impaired.

PubMed

Lee, Cheng-Lung; Chen, Chih-Yung; Sung, Peng-Cheng; Lu, Shih-Yi

2014-07-01

A simple obstacle detection device, based upon an automobile parking sensor, was assessed as a mobility aid for the visually impaired. A questionnaire survey for mobility needs was performed at the start of this study. After the detector was developed, five blindfolded sighted and 15 visually impaired participants were invited to conduct travel experiments under three test conditions: (1) using a white cane only, (2) using the obstacle detector only and (3) using both devices. A post-experiment interview regarding the usefulness of the obstacle detector for the visually impaired participants was performed. The results showed that the obstacle detector could augment mobility performance with the white cane. The obstacle detection device should be used in conjunction with the white cane to achieve the best mobility speed and body protection. Copyright © 2013 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Ventral-stream-like shape representation: from pixel intensity values to trainable object-selective COSFIRE models

PubMed Central

Azzopardi, George; Petkov, Nicolai

2014-01-01

The remarkable abilities of the primate visual system have inspired the construction of computational models of some visual neurons. We propose a trainable hierarchical object recognition model, which we call S-COSFIRE (S stands for Shape and COSFIRE stands for Combination Of Shifted FIlter REsponses) and use it to localize and recognize objects of interests embedded in complex scenes. It is inspired by the visual processing in the ventral stream (V1/V2 → V4 → TEO). Recognition and localization of objects embedded in complex scenes is important for many computer vision applications. Most existing methods require prior segmentation of the objects from the background which on its turn requires recognition. An S-COSFIRE filter is automatically configured to be selective for an arrangement of contour-based features that belong to a prototype shape specified by an example. The configuration comprises selecting relevant vertex detectors and determining certain blur and shift parameters. The response is computed as the weighted geometric mean of the blurred and shifted responses of the selected vertex detectors. S-COSFIRE filters share similar properties with some neurons in inferotemporal cortex, which provided inspiration for this work. We demonstrate the effectiveness of S-COSFIRE filters in two applications: letter and keyword spotting in handwritten manuscripts and object spotting in complex scenes for the computer vision system of a domestic robot. S-COSFIRE filters are effective to recognize and localize (deformable) objects in images of complex scenes without requiring prior segmentation. They are versatile trainable shape detectors, conceptually simple and easy to implement. The presented hierarchical shape representation contributes to a better understanding of the brain and to more robust computer vision algorithms. PMID:25126068

Characterization of selected elementary motion detector cells to image primitives.

PubMed

Benson, Leslie A; Barrett, Steven F; Wright, Cameron H G

2008-01-01

Developing a visual sensing system, complete with motion processing hardware and software would have many applications to current technology. It could be mounted on many autonomous vehicles to provide information about the navigational environment, as well as obstacle avoidance features. Incorporating the motion processing capabilities into the sensor requires a new approach to the algorithm implementation. This research, and that of many others, have turned to nature for inspiration. Elementary motion detector (EMD) cells are involved in a biological preprocessing network to provide information to the motion processing lobes of the house degrees y Musca domestica. This paper describes the response of the photoreceptor inputs to the EMDs. The inputs to the EMD components are tested as they are stimulated with varying image primitives. This is the first of many steps in characterizing the EMD response to image primitives.

Time-Frequency Feature Representation Using Multi-Resolution Texture Analysis and Acoustic Activity Detector for Real-Life Speech Emotion Recognition

PubMed Central

Wang, Kun-Ching

2015-01-01

The classification of emotional speech is mostly considered in speech-related research on human-computer interaction (HCI). In this paper, the purpose is to present a novel feature extraction based on multi-resolutions texture image information (MRTII). The MRTII feature set is derived from multi-resolution texture analysis for characterization and classification of different emotions in a speech signal. The motivation is that we have to consider emotions have different intensity values in different frequency bands. In terms of human visual perceptual, the texture property on multi-resolution of emotional speech spectrogram should be a good feature set for emotion classification in speech. Furthermore, the multi-resolution analysis on texture can give a clearer discrimination between each emotion than uniform-resolution analysis on texture. In order to provide high accuracy of emotional discrimination especially in real-life, an acoustic activity detection (AAD) algorithm must be applied into the MRTII-based feature extraction. Considering the presence of many blended emotions in real life, in this paper make use of two corpora of naturally-occurring dialogs recorded in real-life call centers. Compared with the traditional Mel-scale Frequency Cepstral Coefficients (MFCC) and the state-of-the-art features, the MRTII features also can improve the correct classification rates of proposed systems among different language databases. Experimental results show that the proposed MRTII-based feature information inspired by human visual perception of the spectrogram image can provide significant classification for real-life emotional recognition in speech. PMID:25594590

Visual grading analysis of digital neonatal chest phantom X-ray images: Impact of detector type, dose and image processing on image quality.

PubMed

Smet, M H; Breysem, L; Mussen, E; Bosmans, H; Marshall, N W; Cockmartin, L

2018-07-01

To evaluate the impact of digital detector, dose level and post-processing on neonatal chest phantom X-ray image quality (IQ). A neonatal phantom was imaged using four different detectors: a CR powder phosphor (PIP), a CR needle phosphor (NIP) and two wireless CsI DR detectors (DXD and DRX). Five different dose levels were studied for each detector and two post-processing algorithms evaluated for each vendor. Three paediatric radiologists scored the images using European quality criteria plus additional questions on vascular lines, noise and disease simulation. Visual grading characteristics and ordinal regression statistics were used to evaluate the effect of detector type, post-processing and dose on VGA score (VGAS). No significant differences were found between the NIP, DXD and CRX detectors (p>0.05) whereas the PIP detector had significantly lower VGAS (p< 0.0001). Processing did not influence VGAS (p=0.819). Increasing dose resulted in significantly higher VGAS (p<0.0001). Visual grading analysis (VGA) identified a detector air kerma/image (DAK/image) of ~2.4 μGy as an ideal working point for NIP, DXD and DRX detectors. VGAS tracked IQ differences between detectors and dose levels but not image post-processing changes. VGA showed a DAK/image value above which perceived IQ did not improve, potentially useful for commissioning. • A VGA study detects IQ differences between detectors and dose levels. • The NIP detector matched the VGAS of the CsI DR detectors. • VGA data are useful in setting initial detector air kerma level. • Differences in NNPS were consistent with changes in VGAS.

46 CFR 15.855 - Cabin watchmen and fire patrolmen.

Code of Federal Regulations, 2013 CFR

2013-10-01

... of fire detectors, heat detectors, smoke detectors, and high-water alarms with audible- and visual... conditions are met: (1) Fire detectors are located in each space containing machinery or fuel tanks per § 181... extraction hood per § 181.425 of this chapter. (3) Heat and/or smoke detectors are located in each galley...

46 CFR 15.855 - Cabin watchmen and fire patrolmen.

Code of Federal Regulations, 2011 CFR

2011-10-01

... of fire detectors, heat detectors, smoke detectors, and high-water alarms with audible- and visual... conditions are met: (1) Fire detectors are located in each space containing machinery or fuel tanks per § 181... extraction hood per § 181.425 of this chapter. (3) Heat and/or smoke detectors are located in each galley...

46 CFR 15.855 - Cabin watchmen and fire patrolmen.

Code of Federal Regulations, 2012 CFR

2012-10-01

... of fire detectors, heat detectors, smoke detectors, and high-water alarms with audible- and visual... conditions are met: (1) Fire detectors are located in each space containing machinery or fuel tanks per § 181... extraction hood per § 181.425 of this chapter. (3) Heat and/or smoke detectors are located in each galley...

Multi-Detector Row Computed Tomography Findings of Pelvic Congestion Syndrome Caused by Dilated Ovarian Veins

PubMed Central

Eren, Suat

2010-01-01

Objective: To evaluate the efficacy of multi-detector row CT (MDCT) on pelvic congestion syndrome (PCS), which is often overlooked or poorly visualized with routine imaging examination. Materials and Methods: We evaluated the MDCT features of 40 patients with PCS (mean age, 45 years; range, 29–60 years) using axial, coronal, sagittal, 3D volume-rendered, and Maximum Intensity Projection MIP images. Results: MDCT revealed pelvic varices and ovarian vein dilatations in all patients. Bilateral ovarian vein dilatation was present in 25 patients, and 15 patients had unilateral dilatation. While 12 cases of secondary pelvic varices occurred simultaneously with a retroaortic left renal vein, 10 cases were due solely to a mass obstruction or stenosis of venous structures. Conclusion: MDCT is an effective tool in the evaluation of PCS, and it has more advantages than other imaging modalities. PMID:25610142

Saliency image of feature building for image quality assessment

NASA Astrophysics Data System (ADS)

Ju, Xinuo; Sun, Jiyin; Wang, Peng

2011-11-01

The purpose and method of image quality assessment are quite different for automatic target recognition (ATR) and traditional application. Local invariant feature detectors, mainly including corner detectors, blob detectors and region detectors etc., are widely applied for ATR. A saliency model of feature was proposed to evaluate feasibility of ATR in this paper. The first step consisted of computing the first-order derivatives on horizontal orientation and vertical orientation, and computing DoG maps in different scales respectively. Next, saliency images of feature were built based auto-correlation matrix in different scale. Then, saliency images of feature of different scales amalgamated. Experiment were performed on a large test set, including infrared images and optical images, and the result showed that the salient regions computed by this model were consistent with real feature regions computed by mostly local invariant feature extraction algorithms.

Testing of Haar-Like Feature in Region of Interest Detection for Automated Target Recognition (ATR) System

NASA Technical Reports Server (NTRS)

Zhang, Yuhan; Lu, Dr. Thomas

2010-01-01

The objectives of this project were to develop a ROI (Region of Interest) detector using Haar-like feature similar to the face detection in Intel's OpenCV library, implement it in Matlab code, and test the performance of the new ROI detector against the existing ROI detector that uses Optimal Trade-off Maximum Average Correlation Height filter (OTMACH). The ROI detector included 3 parts: 1, Automated Haar-like feature selection in finding a small set of the most relevant Haar-like features for detecting ROIs that contained a target. 2, Having the small set of Haar-like features from the last step, a neural network needed to be trained to recognize ROIs with targets by taking the Haar-like features as inputs. 3, using the trained neural network from the last step, a filtering method needed to be developed to process the neural network responses into a small set of regions of interests. This needed to be coded in Matlab. All the 3 parts needed to be coded in Matlab. The parameters in the detector needed to be trained by machine learning and tested with specific datasets. Since OpenCV library and Haar-like feature were not available in Matlab, the Haar-like feature calculation needed to be implemented in Matlab. The codes for Adaptive Boosting and max/min filters in Matlab could to be found from the Internet but needed to be integrated to serve the purpose of this project. The performance of the new detector was tested by comparing the accuracy and the speed of the new detector against the existing OTMACH detector. The speed was referred as the average speed to find the regions of interests in an image. The accuracy was measured by the number of false positives (false alarms) at the same detection rate between the two detectors.

Three Small-Receptive-Field Ganglion Cells in the Mouse Retina Are Distinctly Tuned to Size, Speed, and Object Motion

PubMed Central

Jacoby, Jason

2017-01-01

Retinal ganglion cells (RGCs) are frequently divided into functional types by their ability to extract and relay specific features from a visual scene, such as the capacity to discern local or global motion, direction of motion, stimulus orientation, contrast or uniformity, or the presence of large or small objects. Here we introduce three previously uncharacterized, nondirection-selective ON–OFF RGC types that represent a distinct set of feature detectors in the mouse retina. The three high-definition (HD) RGCs possess small receptive-field centers and strong surround suppression. They respond selectively to objects of specific sizes, speeds, and types of motion. We present comprehensive morphological characterization of the HD RGCs and physiological recordings of their light responses, receptive-field size and structure, and synaptic mechanisms of surround suppression. We also explore the similarities and differences between the HD RGCs and a well characterized RGC with a comparably small receptive field, the local edge detector, in response to moving objects and textures. We model populations of each RGC type to study how they differ in their performance tracking a moving object. These results, besides introducing three new RGC types that together constitute a substantial fraction of mouse RGCs, provide insights into the role of different circuits in shaping RGC receptive fields and establish a foundation for continued study of the mechanisms of surround suppression and the neural basis of motion detection. SIGNIFICANCE STATEMENT The output cells of the retina, retinal ganglion cells (RGCs), are a diverse group of ∼40 distinct neuron types that are often assigned “feature detection” profiles based on the specific aspects of the visual scene to which they respond. Here we describe, for the first time, morphological and physiological characterization of three new RGC types in the mouse retina, substantially augmenting our understanding of feature selectivity. Experiments and modeling show that while these three “high-definition” RGCs share certain receptive-field properties, they also have distinct tuning to the size, speed, and type of motion on the retina, enabling them to occupy different niches in stimulus space. PMID:28100743

46 CFR 15.855 - Cabin watchmen and fire patrolmen.

Code of Federal Regulations, 2014 CFR

2014-10-01

... of an uninspected passenger vessel not more than 300 GRT may substitute the use of fire detectors, heat detectors, smoke detectors, and high-water alarms with audible- and visual-warning indicators, in... detectors are located in each space containing machinery or fuel tanks per § 181.400(c) of this chapter. (2...

Detecting bursts in the EEG of very and extremely premature infants using a multi-feature approach.

PubMed

O'Toole, John M; Boylan, Geraldine B; Lloyd, Rhodri O; Goulding, Robert M; Vanhatalo, Sampsa; Stevenson, Nathan J

2017-07-01

To develop a method that segments preterm EEG into bursts and inter-bursts by extracting and combining multiple EEG features. Two EEG experts annotated bursts in individual EEG channels for 36 preterm infants with gestational age < 30 weeks. The feature set included spectral, amplitude, and frequency-weighted energy features. Using a consensus annotation, feature selection removed redundant features and a support vector machine combined features. Area under the receiver operator characteristic (AUC) and Cohen's kappa (κ) evaluated performance within a cross-validation procedure. The proposed channel-independent method improves AUC by 4-5% over existing methods (p < 0.001, n=36), with median (95% confidence interval) AUC of 0.989 (0.973-0.997) and sensitivity-specificity of 95.8-94.4%. Agreement rates between the detector and experts' annotations, κ=0.72 (0.36-0.83) and κ=0.65 (0.32-0.81), are comparable to inter-rater agreement, κ=0.60 (0.21-0.74). Automating the visual identification of bursts in preterm EEG is achievable with a high level of accuracy. Multiple features, combined using a data-driven approach, improves on existing single-feature methods. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Methods of Forming Visual Hydrogen Detector with Variable Reversibility

NASA Technical Reports Server (NTRS)

Muradov, Nazim Z. (Inventor)

2014-01-01

Methods, processes and compositions are provided for a visual or chemochromic hydrogen-detector with variable or tunable reversible color change. The working temperature range for the hydrogen detector is from minus 100 C to plus 500 C. A hydrogen-sensitive pigment, including, but not limited to, oxides, hydroxides and polyoxo-compounds of tungsten, molybdenum, vanadium, chromium and combinations thereof, is combined with nano-sized metal activator particles and preferably, coated on a porous or woven substrate. In the presence of hydrogen, the composition rapidly changes its color from white or light-gray or light-tan to dark gray, navy-blue or black depending on the exposure time and hydrogen concentration in the medium. After hydrogen exposure ceases, the original color of the hydrogen-sensitive pigment is restored, and the visual hydrogen detector can be used repeatedly. By changing the composition of the hydrogen-sensitive pigment, the time required for its complete regeneration is varied from a few seconds to several days.

Visual hydrogen detector with variable reversibility

NASA Technical Reports Server (NTRS)

Muradov, Nazim (Inventor)

2011-01-01

Methods, processes and compositions are provided for a visual or chemochromic hydrogen-detector with variable or tunable reversible color change. The working temperature range for the hydrogen detector is from minus 100.degree. C. to plus 500.degree. C. A hydrogen-sensitive pigment, including, but not limited to, oxides, hydroxides and polyoxo-compounds of tungsten, molybdenum, vanadium, chromium and combinations thereof, is combined with nano-sized metal activator particles and preferably, coated on a porous or woven substrate. In the presence of hydrogen, the composition rapidly changes its color from white or light-gray or light-tan to dark gray, navy-blue or black depending on the exposure time and hydrogen concentration in the medium. After hydrogen exposure ceases, the original color of the hydrogen-sensitive pigment is restored, and the visual hydrogen detector can be used repeatedly. By changing the composition of the hydrogen-sensitive pigment, the time required for its complete regeneration is varied from a few seconds to several days.

Visual hydrogen detector with variable reversibilty

NASA Technical Reports Server (NTRS)

Muradov, Nazim Z. (Inventor)

2012-01-01

Methods, processes and compositions are provided for a visual or chemochromic hydrogen-detector with variable or tunable reversible color change. The working temperature range for the hydrogen detector is from minus 100.degree. C. to plus 500.degree. C. A hydrogen-sensitive pigment, including, but not limited to, oxides, hydroxides and polyoxo-compounds of tungsten, molybdenum, vanadium, chromium and combinations thereof, is combined with nano-sized metal activator particles and preferably, coated on a porous or woven substrate. In the presence of hydrogen, the composition rapidly changes its color from white or light-gray or light-tan to dark gray, navy-blue or black depending on the exposure time and hydrogen concentration in the medium. After hydrogen exposure ceases, the original color of the hydrogen-sensitive pigment is restored, and the visual hydrogen detector can be used repeatedly. By changing the composition of the hydrogen-sensitive pigment, the time required for its complete regeneration is varied from a few seconds to several days.

Attention and apparent motion.

PubMed

Horowitz, T; Treisman, A

1994-01-01

Two dissociations between short- and long-range motion in visual search are reported. Previous research has shown parallel processing for short-range motion and apparently serial processing for long-range motion. This finding has been replicated and it has also been found that search for short-range targets can be impaired both by using bicontrast stimuli, and by prior adaptation to the target direction of motion. Neither factor impaired search in long-range motion displays. Adaptation actually facilitated search with long-range displays, which is attributed to response-level effects. A feature-integration account of apparent motion is proposed. In this theory, short-range motion depends on specialized motion feature detectors operating in parallel across the display, but subject to selective adaptation, whereas attention is needed to link successive elements when they appear at greater separations, or across opposite contrasts.

Chip-scale hermetic feedthroughs for implantable bionics.

PubMed

Guenther, Thomas; Dodds, Christopher W D; Lovell, Nigel H; Suaning, Gregg J

2011-01-01

Most implantable medical devices such as cochlear implants and visual prostheses require protection of the stimulating electronics. This is achieved by way of a hermetic feedthrough system which typically features three important attributes: biocompatibility with the human body, device hermeticity and density of feedthrough conductors. On the quest for building a visual neuroprosthesis, a high number of stimulating channels is required. This has encouraged new technologies with higher rates of production yield and further miniaturization. An Al(2)O(3) based feedthrough system has been developed comprising up to 20 platinum feedthroughs per square millimeter. Ceramics substrates are shown to have leak rates below 1 × 10(-12) atm × cc/s, thus exceeding the resolution limits of most commercially available leak detectors. A sheet resistance of 0.05 Ω can be achieved. This paper describes the design, fabrication process and hermeticity testing of high density feedthroughs for use in neuroprosthetic implants.

Modeling and evaluation of a high-resolution CMOS detector for cone-beam CT of the extremities.

PubMed

Cao, Qian; Sisniega, Alejandro; Brehler, Michael; Stayman, J Webster; Yorkston, John; Siewerdsen, Jeffrey H; Zbijewski, Wojciech

2018-01-01

Quantitative assessment of trabecular bone microarchitecture in extremity cone-beam CT (CBCT) would benefit from the high spatial resolution, low electronic noise, and fast scan time provided by complementary metal-oxide semiconductor (CMOS) x-ray detectors. We investigate the performance of CMOS sensors in extremity CBCT, in particular with respect to potential advantages of thin (<0.7 mm) scintillators offering higher spatial resolution. A cascaded systems model of a CMOS x-ray detector incorporating the effects of CsI:Tl scintillator thickness was developed. Simulation studies were performed using nominal extremity CBCT acquisition protocols (90 kVp, 0.126 mAs/projection). A range of scintillator thickness (0.35-0.75 mm), pixel size (0.05-0.4 mm), focal spot size (0.05-0.7 mm), magnification (1.1-2.1), and dose (15-40 mGy) was considered. The detectability index was evaluated for both CMOS and a-Si:H flat-panel detector (FPD) configurations for a range of imaging tasks emphasizing spatial frequencies associated with feature size aobj. Experimental validation was performed on a CBCT test bench in the geometry of a compact orthopedic CBCT system (SAD = 43.1 cm, SDD = 56.0 cm, matching that of the Carestream OnSight 3D system). The test-bench studies involved a 0.3 mm focal spot x-ray source and two CMOS detectors (Dalsa Xineos-3030HR, 0.099 mm pixel pitch) - one with the standard CsI:Tl thickness of 0.7 mm (C700) and one with a custom 0.4 mm thick scintillator (C400). Measurements of modulation transfer function (MTF), detective quantum efficiency (DQE), and CBCT scans of a cadaveric knee (15 mGy) were obtained for each detector. Optimal detectability for high-frequency tasks (feature size of ~0.06 mm, consistent with the size of trabeculae) was ~4× for the C700 CMOS detector compared to the a-Si:H FPD at nominal system geometry of extremity CBCT. This is due to ~5× lower electronic noise of a CMOS sensor, which enables input quantum-limited imaging at smaller pixel size. Optimal pixel size for high-frequency tasks was <0.1 mm for a CMOS, compared to ~0.14 mm for an a-Si:H FPD. For this fine pixel pitch, detectability of fine features could be improved by using a thinner scintillator to reduce light spread blur. A 22% increase in detectability of 0.06 mm features was found for the C400 configuration compared to C700. An improvement in the frequency at 50% modulation (f 50 ) of MTF was measured, increasing from 1.8 lp/mm for C700 to 2.5 lp/mm for C400. The C400 configuration also achieved equivalent or better DQE as C700 for frequencies above ~2 mm -1 . Images of cadaver specimens confirmed improved visualization of trabeculae with the C400 sensor. The small pixel size of CMOS detectors yields improved performance in high-resolution extremity CBCT compared to a-Si:H FPDs, particularly when coupled with a custom 0.4 mm thick scintillator. The results indicate that adoption of a CMOS detector in extremity CBCT can benefit applications in quantitative imaging of trabecular microstructure in humans. © 2017 American Association of Physicists in Medicine.

Experience improves feature extraction in Drosophila.

PubMed

Peng, Yueqing; Xi, Wang; Zhang, Wei; Zhang, Ke; Guo, Aike

2007-05-09

Previous exposure to a pattern in the visual scene can enhance subsequent recognition of that pattern in many species from honeybees to humans. However, whether previous experience with a visual feature of an object, such as color or shape, can also facilitate later recognition of that particular feature from multiple visual features is largely unknown. Visual feature extraction is the ability to select the key component from multiple visual features. Using a visual flight simulator, we designed a novel protocol for visual feature extraction to investigate the effects of previous experience on visual reinforcement learning in Drosophila. We found that, after conditioning with a visual feature of objects among combinatorial shape-color features, wild-type flies exhibited poor ability to extract the correct visual feature. However, the ability for visual feature extraction was greatly enhanced in flies trained previously with that visual feature alone. Moreover, we demonstrated that flies might possess the ability to extract the abstract category of "shape" but not a particular shape. Finally, this experience-dependent feature extraction is absent in flies with defective MBs, one of the central brain structures in Drosophila. Our results indicate that previous experience can enhance visual feature extraction in Drosophila and that MBs are required for this experience-dependent visual cognition.

Effective real-time vehicle tracking using discriminative sparse coding on local patches

NASA Astrophysics Data System (ADS)

Chen, XiangJun; Ye, Feiyue; Ruan, Yaduan; Chen, Qimei

2016-01-01

A visual tracking framework that provides an object detector and tracker, which focuses on effective and efficient visual tracking in surveillance of real-world intelligent transport system applications, is proposed. The framework casts the tracking task as problems of object detection, feature representation, and classification, which is different from appearance model-matching approaches. Through a feature representation of discriminative sparse coding on local patches called DSCLP, which trains a dictionary on local clustered patches sampled from both positive and negative datasets, the discriminative power and robustness has been improved remarkably, which makes our method more robust to a complex realistic setting with all kinds of degraded image quality. Moreover, by catching objects through one-time background subtraction, along with offline dictionary training, computation time is dramatically reduced, which enables our framework to achieve real-time tracking performance even in a high-definition sequence with heavy traffic. Experiment results show that our work outperforms some state-of-the-art methods in terms of speed, accuracy, and robustness and exhibits increased robustness in a complex real-world scenario with degraded image quality caused by vehicle occlusion, image blur of rain or fog, and change in viewpoint or scale.

A Role for MST Neurons in Heading Estimation

NASA Technical Reports Server (NTRS)

Stone, L. S.; Perrone, J. A.

1994-01-01

A template model of human visual self-motion perception, which uses neurophysiologically realistic "heading detectors", is consistent with numerous human psychophysical results including the failure of humans to estimate their heading (direction of forward translation) accurately under certain visual conditions. We tested the model detectors with stimuli used by others in single-unit studies. The detectors showed emergent properties similar to those of MST neurons: (1) Sensitivity to non-preferred flow; Each detector is tuned to a specific combination of flow components and its response is systematically reduced by the addition of nonpreferred flow, and (2) Position invariance; The detectors maintain their apparent preference for particular flow components over large regions of their receptive fields. It has been argued that this latter property is incompatible with MST playing a role in heading perception. The model however demonstrates how neurons with the above response properties could still support accurate heading estimation within extrastriate cortical maps.

Lab-based x-ray nanoCT imaging

NASA Astrophysics Data System (ADS)

Müller, Mark; Allner, Sebastian; Ferstl, Simone; Dierolf, Martin; Tuohimaa, Tomi; Pfeiffer, Franz

2017-03-01

Due to the recent development of transmission X-ray tubes with very small focal spot sizes, laboratory-based CT imaging with sub-micron resolutions is nowadays possible. We recently developed a novel X-ray nanoCT setup featuring a prototype nanofocus X-ray source and a single-photon counting detector. The system is based on mere geometrical magnification and can reach resolutions of 200 nm. To demonstrate the potential of the nanoCT system for biomedical applications we show high resolution nanoCT data of a small piece of human tooth comprising coronal dentin. The reconstructed CT data clearly visualize the dentin tubules within the tooth piece.

The effect of defect cluster size and interpolation on radiographic image quality

NASA Astrophysics Data System (ADS)

Töpfer, Karin; Yip, Kwok L.

2011-03-01

For digital X-ray detectors, the need to control factory yield and cost invariably leads to the presence of some defective pixels. Recently, a standard procedure was developed to identify such pixels for industrial applications. However, no quality standards exist in medical or industrial imaging regarding the maximum allowable number and size of detector defects. While the answer may be application specific, the minimum requirement for any defect specification is that the diagnostic quality of the images be maintained. A more stringent criterion is to keep any changes in the images due to defects below the visual threshold. Two highly sensitive image simulation and evaluation methods were employed to specify the fraction of allowable defects as a function of defect cluster size in general radiography. First, the most critical situation of the defect being located in the center of the disease feature was explored using image simulation tools and a previously verified human observer model, incorporating a channelized Hotelling observer. Detectability index d' was obtained as a function of defect cluster size for three different disease features on clinical lung and extremity backgrounds. Second, four concentrations of defects of four different sizes were added to clinical images with subtle disease features and then interpolated. Twenty observers evaluated the images against the original on a single display using a 2-AFC method, which was highly sensitive to small changes in image detail. Based on a 50% just-noticeable difference, the fraction of allowed defects was specified vs. cluster size.

Neural mechanisms underlying sensitivity to reverse-phi motion in the fly

PubMed Central

Meier, Matthias; Serbe, Etienne; Eichner, Hubert; Borst, Alexander

2017-01-01

Optical illusions provide powerful tools for mapping the algorithms and circuits that underlie visual processing, revealing structure through atypical function. Of particular note in the study of motion detection has been the reverse-phi illusion. When contrast reversals accompany discrete movement, detected direction tends to invert. This occurs across a wide range of organisms, spanning humans and invertebrates. Here, we map an algorithmic account of the phenomenon onto neural circuitry in the fruit fly Drosophila melanogaster. Through targeted silencing experiments in tethered walking flies as well as electrophysiology and calcium imaging, we demonstrate that ON- or OFF-selective local motion detector cells T4 and T5 are sensitive to certain interactions between ON and OFF. A biologically plausible detector model accounts for subtle features of this particular form of illusory motion reversal, like the re-inversion of turning responses occurring at extreme stimulus velocities. In light of comparable circuit architecture in the mammalian retina, we suggest that similar mechanisms may apply even to human psychophysics. PMID:29261684

Neural mechanisms underlying sensitivity to reverse-phi motion in the fly.

PubMed

Leonhardt, Aljoscha; Meier, Matthias; Serbe, Etienne; Eichner, Hubert; Borst, Alexander

2017-01-01

Optical illusions provide powerful tools for mapping the algorithms and circuits that underlie visual processing, revealing structure through atypical function. Of particular note in the study of motion detection has been the reverse-phi illusion. When contrast reversals accompany discrete movement, detected direction tends to invert. This occurs across a wide range of organisms, spanning humans and invertebrates. Here, we map an algorithmic account of the phenomenon onto neural circuitry in the fruit fly Drosophila melanogaster. Through targeted silencing experiments in tethered walking flies as well as electrophysiology and calcium imaging, we demonstrate that ON- or OFF-selective local motion detector cells T4 and T5 are sensitive to certain interactions between ON and OFF. A biologically plausible detector model accounts for subtle features of this particular form of illusory motion reversal, like the re-inversion of turning responses occurring at extreme stimulus velocities. In light of comparable circuit architecture in the mammalian retina, we suggest that similar mechanisms may apply even to human psychophysics.

A real negative selection algorithm with evolutionary preference for anomaly detection

NASA Astrophysics Data System (ADS)

Yang, Tao; Chen, Wen; Li, Tao

2017-04-01

Traditional real negative selection algorithms (RNSAs) adopt the estimated coverage (c0) as the algorithm termination threshold, and generate detectors randomly. With increasing dimensions, the data samples could reside in the low-dimensional subspace, so that the traditional detectors cannot effectively distinguish these samples. Furthermore, in high-dimensional feature space, c0 cannot exactly reflect the detectors set coverage rate for the nonself space, and it could lead the algorithm to be terminated unexpectedly when the number of detectors is insufficient. These shortcomings make the traditional RNSAs to perform poorly in high-dimensional feature space. Based upon "evolutionary preference" theory in immunology, this paper presents a real negative selection algorithm with evolutionary preference (RNSAP). RNSAP utilizes the "unknown nonself space", "low-dimensional target subspace" and "known nonself feature" as the evolutionary preference to guide the generation of detectors, thus ensuring the detectors can cover the nonself space more effectively. Besides, RNSAP uses redundancy to replace c0 as the termination threshold, in this way RNSAP can generate adequate detectors under a proper convergence rate. The theoretical analysis and experimental result demonstrate that, compared to the classical RNSA (V-detector), RNSAP can achieve a higher detection rate, but with less detectors and computing cost.

Novel drift structures for silicon and compound semiconductor X-ray and gamma-ray detectors

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

Patt, B.E.; Iwanczyk, J.S.

Recently developed silicon- and compound-semiconductor-based drift detector structures have produced excellent performance for charged particles, X-rays, and gamma rays and for low-signal visible light detection. The silicon drift detector (SDD) structures that the authors discuss relate to direct X-ray detectors and scintillation photon detectors coupled with scintillators for gamma rays. Recent designs include several novel features that ensure very low dark current and hence low noise. In addition, application of thin window technology ensures a very high quantum efficiency entrance window on the drift photodetector. The main features of the silicon drift structures for X rays and light detection aremore » very small anode capacitance independent of the overall detector size, low noise, and high throughput. To take advantage of the small detector capacitance, the first stage of the electronics needs to be integrated into the detector anode. In the gamma-ray application, factors other than electronic noise dominate, and there is no need to integrate the electronics into the anode. Thus, a different drift structure is needed in conjunction with a high-Z material. The main features in this case are large active detector volume and electron-only induced signal.« less

Fast Detector/First Responder: Interactions between the Superior Colliculus-Pulvinar Pathway and Stimuli Relevant to Primates

PubMed Central

Soares, Sandra C.; Maior, Rafael S.; Isbell, Lynne A.; Tomaz, Carlos; Nishijo, Hisao

2017-01-01

Primates are distinguished from other mammals by their heavy reliance on the visual sense, which occurred as a result of natural selection continually favoring those individuals whose visual systems were more responsive to challenges in the natural world. Here we describe two independent but also interrelated visual systems, one cortical and the other subcortical, both of which have been modified and expanded in primates for different functions. Available evidence suggests that while the cortical visual system mainly functions to give primates the ability to assess and adjust to fluid social and ecological environments, the subcortical visual system appears to function as a rapid detector and first responder when time is of the essence, i.e., when survival requires very quick action. We focus here on the subcortical visual system with a review of behavioral and neurophysiological evidence that demonstrates its sensitivity to particular, often emotionally charged, ecological and social stimuli, i.e., snakes and fearful and aggressive facial expressions in conspecifics. We also review the literature on subcortical involvement during another, less emotional, situation that requires rapid detection and response—visually guided reaching and grasping during locomotion—to further emphasize our argument that the subcortical visual system evolved as a rapid detector/first responder, a function that remains in place today. Finally, we argue that investigating deficits in this subcortical system may provide greater understanding of Parkinson's disease and Autism Spectrum disorders (ASD). PMID:28261046

Collision detection in complex dynamic scenes using an LGMD-based visual neural network with feature enhancement.

PubMed

Yue, Shigang; Rind, F Claire

2006-05-01

The lobula giant movement detector (LGMD) is an identified neuron in the locust brain that responds most strongly to the images of an approaching object such as a predator. Its computational model can cope with unpredictable environments without using specific object recognition algorithms. In this paper, an LGMD-based neural network is proposed with a new feature enhancement mechanism to enhance the expanded edges of colliding objects via grouped excitation for collision detection with complex backgrounds. The isolated excitation caused by background detail will be filtered out by the new mechanism. Offline tests demonstrated the advantages of the presented LGMD-based neural network in complex backgrounds. Real time robotics experiments using the LGMD-based neural network as the only sensory system showed that the system worked reliably in a wide range of conditions; in particular, the robot was able to navigate in arenas with structured surrounds and complex backgrounds.

The efficacy of 320-detector row computed tomography for the assessment of preoperative pulmonary vasculature of candidates for pulmonary segmentectomy.

PubMed

Tane, Shinya; Ohno, Yoshiharu; Hokka, Daisuke; Ogawa, Hiroyuki; Tauchi, Shunsuke; Nishio, Wataru; Yoshimura, Masahiro; Okita, Yutaka; Maniwa, Yoshimasa

2013-12-01

The purpose of this study was to compare the efficacy of 320-detector row computed tomography (CT) with that of 64-detector row CT for three-dimensional assessment of pulmonary vasculature of candidates for pulmonary segmentectomy. We included 32 patients who underwent both 320- and 64-detector CT before pulmonary segmentectomy, which was performed by cutting the pulmonary artery and bronchi of the affected segment followed by dissection of the intersegmental plane along the intersegmental vein. Before the operation, three-dimensional pulmonary vasculature images were obtained for each patient, and the arteries and intersegmental veins of the affected segments were identified. Two thoracic surgeons independently assessed the vessels with visual scoring systems, and kappa analysis was used to determine interobserver agreement. The Wilcoxon signed-rank test was used to compare the visual scores for the assessment of the visualization capabilities of the two methods. In addition, the final determination of pulmonary vasculature at a given site was made by consensus from thoracic surgeons during operation, and receiver operating characteristic analysis was performed to compare their efficacy of pulmonary vasculature assessment. Sensitivity, specificity and accuracy of either method were also compared by means of McNemar's test. Of the 32 cases, there were no operative complications, but 1 patient died of postoperative idiopathic interstitial pneumonia. Visualization scores for the pulmonary vessels were significantly higher for 320- than those for 64-detector CT (P < 0.0001 for the affected arteries and P < 0.0001 for the intersegmental veins). As for pulmonary vasculature assessment, the areas under the curve showed no statistically significant differences in between the two methods, while the specificity and accuracy of intersegemental vein assessment were significantly better for 320- than those for 64-detector row CT (P < 0.05). Interobserver agreement for the assessment yielded by either method was almost perfect for all cases. Three hundred and twenty-detector row CT is more useful than conventional 64-detector row CT for preoperative three-dimensional assessment of pulmonary vasculature, especially when we identify the intersegmental veins, in candidates for pulmonary segmentectomy.

Particle Detectors and Data Analysis for Cusp Transient Features Campaign

NASA Technical Reports Server (NTRS)

Sharber, J. R.

1998-01-01

Grant NAG5-5084 was awarded to support the participation of South West Research Institute (SwRI) in building the energy per unit charge particle detectors for the Cusp Transient Features Campaign and analysis of flight data from these instruments. The detectors are part of an instrumented payload (Rocket 36.152, Dr. R. Pfaff, P.I.) launched from Svalbard on December 3, 1997, into the dark cusp. The particle instruments, a Cusp Electron Detector (CED) and a Cusp Ion Detector (CID), built on this project, provided differential energy and angular measurements along the rocket trajectory throughout the flight.

Cervical soft tissue imaging using a mobile CBCT scanner with a flat panel detector in comparison with corresponding CT and MRI data sets.

PubMed

Heiland, Max; Pohlenz, Philipp; Blessmann, Marco; Habermann, Christian R; Oesterhelweg, Lars; Begemann, Philipp C; Schmidgunst, Christian; Blake, Felix A S; Püschel, Klaus; Schmelzle, Rainer; Schulze, Dirk

2007-12-01

The aim of this study was to evaluate soft tissue image quality of a mobile cone-beam computed tomography (CBCT) scanner with an integrated flat-panel detector. Eight fresh human cadavers were used in this study. For evaluation of soft tissue visualization, CBCT data sets and corresponding computed tomography (CT) and magnetic resonance imaging (MRI) data sets were acquired. Evaluation was performed with the help of 10 defined cervical anatomical structures. The statistical analysis of the scoring results of 3 examiners revealed the CBCT images to be of inferior quality regarding the visualization of most of the predefined structures. Visualization without a significant difference was found regarding the demarcation of the vertebral bodies and the pyramidal cartilages, the arteriosclerosis of the carotids (compared with CT), and the laryngeal skeleton (compared with MRI). Regarding arteriosclerosis of the carotids compared with MRI, CBCT proved to be superior. The integration of a flat-panel detector improves soft tissue visualization using a mobile CBCT scanner.

Time-resolved imaging of the MALDI linear-TOF ion cloud: direct visualization and exploitation of ion optical phenomena using a position- and time-sensitive detector.

PubMed

Ellis, Shane R; Soltwisch, Jens; Heeren, Ron M A

2014-05-01

In this study, we describe the implementation of a position- and time-sensitive detection system (Timepix detector) to directly visualize the spatial distributions of the matrix-assisted laser desorption ionization ion cloud in a linear-time-of-flight (MALDI linear-ToF) as it is projected onto the detector surface. These time-resolved images allow direct visualization of m/z-dependent ion focusing effects that occur within the ion source of the instrument. The influence of key parameters, namely extraction voltage (E(V)), pulsed-ion extraction (PIE) delay, and even the matrix-dependent initial ion velocity was investigated and were found to alter the focusing properties of the ion-optical system. Under certain conditions where the spatial focal plane coincides with the detector plane, so-called x-y space focusing could be observed (i.e., the focusing of the ion cloud to a small, well-defined spot on the detector). Such conditions allow for the stigmatic ion imaging of intact proteins for the first time on a commercial linear ToF-MS system. In combination with the ion-optical magnification of the system (~100×), a spatial resolving power of 11–16 μm with a pixel size of 550 nm was recorded within a laser spot diameter of ~125 μm. This study demonstrates both the diagnostic and analytical advantages offered by the Timepix detector in ToF-MS.

A general purpose feature extractor for light detection and ranging data.

PubMed

Li, Yangming; Olson, Edwin B

2010-01-01

Feature extraction is a central step of processing Light Detection and Ranging (LIDAR) data. Existing detectors tend to exploit characteristics of specific environments: corners and lines from indoor (rectilinear) environments, and trees from outdoor environments. While these detectors work well in their intended environments, their performance in different environments can be poor. We describe a general purpose feature detector for both 2D and 3D LIDAR data that is applicable to virtually any environment. Our method adapts classic feature detection methods from the image processing literature, specifically the multi-scale Kanade-Tomasi corner detector. The resulting method is capable of identifying highly stable and repeatable features at a variety of spatial scales without knowledge of environment, and produces principled uncertainty estimates and corner descriptors at same time. We present results on both software simulation and standard datasets, including the 2D Victoria Park and Intel Research Center datasets, and the 3D MIT DARPA Urban Challenge dataset.

A General Purpose Feature Extractor for Light Detection and Ranging Data

PubMed Central

Li, Yangming; Olson, Edwin B.

2010-01-01

Feature extraction is a central step of processing Light Detection and Ranging (LIDAR) data. Existing detectors tend to exploit characteristics of specific environments: corners and lines from indoor (rectilinear) environments, and trees from outdoor environments. While these detectors work well in their intended environments, their performance in different environments can be poor. We describe a general purpose feature detector for both 2D and 3D LIDAR data that is applicable to virtually any environment. Our method adapts classic feature detection methods from the image processing literature, specifically the multi-scale Kanade-Tomasi corner detector. The resulting method is capable of identifying highly stable and repeatable features at a variety of spatial scales without knowledge of environment, and produces principled uncertainty estimates and corner descriptors at same time. We present results on both software simulation and standard datasets, including the 2D Victoria Park and Intel Research Center datasets, and the 3D MIT DARPA Urban Challenge dataset. PMID:22163474

Design of fire detection equipment based on ultraviolet detection technology

NASA Astrophysics Data System (ADS)

Liu, Zhenji; Liu, Jin; Chu, Sheng; Ping, Chao; Yuan, Xiaobing

2015-03-01

Utilized the feature of wide bandgap semiconductor of MgZnO, researched and developed a kind of Mid-Ultraviolet-Band(MUV) ultraviolet detector which has passed the simulation experiment in the sun circumstance. Based on the ultraviolet detector, it gives out a design scheme of gun-shot detection device, which is composed of twelve ultraviolet detectors, signal amplifier, processor, annunciator , azimuth indicator and the bracket. Through Analysing the feature of solar blind, ultraviolet responsivity, fire feature of gunshots and detection distance, the feasibility of this design scheme is proved.

Uniform competency-based local feature extraction for remote sensing images

NASA Astrophysics Data System (ADS)

Sedaghat, Amin; Mohammadi, Nazila

2018-01-01

Local feature detectors are widely used in many photogrammetry and remote sensing applications. The quantity and distribution of the local features play a critical role in the quality of the image matching process, particularly for multi-sensor high resolution remote sensing image registration. However, conventional local feature detectors cannot extract desirable matched features either in terms of the number of correct matches or the spatial and scale distribution in multi-sensor remote sensing images. To address this problem, this paper proposes a novel method for uniform and robust local feature extraction for remote sensing images, which is based on a novel competency criterion and scale and location distribution constraints. The proposed method, called uniform competency (UC) local feature extraction, can be easily applied to any local feature detector for various kinds of applications. The proposed competency criterion is based on a weighted ranking process using three quality measures, including robustness, spatial saliency and scale parameters, which is performed in a multi-layer gridding schema. For evaluation, five state-of-the-art local feature detector approaches, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), scale-invariant feature operator (SFOP), maximally stable extremal region (MSER) and hessian-affine, are used. The proposed UC-based feature extraction algorithms were successfully applied to match various synthetic and real satellite image pairs, and the results demonstrate its capability to increase matching performance and to improve the spatial distribution. The code to carry out the UC feature extraction is available from href="https://www.researchgate.net/publication/317956777_UC-Feature_Extraction.

Comparison of pediatric radiation dose and vessel visibility on angiographic systems using piglets as a surrogate: antiscatter grid removal vs. lower detector air kerma settings with a grid — a preclinical investigation

PubMed Central

Racadio, John M.; Abruzzo, Todd A.; Johnson, Neil D.; Patel, Manish N.; Kukreja, Kamlesh U.; den Hartog, Mark. J. H.; Hoornaert, Bart P.A.; Nachabe, Rami A.

2015-01-01

The purpose of this study was to reduce pediatric doses while maintaining or improving image quality scores without removing the grid from X‐ray beam. This study was approved by the Institutional Animal Care and Use Committee. Three piglets (5, 14, and 20 kg) were imaged using six different selectable detector air kerma (Kair) per frame values (100%, 70%, 50%, 35%, 25%, 17.5%) with and without the grid. Number of distal branches visualized with diagnostic confidence relative to the injected vessel defined image quality score. Five pediatric interventional radiologists evaluated all images. Image quality score and piglet Kair were statistically compared using analysis of variance and receiver operating curve analysis to define the preferred dose setting and use of grid for a visibility of 2nd and 3rd order vessel branches. Grid removal reduced both dose to subject and imaging quality by 26%. Third order branches could only be visualized with the grid present; 100% detector Kair was required for smallest pig, while 70% detector Kair was adequate for the two larger pigs. Second order branches could be visualized with grid at 17.5% detector Kair for all three pig sizes. Without the grid, 50%, 35%, and 35% detector Kair were required for smallest to largest pig, respectively. Grid removal reduces both dose and image quality score. Image quality scores can be maintained with less dose to subject with the grid in the beam as opposed to removed. Smaller anatomy requires more dose to the detector to achieve the same image quality score. PACS numbers: 87.53.Bn, 87.57.N‐, 87.57.cj, 87.59.cf, 87.59.Dj PMID:26699297

Visual Recognition of Artifacts by Computer.

DTIC Science & Technology

1979-08-01

detectors , each sensitive to a different group of edge types. An algorithm for selecting the most appropriate detector response in a particular region is...a . *00 . . . . . . . . . . . . . . . . . . . . .* 2 .2. StratwEDGE snco ............. as -o......... . ...... 5 2 *TwO NEW ED)GE DETECTORS 5...27 2.6. Sensitivity , Noise Immunity, and Snape Deformation .. 40 2.7. Conclusions ... . . ......................... ....... 43 3. INTERMEDIATE

Perceptual Learning via Modification of Cortical Top-Down Signals

PubMed Central

Schäfer, Roland; Vasilaki, Eleni; Senn, Walter

2007-01-01

The primary visual cortex (V1) is pre-wired to facilitate the extraction of behaviorally important visual features. Collinear edge detectors in V1, for instance, mutually enhance each other to improve the perception of lines against a noisy background. The same pre-wiring that facilitates line extraction, however, is detrimental when subjects have to discriminate the brightness of different line segments. How is it possible to improve in one task by unsupervised practicing, without getting worse in the other task? The classical view of perceptual learning is that practicing modulates the feedforward input stream through synaptic modifications onto or within V1. However, any rewiring of V1 would deteriorate other perceptual abilities different from the trained one. We propose a general neuronal model showing that perceptual learning can modulate top-down input to V1 in a task-specific way while feedforward and lateral pathways remain intact. Consistent with biological data, the model explains how context-dependent brightness discrimination is improved by a top-down recruitment of recurrent inhibition and a top-down induced increase of the neuronal gain within V1. Both the top-down modulation of inhibition and of neuronal gain are suggested to be universal features of cortical microcircuits which enable perceptual learning. PMID:17715996

Parallel perceptual enhancement and hierarchic relevance evaluation in an audio-visual conjunction task.

PubMed

Potts, Geoffrey F; Wood, Susan M; Kothmann, Delia; Martin, Laura E

2008-10-21

Attention directs limited-capacity information processing resources to a subset of available perceptual representations. The mechanisms by which attention selects task-relevant representations for preferential processing are not fully known. Triesman and Gelade's [Triesman, A., Gelade, G., 1980. A feature integration theory of attention. Cognit. Psychol. 12, 97-136.] influential attention model posits that simple features are processed preattentively, in parallel, but that attention is required to serially conjoin multiple features into an object representation. Event-related potentials have provided evidence for this model showing parallel processing of perceptual features in the posterior Selection Negativity (SN) and serial, hierarchic processing of feature conjunctions in the Frontal Selection Positivity (FSP). Most prior studies have been done on conjunctions within one sensory modality while many real-world objects have multimodal features. It is not known if the same neural systems of posterior parallel processing of simple features and frontal serial processing of feature conjunctions seen within a sensory modality also operate on conjunctions between modalities. The current study used ERPs and simultaneously presented auditory and visual stimuli in three task conditions: Attend Auditory (auditory feature determines the target, visual features are irrelevant), Attend Visual (visual features relevant, auditory irrelevant), and Attend Conjunction (target defined by the co-occurrence of an auditory and a visual feature). In the Attend Conjunction condition when the auditory but not the visual feature was a target there was an SN over auditory cortex, when the visual but not auditory stimulus was a target there was an SN over visual cortex, and when both auditory and visual stimuli were targets (i.e. conjunction target) there were SNs over both auditory and visual cortex, indicating parallel processing of the simple features within each modality. In contrast, an FSP was present when either the visual only or both auditory and visual features were targets, but not when only the auditory stimulus was a target, indicating that the conjunction target determination was evaluated serially and hierarchically with visual information taking precedence. This indicates that the detection of a target defined by audio-visual conjunction is achieved via the same mechanism as within a single perceptual modality, through separate, parallel processing of the auditory and visual features and serial processing of the feature conjunction elements, rather than by evaluation of a fused multimodal percept.

Wristwatch dosimeter

DOEpatents

Wolf, Michael A.; Waechter, David A.; Umbarger, C. John

1986-01-01

The disclosure is directed to a wristwatch dosimeter utilizing a CdTe detector, a microprocessor and an audio and/or visual alarm. The dosimeter is entirely housable with a conventional digital watch case having an additional aperture enabling the detector to receive radiation.

FBP and BPF reconstruction methods for circular X-ray tomography with off-center detector.

PubMed

Schäfer, Dirk; Grass, Michael; van de Haar, Peter

2011-07-01

Circular scanning with an off-center planar detector is an acquisition scheme that allows to save detector area while keeping a large field of view (FOV). Several filtered back-projection (FBP) algorithms have been proposed earlier. The purpose of this work is to present two newly developed back-projection filtration (BPF) variants and evaluate the image quality of these methods compared to the existing state-of-the-art FBP methods. The first new BPF algorithm applies redundancy weighting of overlapping opposite projections before differentiation in a single projection. The second one uses the Katsevich-type differentiation involving two neighboring projections followed by redundancy weighting and back-projection. An averaging scheme is presented to mitigate streak artifacts inherent to circular BPF algorithms along the Hilbert filter lines in the off-center transaxial slices of the reconstructions. The image quality is assessed visually on reconstructed slices of simulated and clinical data. Quantitative evaluation studies are performed with the Forbild head phantom by calculating root-mean-squared-deviations (RMSDs) to the voxelized phantom for different detector overlap settings and by investigating the noise resolution trade-off with a wire phantom in the full detector and off-center scenario. The noise-resolution behavior of all off-center reconstruction methods corresponds to their full detector performance with the best resolution for the FDK based methods with the given imaging geometry. With respect to RMSD and visual inspection, the proposed BPF with Katsevich-type differentiation outperforms all other methods for the smallest chosen detector overlap of about 15 mm. The best FBP method is the algorithm that is also based on the Katsevich-type differentiation and subsequent redundancy weighting. For wider overlap of about 40-50 mm, these two algorithms produce similar results outperforming the other three methods. The clinical case with a detector overlap of about 17 mm confirms these results. The BPF-type reconstructions with Katsevich differentiation are widely independent of the size of the detector overlap and give the best results with respect to RMSD and visual inspection for minimal detector overlap. The increased homogeneity will improve correct assessment of lesions in the entire field of view.

A General Purpose Feature Extractor for Light Detection and Ranging Data

DTIC Science & Technology

2010-11-17

datasets, and the 3D MIT DARPA Urban Challenge dataset. Keywords: SLAM ; LIDARs ; feature detection; uncertainty estimates; descriptors 1. Introduction The...November 2010 Abstract: Feature extraction is a central step of processing Light Detection and Ranging ( LIDAR ) data. Existing detectors tend to exploit...detector for both 2D and 3D LIDAR data that is applicable to virtually any environment. Our method adapts classic feature detection methods from the image

Wrist-watch dosimeter

DOEpatents

Wolf, M.A.; Waechter, D.A.; Umbarger, C.J.

1982-04-16

The disclosure is directed to a wristwatch dosimeter utilizing a CdTe detector, a microprocessor and an audio and/or visual alarm. The dosimeter is entirely housable within a conventional digital watch case having an additional aperture enabling the detector to receive radiation.

Wristwatch dosimeter

DOEpatents

Wolf, M.A.; Waechter, D.A.; Umbarger, C.J.

1986-08-26

The disclosure is directed to a wristwatch dosimeter utilizing a CdTe detector, a microprocessor and an audio and/or visual alarm. The dosimeter is entirely housable with a conventional digital watch case having an additional aperture enabling the detector to receive radiation. 10 figs.

Differential Visual Processing of Animal Images, with and without Conscious Awareness

PubMed Central

Zhu, Weina; Drewes, Jan; Peatfield, Nicholas A.; Melcher, David

2016-01-01

The human visual system can quickly and efficiently extract categorical information from a complex natural scene. The rapid detection of animals in a scene is one compelling example of this phenomenon, and it suggests the automatic processing of at least some types of categories with little or no attentional requirements (Li et al., 2002, 2005). The aim of this study is to investigate whether the remarkable capability to categorize complex natural scenes exist in the absence of awareness, based on recent reports that “invisible” stimuli, which do not reach conscious awareness, can still be processed by the human visual system (Pasley et al., 2004; Williams et al., 2004; Fang and He, 2005; Jiang et al., 2006, 2007; Kaunitz et al., 2011a). In two experiments, we recorded event-related potentials (ERPs) in response to animal and non-animal/vehicle stimuli in both aware and unaware conditions in a continuous flash suppression (CFS) paradigm. Our results indicate that even in the “unseen” condition, the brain responds differently to animal and non-animal/vehicle images, consistent with rapid activation of animal-selective feature detectors prior to, or outside of, suppression by the CFS mask. PMID:27790106

Differential Visual Processing of Animal Images, with and without Conscious Awareness.

PubMed

Zhu, Weina; Drewes, Jan; Peatfield, Nicholas A; Melcher, David

2016-01-01

The human visual system can quickly and efficiently extract categorical information from a complex natural scene. The rapid detection of animals in a scene is one compelling example of this phenomenon, and it suggests the automatic processing of at least some types of categories with little or no attentional requirements (Li et al., 2002, 2005). The aim of this study is to investigate whether the remarkable capability to categorize complex natural scenes exist in the absence of awareness, based on recent reports that "invisible" stimuli, which do not reach conscious awareness, can still be processed by the human visual system (Pasley et al., 2004; Williams et al., 2004; Fang and He, 2005; Jiang et al., 2006, 2007; Kaunitz et al., 2011a). In two experiments, we recorded event-related potentials (ERPs) in response to animal and non-animal/vehicle stimuli in both aware and unaware conditions in a continuous flash suppression (CFS) paradigm. Our results indicate that even in the "unseen" condition, the brain responds differently to animal and non-animal/vehicle images, consistent with rapid activation of animal-selective feature detectors prior to, or outside of, suppression by the CFS mask.

HECTOR: A 240kV micro-CT setup optimized for research

NASA Astrophysics Data System (ADS)

Masschaele, Bert; Dierick, Manuel; Van Loo, Denis; Boone, Matthieu N.; Brabant, Loes; Pauwels, Elin; Cnudde, Veerle; Van Hoorebeke, Luc

2013-10-01

X-ray micro-CT has become a very powerful and common tool for non-destructive three-dimensional (3D) visualization and analysis of objects. Many systems are commercially available, but they are typically limited in terms of operational freedom both from a mechanical point of view as well as for acquisition routines. HECTOR is the latest system developed by the Ghent University Centre for X-ray Tomography (http://www.ugct.ugent.be) in collaboration with X-Ray Engineering (XRE bvba, Ghent, Belgium). It consists of a mechanical setup with nine motorized axes and a modular acquisition software package and combines a microfocus directional target X-ray source up to 240 kV with a large flat-panel detector. Provisions are made to install a line-detector for a maximal operational range. The system can accommodate samples up to 80 kg, 1 m long and 80 cm in diameter while it is also suited for high resolution (down to 4 μm) tomography. The bi-directional detector tiling is suited for large samples while the variable source-detector distance optimizes the signal to noise ratio (SNR) for every type of sample, even with peripheral equipment such as compression stages or climate chambers. The large vertical travel of 1 m can be used for helical scanning and a vertical detector rotation axis allows laminography experiments. The setup is installed in a large concrete bunker to allow accommodation of peripheral equipment such as pumps, chillers, etc., which can be integrated in the modular acquisition software to obtain a maximal correlation between the environmental control and the CT data taken. The acquisition software does not only allow good coupling with the peripheral equipment but its scripting feature is also particularly interesting for testing new and exotic acquisition routines.

Insulation failure in electrosurgery instrumentation: a prospective evaluation.

PubMed

Tixier, Floriane; Garçon, Mélanie; Rochefort, Françoise; Corvaisier, Stéphane

2016-11-01

The use of electrosurgery has expanded to a wide variety of surgical specialities, but it has also been accompanied by its share of complications, including thermal injuries to nontargeted tissues, caused by a break or defect in the insulation of the instrument's coat. The purpose of this study was to determine the prevalence and the location of insulation failures (IFs) in electrosurgical instruments, then to assess the necessity of routine IF testing. Electrosurgical instruments were visually inspected and checked for IF using a high-voltage detector. Two different detectors were used during two testing sessions: DTU-6 (Petel company) and DIATEG (Morgate company). Laparoscopic and non-laparoscopic instruments were determined to have IF if current crossed the instrument's insulation, signaled by an alarm sound. A total of 489 instruments were tested. The overall prevalence of IFs was 24.1 % with only visual inspection and 37.2 % with the IF detector. Among the 489 instruments, 13.1 % were visually intact, but had an electric test failure. DTU-6 and DIATEG detectors showed comparable efficiency in detection of overall IFs and for laparoscopic and non-laparoscopic instruments. The median location of IFs was more pronounced for laparoscopic instruments (50.4 %) and the distal location for non-laparoscopic instruments (40.4 %). Accidental burns are a hidden problem and can lead to patient complications. In Central Sterilization Service Department, prevention currently includes only visual control of electrosurgery instrumentation, but testing campaigns are now necessary in order to identify maximum instruments' defects.

Hierarchical extreme learning machine based reinforcement learning for goal localization

NASA Astrophysics Data System (ADS)

AlDahoul, Nouar; Zaw Htike, Zaw; Akmeliawati, Rini

2017-03-01

The objective of goal localization is to find the location of goals in noisy environments. Simple actions are performed to move the agent towards the goal. The goal detector should be capable of minimizing the error between the predicted locations and the true ones. Few regions need to be processed by the agent to reduce the computational effort and increase the speed of convergence. In this paper, reinforcement learning (RL) method was utilized to find optimal series of actions to localize the goal region. The visual data, a set of images, is high dimensional unstructured data and needs to be represented efficiently to get a robust detector. Different deep Reinforcement models have already been used to localize a goal but most of them take long time to learn the model. This long learning time results from the weights fine tuning stage that is applied iteratively to find an accurate model. Hierarchical Extreme Learning Machine (H-ELM) was used as a fast deep model that doesn’t fine tune the weights. In other words, hidden weights are generated randomly and output weights are calculated analytically. H-ELM algorithm was used in this work to find good features for effective representation. This paper proposes a combination of Hierarchical Extreme learning machine and Reinforcement learning to find an optimal policy directly from visual input. This combination outperforms other methods in terms of accuracy and learning speed. The simulations and results were analysed by using MATLAB.

Refrigerant leak detector

NASA Technical Reports Server (NTRS)

Byrne, E. J.

1979-01-01

Quantitative leak detector visually demonstrates refrigerant loss from precision volume of large refrigeration system over established period of time from single test point. Mechanical unit is less costly than electronic "sniffers" and is more reliable due to absence of electronic circuits that are susceptible to drift.

A Model for an Angular Velocity-Tuned Motion Detector Accounting for Deviations in the Corridor-Centering Response of the Bee.

PubMed

Cope, Alex J; Sabo, Chelsea; Gurney, Kevin; Vasilaki, Eleni; Marshall, James A R

2016-05-01

We present a novel neurally based model for estimating angular velocity (AV) in the bee brain, capable of quantitatively reproducing experimental observations of visual odometry and corridor-centering in free-flying honeybees, including previously unaccounted for manipulations of behaviour. The model is fitted using electrophysiological data, and tested using behavioural data. Based on our model we suggest that the AV response can be considered as an evolutionary extension to the optomotor response. The detector is tested behaviourally in silico with the corridor-centering paradigm, where bees navigate down a corridor with gratings (square wave or sinusoidal) on the walls. When combined with an existing flight control algorithm the detector reproduces the invariance of the average flight path to the spatial frequency and contrast of the gratings, including deviations from perfect centering behaviour as found in the real bee's behaviour. In addition, the summed response of the detector to a unit distance movement along the corridor is constant for a large range of grating spatial frequencies, demonstrating that the detector can be used as a visual odometer.

A Model for an Angular Velocity-Tuned Motion Detector Accounting for Deviations in the Corridor-Centering Response of the Bee

PubMed Central

Sabo, Chelsea; Gurney, Kevin; Vasilaki, Eleni; Marshall, James A. R.

2016-01-01

We present a novel neurally based model for estimating angular velocity (AV) in the bee brain, capable of quantitatively reproducing experimental observations of visual odometry and corridor-centering in free-flying honeybees, including previously unaccounted for manipulations of behaviour. The model is fitted using electrophysiological data, and tested using behavioural data. Based on our model we suggest that the AV response can be considered as an evolutionary extension to the optomotor response. The detector is tested behaviourally in silico with the corridor-centering paradigm, where bees navigate down a corridor with gratings (square wave or sinusoidal) on the walls. When combined with an existing flight control algorithm the detector reproduces the invariance of the average flight path to the spatial frequency and contrast of the gratings, including deviations from perfect centering behaviour as found in the real bee’s behaviour. In addition, the summed response of the detector to a unit distance movement along the corridor is constant for a large range of grating spatial frequencies, demonstrating that the detector can be used as a visual odometer. PMID:27148968

Enhancement of ELDA Tracker Based on CNN Features and Adaptive Model Update.

PubMed

Gao, Changxin; Shi, Huizhang; Yu, Jin-Gang; Sang, Nong

2016-04-15

Appearance representation and the observation model are the most important components in designing a robust visual tracking algorithm for video-based sensors. Additionally, the exemplar-based linear discriminant analysis (ELDA) model has shown good performance in object tracking. Based on that, we improve the ELDA tracking algorithm by deep convolutional neural network (CNN) features and adaptive model update. Deep CNN features have been successfully used in various computer vision tasks. Extracting CNN features on all of the candidate windows is time consuming. To address this problem, a two-step CNN feature extraction method is proposed by separately computing convolutional layers and fully-connected layers. Due to the strong discriminative ability of CNN features and the exemplar-based model, we update both object and background models to improve their adaptivity and to deal with the tradeoff between discriminative ability and adaptivity. An object updating method is proposed to select the "good" models (detectors), which are quite discriminative and uncorrelated to other selected models. Meanwhile, we build the background model as a Gaussian mixture model (GMM) to adapt to complex scenes, which is initialized offline and updated online. The proposed tracker is evaluated on a benchmark dataset of 50 video sequences with various challenges. It achieves the best overall performance among the compared state-of-the-art trackers, which demonstrates the effectiveness and robustness of our tracking algorithm.

Enhancement of ELDA Tracker Based on CNN Features and Adaptive Model Update

PubMed Central

Gao, Changxin; Shi, Huizhang; Yu, Jin-Gang; Sang, Nong

2016-01-01

Appearance representation and the observation model are the most important components in designing a robust visual tracking algorithm for video-based sensors. Additionally, the exemplar-based linear discriminant analysis (ELDA) model has shown good performance in object tracking. Based on that, we improve the ELDA tracking algorithm by deep convolutional neural network (CNN) features and adaptive model update. Deep CNN features have been successfully used in various computer vision tasks. Extracting CNN features on all of the candidate windows is time consuming. To address this problem, a two-step CNN feature extraction method is proposed by separately computing convolutional layers and fully-connected layers. Due to the strong discriminative ability of CNN features and the exemplar-based model, we update both object and background models to improve their adaptivity and to deal with the tradeoff between discriminative ability and adaptivity. An object updating method is proposed to select the “good” models (detectors), which are quite discriminative and uncorrelated to other selected models. Meanwhile, we build the background model as a Gaussian mixture model (GMM) to adapt to complex scenes, which is initialized offline and updated online. The proposed tracker is evaluated on a benchmark dataset of 50 video sequences with various challenges. It achieves the best overall performance among the compared state-of-the-art trackers, which demonstrates the effectiveness and robustness of our tracking algorithm. PMID:27092505

Star sensor/mapper with a self deployable, high-attenuation light shade for SAS-B

NASA Technical Reports Server (NTRS)

Schenkel, F. W.; Finkel, A.

1972-01-01

A star sensor/mapper to determine positional data for the small astronomy satellites was tested to detect stars of plus 4 visual magnitude. It utilizes two information channels with memory so that it can be used with a low-data-rate telemetry system. One channel yields star amplitude information; the other yields the time of star occurrence as the star passes across an N-slit reticle/photomultiplier detector system. Some of the features of the star sensor/mapper are its low weight of 6.5 pounds, low power consumption of 0.4 watt, bandwidth switching to match the satellite spin rate, optical equalization of sensitivity over the 5-by-10 deg field of view, and self-deployable sunshade. The attitude determination accuracy is 3 arc minutes. This is determined by such parameters as the reticle configuration, optical train, and telemetry readout. The optical and electronic design of the star sensor/mapper, its expansion capabilities, and its features are discussed.

On computer vision in wireless sensor networks.

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

Berry, Nina M.; Ko, Teresa H.

Wireless sensor networks allow detailed sensing of otherwise unknown and inaccessible environments. While it would be beneficial to include cameras in a wireless sensor network because images are so rich in information, the power cost of transmitting an image across the wireless network can dramatically shorten the lifespan of the sensor nodes. This paper describe a new paradigm for the incorporation of imaging into wireless networks. Rather than focusing on transmitting images across the network, we show how an image can be processed locally for key features using simple detectors. Contrasted with traditional event detection systems that trigger an imagemore » capture, this enables a new class of sensors which uses a low power imaging sensor to detect a variety of visual cues. Sharing these features among relevant nodes cues specific actions to better provide information about the environment. We report on various existing techniques developed for traditional computer vision research which can aid in this work.« less

Temporal properties of material categorization and material rating: visual vs non-visual material features.

PubMed

Nagai, Takehiro; Matsushima, Toshiki; Koida, Kowa; Tani, Yusuke; Kitazaki, Michiteru; Nakauchi, Shigeki

2015-10-01

Humans can visually recognize material categories of objects, such as glass, stone, and plastic, easily. However, little is known about the kinds of surface quality features that contribute to such material class recognition. In this paper, we examine the relationship between perceptual surface features and material category discrimination performance for pictures of materials, focusing on temporal aspects, including reaction time and effects of stimulus duration. The stimuli were pictures of objects with an identical shape but made of different materials that could be categorized into seven classes (glass, plastic, metal, stone, wood, leather, and fabric). In a pre-experiment, observers rated the pictures on nine surface features, including visual (e.g., glossiness and transparency) and non-visual features (e.g., heaviness and warmness), on a 7-point scale. In the main experiments, observers judged whether two simultaneously presented pictures were classified as the same or different material category. Reaction times and effects of stimulus duration were measured. The results showed that visual feature ratings were correlated with material discrimination performance for short reaction times or short stimulus durations, while non-visual feature ratings were correlated only with performance for long reaction times or long stimulus durations. These results suggest that the mechanisms underlying visual and non-visual feature processing may differ in terms of processing time, although the cause is unclear. Visual surface features may mainly contribute to material recognition in daily life, while non-visual features may contribute only weakly, if at all. Copyright © 2014 Elsevier Ltd. All rights reserved.

a Performance Comparison of Feature Detectors for Planetary Rover Mapping and Localization

NASA Astrophysics Data System (ADS)

Wan, W.; Peng, M.; Xing, Y.; Wang, Y.; Liu, Z.; Di, K.; Teng, B.; Mao, X.; Zhao, Q.; Xin, X.; Jia, M.

2017-07-01

Feature detection and matching are key techniques in computer vision and robotics, and have been successfully implemented in many fields. So far there is no performance comparison of feature detectors and matching methods for planetary mapping and rover localization using rover stereo images. In this research, we present a comprehensive evaluation and comparison of six feature detectors, including Moravec, Förstner, Harris, FAST, SIFT and SURF, aiming for optimal implementation of feature-based matching in planetary surface environment. To facilitate quantitative analysis, a series of evaluation criteria, including distribution evenness of matched points, coverage of detected points, and feature matching accuracy, are developed in the research. In order to perform exhaustive evaluation, stereo images, simulated under different baseline, pitch angle, and interval of adjacent rover locations, are taken as experimental data source. The comparison results show that SIFT offers the best overall performance, especially it is less sensitive to changes of image taken at adjacent locations.

Data Acquisition Visualization Development for the MAJORANA DEMONSTRATOR

NASA Astrophysics Data System (ADS)

Wendlandt, Laura; Howe, Mark; Wilkerson, John; Majorana Collaboration

2013-10-01

The MAJORANA Project is building an array of germanium detectors with very low backgrounds in order to search for neutrinoless double-beta decay, a rare process that, if detected, would give us information about neutrinos. This decay would prove that neutrinos are their own anti-particles, would show that lepton number is not conserved, and would help determine absolute neutrino mass. An object-oriented, data acquisition software program known as ORCA (Object-oriented Real-time Control and Acquisition) will be used to collect data from the array. This paper describes the implementation of computer visualizations for detector calibrations, as well as tools for more general computer modeling in ORCA. Specifically, it details software that converts a CAD file to OpenGL, which can be used in ORCA. This paper also contains information about using a barium-133 source to take measurements from various locations around the detector, to better understand how data varies with detector crystal orientation. Work made possible by National Science Foundation Award OCI-1155614.

Storage of features, conjunctions and objects in visual working memory.

PubMed

Vogel, E K; Woodman, G F; Luck, S J

2001-02-01

Working memory can be divided into separate subsystems for verbal and visual information. Although the verbal system has been well characterized, the storage capacity of visual working memory has not yet been established for simple features or for conjunctions of features. The authors demonstrate that it is possible to retain information about only 3-4 colors or orientations in visual working memory at one time. Observers are also able to retain both the color and the orientation of 3-4 objects, indicating that visual working memory stores integrated objects rather than individual features. Indeed, objects defined by a conjunction of four features can be retained in working memory just as well as single-feature objects, allowing many individual features to be retained when distributed across a small number of objects. Thus, the capacity of visual working memory must be understood in terms of integrated objects rather than individual features.

FBP and BPF reconstruction methods for circular X-ray tomography with off-center detector

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

Schaefer, Dirk; Grass, Michael; Haar, Peter van de

2011-05-15

Purpose: Circular scanning with an off-center planar detector is an acquisition scheme that allows to save detector area while keeping a large field of view (FOV). Several filtered back-projection (FBP) algorithms have been proposed earlier. The purpose of this work is to present two newly developed back-projection filtration (BPF) variants and evaluate the image quality of these methods compared to the existing state-of-the-art FBP methods. Methods: The first new BPF algorithm applies redundancy weighting of overlapping opposite projections before differentiation in a single projection. The second one uses the Katsevich-type differentiation involving two neighboring projections followed by redundancy weighting andmore » back-projection. An averaging scheme is presented to mitigate streak artifacts inherent to circular BPF algorithms along the Hilbert filter lines in the off-center transaxial slices of the reconstructions. The image quality is assessed visually on reconstructed slices of simulated and clinical data. Quantitative evaluation studies are performed with the Forbild head phantom by calculating root-mean-squared-deviations (RMSDs) to the voxelized phantom for different detector overlap settings and by investigating the noise resolution trade-off with a wire phantom in the full detector and off-center scenario. Results: The noise-resolution behavior of all off-center reconstruction methods corresponds to their full detector performance with the best resolution for the FDK based methods with the given imaging geometry. With respect to RMSD and visual inspection, the proposed BPF with Katsevich-type differentiation outperforms all other methods for the smallest chosen detector overlap of about 15 mm. The best FBP method is the algorithm that is also based on the Katsevich-type differentiation and subsequent redundancy weighting. For wider overlap of about 40-50 mm, these two algorithms produce similar results outperforming the other three methods. The clinical case with a detector overlap of about 17 mm confirms these results. Conclusions: The BPF-type reconstructions with Katsevich differentiation are widely independent of the size of the detector overlap and give the best results with respect to RMSD and visual inspection for minimal detector overlap. The increased homogeneity will improve correct assessment of lesions in the entire field of view.« less

Assessing Photoreceptor Structure in Retinitis Pigmentosa and Usher Syndrome.

PubMed

Sun, Lynn W; Johnson, Ryan D; Langlo, Christopher S; Cooper, Robert F; Razeen, Moataz M; Russillo, Madia C; Dubra, Alfredo; Connor, Thomas B; Han, Dennis P; Pennesi, Mark E; Kay, Christine N; Weinberg, David V; Stepien, Kimberly E; Carroll, Joseph

2016-05-01

The purpose of this study was to examine cone photoreceptor structure in retinitis pigmentosa (RP) and Usher syndrome using confocal and nonconfocal split-detector adaptive optics scanning light ophthalmoscopy (AOSLO). Nineteen subjects (11 RP, 8 Usher syndrome) underwent ophthalmic and genetic testing, spectral-domain optical coherence tomography (SD-OCT), and AOSLO imaging. Split-detector images obtained in 11 subjects (7 RP, 4 Usher syndrome) were used to assess remnant cone structure in areas of altered cone reflectivity on confocal AOSLO. Despite normal interdigitation zone and ellipsoid zone appearance on OCT, foveal and parafoveal cone densities derived from confocal AOSLO images were significantly lower in Usher syndrome compared with RP. This was due in large part to an increased prevalence of non-waveguiding cones in the Usher syndrome retina. Although significantly correlated to best-corrected visual acuity and foveal sensitivity, cone density can decrease by nearly 38% before visual acuity becomes abnormal. Aberrantly waveguiding cones were noted within the transition zone of all eyes and corresponded to intact inner segment structures. These remnant cones decreased in density and increased in diameter across the transition zone and disappeared with external limiting membrane collapse. Foveal cone density can be decreased in RP and Usher syndrome before visible changes on OCT or a decline in visual function. Thus, AOSLO imaging may allow more sensitive monitoring of disease than current methods. However, confocal AOSLO is limited by dependence on cone waveguiding, whereas split-detector AOSLO offers unambiguous and quantifiable visualization of remnant cone inner segment structure. Confocal and split-detector thus offer complementary insights into retinal pathology.

Assessing Photoreceptor Structure in Retinitis Pigmentosa and Usher Syndrome

PubMed Central

Sun, Lynn W.; Johnson, Ryan D.; Langlo, Christopher S.; Cooper, Robert F.; Razeen, Moataz M.; Russillo, Madia C.; Dubra, Alfredo; Connor, Thomas B.; Han, Dennis P.; Pennesi, Mark E.; Kay, Christine N.; Weinberg, David V.; Stepien, Kimberly E.; Carroll, Joseph

2016-01-01

Purpose The purpose of this study was to examine cone photoreceptor structure in retinitis pigmentosa (RP) and Usher syndrome using confocal and nonconfocal split-detector adaptive optics scanning light ophthalmoscopy (AOSLO). Methods Nineteen subjects (11 RP, 8 Usher syndrome) underwent ophthalmic and genetic testing, spectral-domain optical coherence tomography (SD-OCT), and AOSLO imaging. Split-detector images obtained in 11 subjects (7 RP, 4 Usher syndrome) were used to assess remnant cone structure in areas of altered cone reflectivity on confocal AOSLO. Results Despite normal interdigitation zone and ellipsoid zone appearance on OCT, foveal and parafoveal cone densities derived from confocal AOSLO images were significantly lower in Usher syndrome compared with RP. This was due in large part to an increased prevalence of non-waveguiding cones in the Usher syndrome retina. Although significantly correlated to best-corrected visual acuity and foveal sensitivity, cone density can decrease by nearly 38% before visual acuity becomes abnormal. Aberrantly waveguiding cones were noted within the transition zone of all eyes and corresponded to intact inner segment structures. These remnant cones decreased in density and increased in diameter across the transition zone and disappeared with external limiting membrane collapse. Conclusions Foveal cone density can be decreased in RP and Usher syndrome before visible changes on OCT or a decline in visual function. Thus, AOSLO imaging may allow more sensitive monitoring of disease than current methods. However, confocal AOSLO is limited by dependence on cone waveguiding, whereas split-detector AOSLO offers unambiguous and quantifiable visualization of remnant cone inner segment structure. Confocal and split-detector thus offer complementary insights into retinal pathology. PMID:27145477

Investigation of energy weighting using an energy discriminating photon counting detector for breast CT

PubMed Central

Kalluri, Kesava S.; Mahd, Mufeed; Glick, Stephen J.

2013-01-01

Purpose: Breast CT is an emerging imaging technique that can portray the breast in 3D and improve visualization of important diagnostic features. Early clinical studies have suggested that breast CT has sufficient spatial and contrast resolution for accurate detection of masses and microcalcifications in the breast, reducing structural overlap that is often a limiting factor in reading mammographic images. For a number of reasons, image quality in breast CT may be improved by use of an energy resolving photon counting detector. In this study, the authors investigate the improvements in image quality obtained when using energy weighting with an energy resolving photon counting detector as compared to that with a conventional energy integrating detector. Methods: Using computer simulation, realistic CT images of multiple breast phantoms were generated. The simulation modeled a prototype breast CT system using an amorphous silicon (a-Si), CsI based energy integrating detector with different x-ray spectra, and a hypothetical, ideal CZT based photon counting detector with capability of energy discrimination. Three biological signals of interest were modeled as spherical lesions and inserted into breast phantoms; hydroxyapatite (HA) to represent microcalcification, infiltrating ductal carcinoma (IDC), and iodine enhanced infiltrating ductal carcinoma (IIDC). Signal-to-noise ratio (SNR) of these three lesions was measured from the CT reconstructions. In addition, a psychophysical study was conducted to evaluate observer performance in detecting microcalcifications embedded into a realistic anthropomorphic breast phantom. Results: In the energy range tested, improvements in SNR with a photon counting detector using energy weighting was higher (than the energy integrating detector method) by 30%–63% and 4%–34%, for HA and IDC lesions and 12%–30% (with Al filtration) and 32%–38% (with Ce filtration) for the IIDC lesion, respectively. The average area under the receiver operating characteristic curve (AUC) for detection of microcalcifications was higher by greater than 19% (for the different energy weighting methods tested) as compared to the AUC obtained with an energy integrating detector. Conclusions: This study showed that breast CT with a CZT photon counting detector using energy weighting can provide improvements in pixel SNR, and detectability of microcalcifications as compared to that with a conventional energy integrating detector. Since a number of degrading physical factors were not modeled into the photon counting detector, this improvement should be considered as an upper bound on achievable performance. PMID:23927337

Image Feature Types and Their Predictions of Aesthetic Preference and Naturalness

PubMed Central

Ibarra, Frank F.; Kardan, Omid; Hunter, MaryCarol R.; Kotabe, Hiroki P.; Meyer, Francisco A. C.; Berman, Marc G.

2017-01-01

Previous research has investigated ways to quantify visual information of a scene in terms of a visual processing hierarchy, i.e., making sense of visual environment by segmentation and integration of elementary sensory input. Guided by this research, studies have developed categories for low-level visual features (e.g., edges, colors), high-level visual features (scene-level entities that convey semantic information such as objects), and how models of those features predict aesthetic preference and naturalness. For example, in Kardan et al. (2015a), 52 participants provided aesthetic preference and naturalness ratings, which are used in the current study, for 307 images of mixed natural and urban content. Kardan et al. (2015a) then developed a model using low-level features to predict aesthetic preference and naturalness and could do so with high accuracy. What has yet to be explored is the ability of higher-level visual features (e.g., horizon line position relative to viewer, geometry of building distribution relative to visual access) to predict aesthetic preference and naturalness of scenes, and whether higher-level features mediate some of the association between the low-level features and aesthetic preference or naturalness. In this study we investigated these relationships and found that low- and high- level features explain 68.4% of the variance in aesthetic preference ratings and 88.7% of the variance in naturalness ratings. Additionally, several high-level features mediated the relationship between the low-level visual features and aaesthetic preference. In a multiple mediation analysis, the high-level feature mediators accounted for over 50% of the variance in predicting aesthetic preference. These results show that high-level visual features play a prominent role predicting aesthetic preference, but do not completely eliminate the predictive power of the low-level visual features. These strong predictors provide powerful insights for future research relating to landscape and urban design with the aim of maximizing subjective well-being, which could lead to improved health outcomes on a larger scale. PMID:28503158

Light-weight analyzer for odor recognition

DOEpatents

Vass, Arpad A; Wise, Marcus B

2014-05-20

The invention provides a light weight analyzer, e.g., detector, capable of locating clandestine graves. The detector utilizes the very specific and unique chemicals identified in the database of human decompositional odor. This detector, based on specific chemical compounds found relevant to human decomposition, is the next step forward in clandestine grave detection and will take the guess-work out of current methods using canines and ground-penetrating radar, which have historically been unreliable. The detector is self contained, portable and built for field use. Both visual and auditory cues are provided to the operator.

Stabilized display of coronary x-ray image sequences

NASA Astrophysics Data System (ADS)

Close, Robert A.; Whiting, James S.; Da, Xiaolin; Eigler, Neal L.

2004-05-01

Display stabilization is a technique by which a feature of interest in a cine image sequence is tracked and then shifted to remain approximately stationary on the display device. Prior simulations indicate that display stabilization with high playback rates ( 30 f/s) can significantly improve detectability of low-contrast features in coronary angiograms. Display stabilization may also help to improve the accuracy of intra-coronary device placement. We validated our automated tracking algorithm by comparing the inter-frame difference (jitter) between manual and automated tracking of 150 coronary x-ray image sequences acquired on a digital cardiovascular X-ray imaging system with CsI/a-Si flat panel detector. We find that the median (50%) inter-frame jitter between manual and automatic tracking is 1.41 pixels or less, indicating a jump no further than an adjacent pixel. This small jitter implies that automated tracking and manual tracking should yield similar improvements in the performance of most visual tasks. We hypothesize that cardiologists would perceive a benefit in viewing the stabilized display as an addition to the standard playback of cine recordings. A benefit of display stabilization was identified in 87 of 101 sequences (86%). The most common tasks cited were evaluation of stenosis and determination of stent and balloon positions. We conclude that display stabilization offers perceptible improvements in the performance of visual tasks by cardiologists.

Research on metallic material defect detection based on bionic sensing of human visual properties

NASA Astrophysics Data System (ADS)

Zhang, Pei Jiang; Cheng, Tao

2018-05-01

Due to the fact that human visual system can quickly lock the areas of interest in complex natural environment and focus on it, this paper proposes an eye-based visual attention mechanism by simulating human visual imaging features based on human visual attention mechanism Bionic Sensing Visual Inspection Model Method to Detect Defects of Metallic Materials in the Mechanical Field. First of all, according to the biologically visually significant low-level features, the mark of defect experience marking is used as the intermediate feature of simulated visual perception. Afterwards, SVM method was used to train the advanced features of visual defects of metal material. According to the weight of each party, the biometrics detection model of metal material defect, which simulates human visual characteristics, is obtained.

Detector Control System for the AFP detector in ATLAS experiment at CERN

NASA Astrophysics Data System (ADS)

Banaś, E.; Caforio, D.; Czekierda, S.; Hajduk, Z.; Olszowska, J.; Seabra, L.; Šícho, P.

2017-10-01

The ATLAS Forward Proton (AFP) detector consists of two forward detectors located at 205 m and 217 m on either side of the ATLAS experiment. The aim is to measure the momenta and angles of diffractively scattered protons. In 2016, two detector stations on one side of the ATLAS interaction point were installed and commissioned. The detector infrastructure and necessary services were installed and are supervised by the Detector Control System (DCS), which is responsible for the coherent and safe operation of the detector. A large variety of used equipment represents a considerable challenge for the AFP DCS design. Industrial Supervisory Control and Data Acquisition (SCADA) product Siemens WinCCOA, together with the CERN Joint Control Project (JCOP) framework and standard industrial and custom developed server applications and protocols are used for reading, processing, monitoring and archiving of the detector parameters. Graphical user interfaces allow for overall detector operation and visualization of the detector status. Parameters, important for the detector safety, are used for alert generation and interlock mechanisms.

Observers' cognitive states modulate how visual inputs relate to gaze control.

PubMed

Kardan, Omid; Henderson, John M; Yourganov, Grigori; Berman, Marc G

2016-09-01

Previous research has shown that eye-movements change depending on both the visual features of our environment, and the viewer's top-down knowledge. One important question that is unclear is the degree to which the visual goals of the viewer modulate how visual features of scenes guide eye-movements. Here, we propose a systematic framework to investigate this question. In our study, participants performed 3 different visual tasks on 135 scenes: search, memorization, and aesthetic judgment, while their eye-movements were tracked. Canonical correlation analyses showed that eye-movements were reliably more related to low-level visual features at fixations during the visual search task compared to the aesthetic judgment and scene memorization tasks. Different visual features also had different relevance to eye-movements between tasks. This modulation of the relationship between visual features and eye-movements by task was also demonstrated with classification analyses, where classifiers were trained to predict the viewing task based on eye movements and visual features at fixations. Feature loadings showed that the visual features at fixations could signal task differences independent of temporal and spatial properties of eye-movements. When classifying across participants, edge density and saliency at fixations were as important as eye-movements in the successful prediction of task, with entropy and hue also being significant, but with smaller effect sizes. When classifying within participants, brightness and saturation were also significant contributors. Canonical correlation and classification results, together with a test of moderation versus mediation, suggest that the cognitive state of the observer moderates the relationship between stimulus-driven visual features and eye-movements. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Visual Motion Perception and Visual Attentive Processes.

DTIC Science & Technology

1988-04-01

88-0551 Visual Motion Perception and Visual Attentive Processes George Spering , New YorkUnivesity A -cesson For DTIC TAB rant AFOSR 85-0364... Spering . HIPSt: A Unix-based image processing syslem. Computer Vision, Graphics, and Image Processing, 1984,25. 331-347. ’HIPS is the Human Information...Processing Laboratory’s Image Processing System. 1985 van Santen, Jan P. It, and George Spering . Elaborated Reichardt detectors. Journal of the Optical

A Role for MST Neurons in Heading Estimation

NASA Technical Reports Server (NTRS)

Stone, Leland Scott; Perrone, J. A.; Wade, Charles E. (Technical Monitor)

1994-01-01

A template model of human visual self-motion perception (Perrone, JOSA, 1992; Perrone & Stone, Vis. Res., in press), which uses neurophysiologically realistic "heading detectors", is consistent with numerous human psychophysical results (Warren & Hannon, Nature, 1988; Stone & Perrone, Neuro. Abstr., 1991) including the failure of humans to estimate their heading (direction of forward translation) accurately under certain visual conditions (Royden et al., Nature, 1992). We tested the model detectors with stimuli used by others in- single-unit studies. The detectors showed emergent properties similar to those of MST neurons: 1) Sensitivity to non-preferred flow. Each detector is tuned to a specific combination of flow components and its response is systematically reduced by the addition of nonpreferred flow (Orban et al., PNAS, 1992), and 2) Position invariance. The detectors maintain their apparent preference for particular flow components over large regions of their receptive fields (e.g. Duffy & Wurtz, J. Neurophys., 1991; Graziano et al., J. Neurosci., 1994). It has been argued that this latter property is incompatible with MST playing a role in heading perception. The model however demonstrates how neurons with the above response properties could still support accurate heading estimation within extrastriate cortical maps.

Visual affective classification by combining visual and text features.

PubMed

Liu, Ningning; Wang, Kai; Jin, Xin; Gao, Boyang; Dellandréa, Emmanuel; Chen, Liming

2017-01-01

Affective analysis of images in social networks has drawn much attention, and the texts surrounding images are proven to provide valuable semantic meanings about image content, which can hardly be represented by low-level visual features. In this paper, we propose a novel approach for visual affective classification (VAC) task. This approach combines visual representations along with novel text features through a fusion scheme based on Dempster-Shafer (D-S) Evidence Theory. Specifically, we not only investigate different types of visual features and fusion methods for VAC, but also propose textual features to effectively capture emotional semantics from the short text associated to images based on word similarity. Experiments are conducted on three public available databases: the International Affective Picture System (IAPS), the Artistic Photos and the MirFlickr Affect set. The results demonstrate that the proposed approach combining visual and textual features provides promising results for VAC task.

Visual affective classification by combining visual and text features

PubMed Central

Liu, Ningning; Wang, Kai; Jin, Xin; Gao, Boyang; Dellandréa, Emmanuel; Chen, Liming

2017-01-01

Affective analysis of images in social networks has drawn much attention, and the texts surrounding images are proven to provide valuable semantic meanings about image content, which can hardly be represented by low-level visual features. In this paper, we propose a novel approach for visual affective classification (VAC) task. This approach combines visual representations along with novel text features through a fusion scheme based on Dempster-Shafer (D-S) Evidence Theory. Specifically, we not only investigate different types of visual features and fusion methods for VAC, but also propose textual features to effectively capture emotional semantics from the short text associated to images based on word similarity. Experiments are conducted on three public available databases: the International Affective Picture System (IAPS), the Artistic Photos and the MirFlickr Affect set. The results demonstrate that the proposed approach combining visual and textual features provides promising results for VAC task. PMID:28850566

News video story segmentation method using fusion of audio-visual features

NASA Astrophysics Data System (ADS)

Wen, Jun; Wu, Ling-da; Zeng, Pu; Luan, Xi-dao; Xie, Yu-xiang

2007-11-01

News story segmentation is an important aspect for news video analysis. This paper presents a method for news video story segmentation. Different form prior works, which base on visual features transform, the proposed technique uses audio features as baseline and fuses visual features with it to refine the results. At first, it selects silence clips as audio features candidate points, and selects shot boundaries and anchor shots as two kinds of visual features candidate points. Then this paper selects audio feature candidates as cues and develops different fusion method, which effectively using diverse type visual candidates to refine audio candidates, to get story boundaries. Experiment results show that this method has high efficiency and adaptability to different kinds of news video.

Emulating the visual receptive-field properties of MST neurons with a template model of heading estimation

NASA Technical Reports Server (NTRS)

Perrone, J. A.; Stone, L. S.

1998-01-01

We have proposed previously a computational neural-network model by which the complex patterns of retinal image motion generated during locomotion (optic flow) can be processed by specialized detectors acting as templates for specific instances of self-motion. The detectors in this template model respond to global optic flow by sampling image motion over a large portion of the visual field through networks of local motion sensors with properties similar to those of neurons found in the middle temporal (MT) area of primate extrastriate visual cortex. These detectors, arranged within cortical-like maps, were designed to extract self-translation (heading) and self-rotation, as well as the scene layout (relative distances) ahead of a moving observer. We then postulated that heading from optic flow is directly encoded by individual neurons acting as heading detectors within the medial superior temporal (MST) area. Others have questioned whether individual MST neurons can perform this function because some of their receptive-field properties seem inconsistent with this role. To resolve this issue, we systematically compared MST responses with those of detectors from two different configurations of the model under matched stimulus conditions. We found that the characteristic physiological properties of MST neurons can be explained by the template model. We conclude that MST neurons are well suited to support self-motion estimation via a direct encoding of heading and that the template model provides an explicit set of testable hypotheses that can guide future exploration of MST and adjacent areas within the superior temporal sulcus.

Feature precedence in processing multifeature visual information in the human brain: an event-related potential study.

PubMed

Liu, B; Meng, X; Wu, G; Huang, Y

2012-05-17

In this article, we aimed to study whether feature precedence existed in the cognitive processing of multifeature visual information in the human brain. In our experiment, we paid attention to two important visual features as follows: color and shape. In order to avoid the presence of semantic constraints between them and the resulting impact, pure color and simple geometric shape were chosen as the color feature and shape feature of visual stimulus, respectively. We adopted an "old/new" paradigm to study the cognitive processing of color feature, shape feature and the combination of color feature and shape feature, respectively. The experiment consisted of three tasks as follows: Color task, Shape task and Color-Shape task. The results showed that the feature-based pattern would be activated in the human brain in processing multifeature visual information without semantic association between features. Furthermore, shape feature was processed earlier than color feature, and the cognitive processing of color feature was more difficult than that of shape feature. Copyright © 2012 IBRO. Published by Elsevier Ltd. All rights reserved.

The artificial retina for track reconstruction at the LHC crossing rate

NASA Astrophysics Data System (ADS)

Abba, A.; Bedeschi, F.; Citterio, M.; Caponio, F.; Cusimano, A.; Geraci, A.; Marino, P.; Morello, M. J.; Neri, N.; Punzi, G.; Piucci, A.; Ristori, L.; Spinella, F.; Stracka, S.; Tonelli, D.

2016-04-01

We present the results of an R&D study for a specialized processor capable of precisely reconstructing events with hundreds of charged-particle tracks in pixel and silicon strip detectors at 40 MHz, thus suitable for processing LHC events at the full crossing frequency. For this purpose we design and test a massively parallel pattern-recognition algorithm, inspired to the current understanding of the mechanisms adopted by the primary visual cortex of mammals in the early stages of visual-information processing. The detailed geometry and charged-particle's activity of a large tracking detector are simulated and used to assess the performance of the artificial retina algorithm. We find that high-quality tracking in large detectors is possible with sub-microsecond latencies when the algorithm is implemented in modern, high-speed, high-bandwidth FPGA devices.

Feature-based attentional modulations in the absence of direct visual stimulation.

PubMed

Serences, John T; Boynton, Geoffrey M

2007-07-19

When faced with a crowded visual scene, observers must selectively attend to behaviorally relevant objects to avoid sensory overload. Often this selection process is guided by prior knowledge of a target-defining feature (e.g., the color red when looking for an apple), which enhances the firing rate of visual neurons that are selective for the attended feature. Here, we used functional magnetic resonance imaging and a pattern classification algorithm to predict the attentional state of human observers as they monitored a visual feature (one of two directions of motion). We find that feature-specific attention effects spread across the visual field-even to regions of the scene that do not contain a stimulus. This spread of feature-based attention to empty regions of space may facilitate the perception of behaviorally relevant stimuli by increasing sensitivity to attended features at all locations in the visual field.

Temporal and spatial adaptation of transient responses to local features

PubMed Central

O'Carroll, David C.; Barnett, Paul D.; Nordström, Karin

2012-01-01

Interpreting visual motion within the natural environment is a challenging task, particularly considering that natural scenes vary enormously in brightness, contrast and spatial structure. The performance of current models for the detection of self-generated optic flow depends critically on these very parameters, but despite this, animals manage to successfully navigate within a broad range of scenes. Within global scenes local areas with more salient features are common. Recent work has highlighted the influence that local, salient features have on the encoding of optic flow, but it has been difficult to quantify how local transient responses affect responses to subsequent features and thus contribute to the global neural response. To investigate this in more detail we used experimenter-designed stimuli and recorded intracellularly from motion-sensitive neurons. We limited the stimulus to a small vertically elongated strip, to investigate local and global neural responses to pairs of local “doublet” features that were designed to interact with each other in the temporal and spatial domain. We show that the passage of a high-contrast doublet feature produces a complex transient response from local motion detectors consistent with predictions of a simple computational model. In the neuron, the passage of a high-contrast feature induces a local reduction in responses to subsequent low-contrast features. However, this neural contrast gain reduction appears to be recruited only when features stretch vertically (i.e., orthogonal to the direction of motion) across at least several aligned neighboring ommatidia. Horizontal displacement of the components of elongated features abolishes the local adaptation effect. It is thus likely that features in natural scenes with vertically aligned edges, such as tree trunks, recruit the greatest amount of response suppression. This property could emphasize the local responses to such features vs. those in nearby texture within the scene. PMID:23087617

Problematic projection to the in-sample subspace for a kernelized anomaly detector

DOE PAGES

Theiler, James; Grosklos, Guen

2016-03-07

We examine the properties and performance of kernelized anomaly detectors, with an emphasis on the Mahalanobis-distance-based kernel RX (KRX) algorithm. Although the detector generally performs well for high-bandwidth Gaussian kernels, it exhibits problematic (in some cases, catastrophic) performance for distances that are large compared to the bandwidth. By comparing KRX to two other anomaly detectors, we can trace the problem to a projection in feature space, which arises when a pseudoinverse is used on the covariance matrix in that feature space. Here, we show that a regularized variant of KRX overcomes this difficulty and achieves superior performance over a widemore » range of bandwidths.« less

Face Alignment via Regressing Local Binary Features.

PubMed

Ren, Shaoqing; Cao, Xudong; Wei, Yichen; Sun, Jian

2016-03-01

This paper presents a highly efficient and accurate regression approach for face alignment. Our approach has two novel components: 1) a set of local binary features and 2) a locality principle for learning those features. The locality principle guides us to learn a set of highly discriminative local binary features for each facial landmark independently. The obtained local binary features are used to jointly learn a linear regression for the final output. This approach achieves the state-of-the-art results when tested on the most challenging benchmarks to date. Furthermore, because extracting and regressing local binary features are computationally very cheap, our system is much faster than previous methods. It achieves over 3000 frames per second (FPS) on a desktop or 300 FPS on a mobile phone for locating a few dozens of landmarks. We also study a key issue that is important but has received little attention in the previous research, which is the face detector used to initialize alignment. We investigate several face detectors and perform quantitative evaluation on how they affect alignment accuracy. We find that an alignment friendly detector can further greatly boost the accuracy of our alignment method, reducing the error up to 16% relatively. To facilitate practical usage of face detection/alignment methods, we also propose a convenient metric to measure how good a detector is for alignment initialization.

A competitive interaction theory of attentional selection and decision making in brief, multielement displays.

PubMed

Smith, Philip L; Sewell, David K

2013-07-01

We generalize the integrated system model of Smith and Ratcliff (2009) to obtain a new theory of attentional selection in brief, multielement visual displays. The theory proposes that attentional selection occurs via competitive interactions among detectors that signal the presence of task-relevant features at particular display locations. The outcome of the competition, together with attention, determines which stimuli are selected into visual short-term memory (VSTM). Decisions about the contents of VSTM are made by a diffusion-process decision stage. The selection process is modeled by coupled systems of shunting equations, which perform gated where-on-what pathway VSTM selection. The theory provides a computational account of key findings from attention tasks with near-threshold stimuli. These are (a) the success of the MAX model of visual search and spatial cuing, (b) the distractor homogeneity effect, (c) the double-target detection deficit, (d) redundancy costs in the post-stimulus probe task, (e) the joint item and information capacity limits of VSTM, and (f) the object-based nature of attentional selection. We argue that these phenomena are all manifestations of an underlying competitive VSTM selection process, which arise as a natural consequence of our theory. PsycINFO Database Record (c) 2013 APA, all rights reserved.

A fast and automatic fusion algorithm for unregistered multi-exposure image sequence

NASA Astrophysics Data System (ADS)

Liu, Yan; Yu, Feihong

2014-09-01

Human visual system (HVS) can visualize all the brightness levels of the scene through visual adaptation. However, the dynamic range of most commercial digital cameras and display devices are smaller than the dynamic range of human eye. This implies low dynamic range (LDR) images captured by normal digital camera may lose image details. We propose an efficient approach to high dynamic (HDR) image fusion that copes with image displacement and image blur degradation in a computationally efficient manner, which is suitable for implementation on mobile devices. The various image registration algorithms proposed in the previous literatures are unable to meet the efficiency and performance requirements in the application of mobile devices. In this paper, we selected Oriented Brief (ORB) detector to extract local image structures. The descriptor selected in multi-exposure image fusion algorithm has to be fast and robust to illumination variations and geometric deformations. ORB descriptor is the best candidate in our algorithm. Further, we perform an improved RANdom Sample Consensus (RANSAC) algorithm to reject incorrect matches. For the fusion of images, a new approach based on Stationary Wavelet Transform (SWT) is used. The experimental results demonstrate that the proposed algorithm generates high quality images at low computational cost. Comparisons with a number of other feature matching methods show that our method gets better performance.

What are the assets and weaknesses of HFO detectors? A benchmark framework based on realistic simulations

PubMed Central

Pizzo, Francesca; Bartolomei, Fabrice; Wendling, Fabrice; Bénar, Christian-George

2017-01-01

High-frequency oscillations (HFO) have been suggested as biomarkers of epileptic tissues. While visual marking of these short and small oscillations is tedious and time-consuming, automatic HFO detectors have not yet met a large consensus. Even though detectors have been shown to perform well when validated against visual marking, the large number of false detections due to their lack of robustness hinder their clinical application. In this study, we developed a validation framework based on realistic and controlled simulations to quantify precisely the assets and weaknesses of current detectors. We constructed a dictionary of synthesized elements—HFOs and epileptic spikes—from different patients and brain areas by extracting these elements from the original data using discrete wavelet transform coefficients. These elements were then added to their corresponding simulated background activity (preserving patient- and region- specific spectra). We tested five existing detectors against this benchmark. Compared to other studies confronting detectors, we did not only ranked them according their performance but we investigated the reasons leading to these results. Our simulations, thanks to their realism and their variability, enabled us to highlight unreported issues of current detectors: (1) the lack of robust estimation of the background activity, (2) the underestimated impact of the 1/f spectrum, and (3) the inadequate criteria defining an HFO. We believe that our benchmark framework could be a valuable tool to translate HFOs into a clinical environment. PMID:28406919

IUE detector saturation and the new 2800 A absorption feature 'discovered' by Karim, Hoyle, and Wickramasinghe

NASA Astrophysics Data System (ADS)

Savage, B. D.; Sitko, M. L.

1984-03-01

The 2800 A feature of Karim et al. (1983) is shown to be the result of IUE detector saturation effects in overexposed spectra. A properly exposed spectrum and an overexposed one are shown. The latter shows a broad absorption peak at 2800 A while the former does not.

BATSE gamma-ray burst line search. 2: Bayesian consistency methodology

NASA Technical Reports Server (NTRS)

Band, D. L.; Ford, L. A.; Matteson, J. L.; Briggs, M.; Paciesas, W.; Pendleton, G.; Preece, R.; Palmer, D.; Teegarden, B.; Schaefer, B.

1994-01-01

We describe a Bayesian methodology to evaluate the consistency between the reported Ginga and Burst and Transient Source Experiment (BATSE) detections of absorption features in gamma-ray burst spectra. Currently no features have been detected by BATSE, but this methodology will still be applicable if and when such features are discovered. The Bayesian methodology permits the comparison of hypotheses regarding the two detectors' observations and makes explicit the subjective aspects of our analysis (e.g., the quantification of our confidence in detector performance). We also present non-Bayesian consistency statistics. Based on preliminary calculations of line detectability, we find that both the Bayesian and non-Bayesian techniques show that the BATSE and Ginga observations are consistent given our understanding of these detectors.

Caudate nucleus reactivity predicts perceptual learning rate for visual feature conjunctions.

PubMed

Reavis, Eric A; Frank, Sebastian M; Tse, Peter U

2015-04-15

Useful information in the visual environment is often contained in specific conjunctions of visual features (e.g., color and shape). The ability to quickly and accurately process such conjunctions can be learned. However, the neural mechanisms responsible for such learning remain largely unknown. It has been suggested that some forms of visual learning might involve the dopaminergic neuromodulatory system (Roelfsema et al., 2010; Seitz and Watanabe, 2005), but this hypothesis has not yet been directly tested. Here we test the hypothesis that learning visual feature conjunctions involves the dopaminergic system, using functional neuroimaging, genetic assays, and behavioral testing techniques. We use a correlative approach to evaluate potential associations between individual differences in visual feature conjunction learning rate and individual differences in dopaminergic function as indexed by neuroimaging and genetic markers. We find a significant correlation between activity in the caudate nucleus (a component of the dopaminergic system connected to visual areas of the brain) and visual feature conjunction learning rate. Specifically, individuals who showed a larger difference in activity between positive and negative feedback on an unrelated cognitive task, indicative of a more reactive dopaminergic system, learned visual feature conjunctions more quickly than those who showed a smaller activity difference. This finding supports the hypothesis that the dopaminergic system is involved in visual learning, and suggests that visual feature conjunction learning could be closely related to associative learning. However, no significant, reliable correlations were found between feature conjunction learning and genotype or dopaminergic activity in any other regions of interest. Copyright © 2015 Elsevier Inc. All rights reserved.

Short-term retention of visual information: Evidence in support of feature-based attention as an underlying mechanism.

PubMed

Sneve, Markus H; Sreenivasan, Kartik K; Alnæs, Dag; Endestad, Tor; Magnussen, Svein

2015-01-01

Retention of features in visual short-term memory (VSTM) involves maintenance of sensory traces in early visual cortex. However, the mechanism through which this is accomplished is not known. Here, we formulate specific hypotheses derived from studies on feature-based attention to test the prediction that visual cortex is recruited by attentional mechanisms during VSTM of low-level features. Functional magnetic resonance imaging (fMRI) of human visual areas revealed that neural populations coding for task-irrelevant feature information are suppressed during maintenance of detailed spatial frequency memory representations. The narrow spectral extent of this suppression agrees well with known effects of feature-based attention. Additionally, analyses of effective connectivity during maintenance between retinotopic areas in visual cortex show that the observed highlighting of task-relevant parts of the feature spectrum originates in V4, a visual area strongly connected with higher-level control regions and known to convey top-down influence to earlier visual areas during attentional tasks. In line with this property of V4 during attentional operations, we demonstrate that modulations of earlier visual areas during memory maintenance have behavioral consequences, and that these modulations are a result of influences from V4. Copyright © 2014 Elsevier Ltd. All rights reserved.

Visual Prediction Error Spreads Across Object Features in Human Visual Cortex

PubMed Central

Summerfield, Christopher; Egner, Tobias

2016-01-01

Visual cognition is thought to rely heavily on contextual expectations. Accordingly, previous studies have revealed distinct neural signatures for expected versus unexpected stimuli in visual cortex. However, it is presently unknown how the brain combines multiple concurrent stimulus expectations such as those we have for different features of a familiar object. To understand how an unexpected object feature affects the simultaneous processing of other expected feature(s), we combined human fMRI with a task that independently manipulated expectations for color and motion features of moving-dot stimuli. Behavioral data and neural signals from visual cortex were then interrogated to adjudicate between three possible ways in which prediction error (surprise) in the processing of one feature might affect the concurrent processing of another, expected feature: (1) feature processing may be independent; (2) surprise might “spread” from the unexpected to the expected feature, rendering the entire object unexpected; or (3) pairing a surprising feature with an expected feature might promote the inference that the two features are not in fact part of the same object. To formalize these rival hypotheses, we implemented them in a simple computational model of multifeature expectations. Across a range of analyses, behavior and visual neural signals consistently supported a model that assumes a mixing of prediction error signals across features: surprise in one object feature spreads to its other feature(s), thus rendering the entire object unexpected. These results reveal neurocomputational principles of multifeature expectations and indicate that objects are the unit of selection for predictive vision. SIGNIFICANCE STATEMENT We address a key question in predictive visual cognition: how does the brain combine multiple concurrent expectations for different features of a single object such as its color and motion trajectory? By combining a behavioral protocol that independently varies expectation of (and attention to) multiple object features with computational modeling and fMRI, we demonstrate that behavior and fMRI activity patterns in visual cortex are best accounted for by a model in which prediction error in one object feature spreads to other object features. These results demonstrate how predictive vision forms object-level expectations out of multiple independent features. PMID:27810936

Object-based attention underlies the rehearsal of feature binding in visual working memory.

PubMed

Shen, Mowei; Huang, Xiang; Gao, Zaifeng

2015-04-01

Feature binding is a core concept in many research fields, including the study of working memory (WM). Over the past decade, it has been debated whether keeping the feature binding in visual WM consumes more visual attention than the constituent single features. Previous studies have only explored the contribution of domain-general attention or space-based attention in the binding process; no study so far has explored the role of object-based attention in retaining binding in visual WM. We hypothesized that object-based attention underlay the mechanism of rehearsing feature binding in visual WM. Therefore, during the maintenance phase of a visual WM task, we inserted a secondary mental rotation (Experiments 1-3), transparent motion (Experiment 4), or an object-based feature report task (Experiment 5) to consume the object-based attention available for binding. In line with the prediction of the object-based attention hypothesis, Experiments 1-5 revealed a more significant impairment for binding than for constituent single features. However, this selective binding impairment was not observed when inserting a space-based visual search task (Experiment 6). We conclude that object-based attention underlies the rehearsal of binding representation in visual WM. (c) 2015 APA, all rights reserved.

Spectroscopic micro-tomography of metallic-organic composites by means of photon-counting detectors

NASA Astrophysics Data System (ADS)

Pichotka, M.; Jakubek, J.; Vavrik, D.

2015-12-01

The presumed capabilities of photon counting detectors have aroused major expectations in several fields of research. In the field of nuclear imaging ample benefits over standard detectors are to be expected from photon counting devices. First of all a very high contrast, as has by now been verified in numerous experiments. The spectroscopic capabilities of photon counting detectors further allow material decomposition in computed tomography and therefore inherently adequate beam hardening correction. For these reasons measurement setups featuring standard X-ray tubes combined with photon counting detectors constitute a possible replacement of the much more cost intensive tomographic setups at synchrotron light-sources. The actual application of photon counting detectors in radiographic setups in recent years has been impeded by a number of practical issues, above all by restrictions in the detectors size. Currently two tomographic setups in Czech Republic feature photon counting large-area detectors (LAD) fabricated in Prague. The employed large area hybrid pixel-detector assemblies [1] consisting of 10×10/10×5 Timepix devices have a surface area of 143×143 mm2 / 143×71,5 mm2 respectively, suitable for micro-tomographic applications. In the near future LAD devices featuring the Medipix3 readout chip as well as heavy sensors (CdTe, GaAs) will become available. Data analysis is obtained by a number of in house software tools including iterative multi-energy volume reconstruction.In this paper tomographic analysis of of metallic-organic composites is employed to illustrate the capabilities of our technology. Other than successful material decomposition by spectroscopic tomography we present a method to suppress metal artefacts under certain conditions.

Trabecular bone class mapping across resolutions: translating methods from HR-pQCT to clinical CT

NASA Astrophysics Data System (ADS)

Valentinitsch, Alexander; Fischer, Lukas; Patsch, Janina M.; Bauer, Jan; Kainberger, Franz; Langs, Georg; DiFranco, Matthew

2015-03-01

Quantitative assessment of 3D bone microarchitecture in high-resolution peripheral quantitative computed tomography (HR-pQCT) has shown promise in fracture risk assessment and biomechanics, but is limited to the distal radius and tibia. Trabecular microarchitecture classes (TMACs), based on voxel-wise clustering texture and structure tensor features in HRpQCT, is extended in this paper to quantify trabecular bone classes in clinical multi-detector CT (MDCT) images. Our comparison of TMACs in 12 cadaver radii imaged using both HRpQCT and MDCT yields a mean Dice score of up to 0.717+/-0.40 and visually concordant bone quality maps. Further work to develop clinically viable bone quantitative imaging using HR-pQCT validation could have a significant impact on overall bone health assessment.

Integrative and distinctive coding of visual and conceptual object features in the ventral visual stream

PubMed Central

Douglas, Danielle; Newsome, Rachel N; Man, Louisa LY

2018-01-01

A significant body of research in cognitive neuroscience is aimed at understanding how object concepts are represented in the human brain. However, it remains unknown whether and where the visual and abstract conceptual features that define an object concept are integrated. We addressed this issue by comparing the neural pattern similarities among object-evoked fMRI responses with behavior-based models that independently captured the visual and conceptual similarities among these stimuli. Our results revealed evidence for distinctive coding of visual features in lateral occipital cortex, and conceptual features in the temporal pole and parahippocampal cortex. By contrast, we found evidence for integrative coding of visual and conceptual object features in perirhinal cortex. The neuroanatomical specificity of this effect was highlighted by results from a searchlight analysis. Taken together, our findings suggest that perirhinal cortex uniquely supports the representation of fully specified object concepts through the integration of their visual and conceptual features. PMID:29393853

Scanning Seismic Intrusion Detector

NASA Technical Reports Server (NTRS)

Lee, R. D.

1982-01-01

Scanning seismic intrusion detector employs array of automatically or manually scanned sensors to determine approximate location of intruder. Automatic-scanning feature enables one operator to tend system of many sensors. Typical sensors used with new system are moving-coil seismic pickups. Detector finds uses in industrial security systems.

46 CFR 161.002-2 - Types of fire-protective systems.

Code of Federal Regulations, 2012 CFR

2012-10-01

..., but not be limited to, automatic fire and smoke detecting systems, manual fire alarm systems, sample... unit, fire detectors, smoke detectors, and audible and visual alarms distinct in both respects from the alarms of any other system not indicating fire. (c) Manual fire alarm systems. For the purpose of this...

Quantitative Features of Liver Lesions, Lung Nodules, and Renal Stones at Multi-Detector Row CT Examinations: Dependency on Radiation Dose and Reconstruction Algorithm.

PubMed

Solomon, Justin; Mileto, Achille; Nelson, Rendon C; Roy Choudhury, Kingshuk; Samei, Ehsan

2016-04-01

To determine if radiation dose and reconstruction algorithm affect the computer-based extraction and analysis of quantitative imaging features in lung nodules, liver lesions, and renal stones at multi-detector row computed tomography (CT). Retrospective analysis of data from a prospective, multicenter, HIPAA-compliant, institutional review board-approved clinical trial was performed by extracting 23 quantitative imaging features (size, shape, attenuation, edge sharpness, pixel value distribution, and texture) of lesions on multi-detector row CT images of 20 adult patients (14 men, six women; mean age, 63 years; range, 38-72 years) referred for known or suspected focal liver lesions, lung nodules, or kidney stones. Data were acquired between September 2011 and April 2012. All multi-detector row CT scans were performed at two different radiation dose levels; images were reconstructed with filtered back projection, adaptive statistical iterative reconstruction, and model-based iterative reconstruction (MBIR) algorithms. A linear mixed-effects model was used to assess the effect of radiation dose and reconstruction algorithm on extracted features. Among the 23 imaging features assessed, radiation dose had a significant effect on five, three, and four of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 for all comparisons). Adaptive statistical iterative reconstruction had a significant effect on three, one, and one of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 for all comparisons). MBIR reconstruction had a significant effect on nine, 11, and 15 of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 for all comparisons). Of note, the measured size of lung nodules and renal stones with MBIR was significantly different than those for the other two algorithms (P < .002 for all comparisons). Although lesion texture was significantly affected by the reconstruction algorithm used (average of 3.33 features affected by MBIR throughout lesion types; P < .002, for all comparisons), no significant effect of the radiation dose setting was observed for all but one of the texture features (P = .002-.998). Radiation dose settings and reconstruction algorithms affect the extraction and analysis of quantitative imaging features in lesions at multi-detector row CT.

Deconvolution single shot multibox detector for supermarket commodity detection and classification

NASA Astrophysics Data System (ADS)

Li, Dejian; Li, Jian; Nie, Binling; Sun, Shouqian

2017-07-01

This paper proposes an image detection model to detect and classify supermarkets shelves' commodity. Based on the principle of the features directly affects the accuracy of the final classification, feature maps are performed to combine high level features with bottom level features. Then set some fixed anchors on those feature maps, finally the label and the position of commodity is generated by doing a box regression and classification. In this work, we proposed a model named Deconvolutiuon Single Shot MultiBox Detector, we evaluated the model using 300 images photographed from real supermarket shelves. Followed the same protocol in other recent methods, the results showed that our model outperformed other baseline methods.

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

Theiler, James; Grosklos, Guen

We examine the properties and performance of kernelized anomaly detectors, with an emphasis on the Mahalanobis-distance-based kernel RX (KRX) algorithm. Although the detector generally performs well for high-bandwidth Gaussian kernels, it exhibits problematic (in some cases, catastrophic) performance for distances that are large compared to the bandwidth. By comparing KRX to two other anomaly detectors, we can trace the problem to a projection in feature space, which arises when a pseudoinverse is used on the covariance matrix in that feature space. Here, we show that a regularized variant of KRX overcomes this difficulty and achieves superior performance over a widemore » range of bandwidths.« less

Effect of time discretization of the imaging process on the accuracy of trajectory estimation in fluorescence microscopy

PubMed Central

Wong, Yau; Chao, Jerry; Lin, Zhiping; Ober, Raimund J.

2014-01-01

In fluorescence microscopy, high-speed imaging is often necessary for the proper visualization and analysis of fast subcellular dynamics. Here, we examine how the speed of image acquisition affects the accuracy with which parameters such as the starting position and speed of a microscopic non-stationary fluorescent object can be estimated from the resulting image sequence. Specifically, we use a Fisher information-based performance bound to investigate the detector-dependent effect of frame rate on the accuracy of parameter estimation. We demonstrate that when a charge-coupled device detector is used, the estimation accuracy deteriorates as the frame rate increases beyond a point where the detector’s readout noise begins to overwhelm the low number of photons detected in each frame. In contrast, we show that when an electron-multiplying charge-coupled device (EMCCD) detector is used, the estimation accuracy improves with increasing frame rate. In fact, at high frame rates where the low number of photons detected in each frame renders the fluorescent object difficult to detect visually, imaging with an EMCCD detector represents a natural implementation of the Ultrahigh Accuracy Imaging Modality, and enables estimation with an accuracy approaching that which is attainable only when a hypothetical noiseless detector is used. PMID:25321248

A novel x-ray detector design with higher DQE and reduced aliasing: Theoretical analysis of x-ray reabsoprtion in detector converter material

NASA Astrophysics Data System (ADS)

Nano, Tomi; Escartin, Terenz; Karim, Karim S.; Cunningham, Ian A.

2016-03-01

The ability to improve visualization of structural information in digital radiography without increasing radiation exposures requires improved image quality across all spatial frequencies, especially at high frequencies. The detective quantum efficiency (DQE) as a function of spatial frequency quantifies image quality given by an x-ray detector. We present a method of increasing DQE at high spatial frequencies by improving the modulation transfer function (MTF) and reducing noise aliasing. The Apodized Aperature Pixel (AAP) design uses a detector with micro-elements to synthesize desired pixels and provide higher DQE than conventional detector designs. A cascaded system analysis (CSA) that incorporates x-ray interactions is used for comparison of the theoretical MTF, noise power spectrum (NPS), and DQE. Signal and noise transfer through the converter material is shown to consist of correlated an uncorrelated terms. The AAP design was shown to improve the DQE of both material types that have predominantly correlated transfer (such as CsI) and predominantly uncorrelated transfer (such as Se). Improvement in the MTF by 50% and the DQE by 100% at the sampling cut-off frequency is obtained when uncorrelated transfer is prevalent through the converter material. Optimizing high-frequency DQE results in improved image contrast and visualization of small structures and fine-detail.

Sparsening Filter Design for Iterative Soft-Input Soft-Output Detectors

DTIC Science & Technology

2012-02-29

filter/detector structure. Since the BP detector itself is unaltered from [1], it can accommodate a system employing channel codes such as LDPC encoding...considered in [1], or can readily be extended to the MIMO case with, for example, space-time coding as in [2,8]. Since our focus is on the design of...simplex method of [15], since it was already available in Matlab , via the “fminsearch” function. 6 Cost surfaces To visualize the cost surfaces, consider

Facial identification in very low-resolution images simulating prosthetic vision.

PubMed

Chang, M H; Kim, H S; Shin, J H; Park, K S

2012-08-01

Familiar facial identification is important to blind or visually impaired patients and can be achieved using a retinal prosthesis. Nevertheless, there are limitations in delivering the facial images with a resolution sufficient to distinguish facial features, such as eyes and nose, through multichannel electrode arrays used in current visual prostheses. This study verifies the feasibility of familiar facial identification under low-resolution prosthetic vision and proposes an edge-enhancement method to deliver more visual information that is of higher quality. We first generated a contrast-enhanced image and an edge image by applying the Sobel edge detector and blocked each of them by averaging. Then, we subtracted the blocked edge image from the blocked contrast-enhanced image and produced a pixelized image imitating an array of phosphenes. Before subtraction, every gray value of the edge images was weighted as 50% (mode 2), 75% (mode 3) and 100% (mode 4). In mode 1, the facial image was blocked and pixelized with no further processing. The most successful identification was achieved with mode 3 at every resolution in terms of identification index, which covers both accuracy and correct response time. We also found that the subjects recognized a distinctive face especially more accurately and faster than the other given facial images even under low-resolution prosthetic vision. Every subject could identify familiar faces even in very low-resolution images. And the proposed edge-enhancement method seemed to contribute to intermediate-stage visual prostheses.

Visual search, visual streams, and visual architectures.

PubMed

Green, M

1991-10-01

Most psychological, physiological, and computational models of early vision suggest that retinal information is divided into a parallel set of feature modules. The dominant theories of visual search assume that these modules form a "blackboard" architecture: a set of independent representations that communicate only through a central processor. A review of research shows that blackboard-based theories, such as feature-integration theory, cannot easily explain the existing data. The experimental evidence is more consistent with a "network" architecture, which stresses that: (1) feature modules are directly connected to one another, (2) features and their locations are represented together, (3) feature detection and integration are not distinct processing stages, and (4) no executive control process, such as focal attention, is needed to integrate features. Attention is not a spotlight that synthesizes objects from raw features. Instead, it is better to conceptualize attention as an aperture which masks irrelevant visual information.

Assessment of image quality in soft tissue and bone visualization tasks for a dedicated extremity cone-beam CT system.

PubMed

Demehri, S; Muhit, A; Zbijewski, W; Stayman, J W; Yorkston, J; Packard, N; Senn, R; Yang, D; Foos, D; Thawait, G K; Fayad, L M; Chhabra, A; Carrino, J A; Siewerdsen, J H

2015-06-01

To assess visualization tasks using cone-beam CT (CBCT) compared to multi-detector CT (MDCT) for musculoskeletal extremity imaging. Ten cadaveric hands and ten knees were examined using a dedicated CBCT prototype and a clinical multi-detector CT using nominal protocols (80 kVp-108mAs for CBCT; 120 kVp- 300 mAs for MDCT). Soft tissue and bone visualization tasks were assessed by four radiologists using five-point satisfaction (for CBCT and MDCT individually) and five-point preference (side-by-side CBCT versus MDCT image quality comparison) rating tests. Ratings were analyzed using Kruskal-Wallis and Wilcoxon signed-rank tests, and observer agreement was assessed using the Kappa-statistic. Knee CBCT images were rated "excellent" or "good" (median scores 5 and 4) for "bone" and "soft tissue" visualization tasks. Hand CBCT images were rated "excellent" or "adequate" (median scores 5 and 3) for "bone" and "soft tissue" visualization tasks. Preference tests rated CBCT equivalent or superior to MDCT for bone visualization and favoured the MDCT for soft tissue visualization tasks. Intraobserver agreement for CBCT satisfaction tests was fair to almost perfect (κ ~ 0.26-0.92), and interobserver agreement was fair to moderate (κ ~ 0.27-0.54). CBCT provided excellent image quality for bone visualization and adequate image quality for soft tissue visualization tasks. • CBCT provided adequate image quality for diagnostic tasks in extremity imaging. • CBCT images were "excellent" for "bone" and "good/adequate" for "soft tissue" visualization tasks. • CBCT image quality was equivalent/superior to MDCT for bone visualization tasks.

Perceptual learning in visual search: fast, enduring, but non-specific.

PubMed

Sireteanu, R; Rettenbach, R

1995-07-01

Visual search has been suggested as a tool for isolating visual primitives. Elementary "features" were proposed to involve parallel search, while serial search is necessary for items without a "feature" status, or, in some cases, for conjunctions of "features". In this study, we investigated the role of practice in visual search tasks. We found that, under some circumstances, initially serial tasks can become parallel after a few hundred trials. Learning in visual search is far less specific than learning of visual discriminations and hyperacuity, suggesting that it takes place at another level in the central visual pathway, involving different neural circuits.

Impaired visual search in rats reveals cholinergic contributions to feature binding in visuospatial attention.

PubMed

Botly, Leigh C P; De Rosa, Eve

2012-10-01

The visual search task established the feature integration theory of attention in humans and measures visuospatial attentional contributions to feature binding. We recently demonstrated that the neuromodulator acetylcholine (ACh), from the nucleus basalis magnocellularis (NBM), supports the attentional processes required for feature binding using a rat digging-based task. Additional research has demonstrated cholinergic contributions from the NBM to visuospatial attention in rats. Here, we combined these lines of evidence and employed visual search in rats to examine whether cortical cholinergic input supports visuospatial attention specifically for feature binding. We trained 18 male Long-Evans rats to perform visual search using touch screen-equipped operant chambers. Sessions comprised Feature Search (no feature binding required) and Conjunctive Search (feature binding required) trials using multiple stimulus set sizes. Following acquisition of visual search, 8 rats received bilateral NBM lesions using 192 IgG-saporin to selectively reduce cholinergic afferentation of the neocortex, which we hypothesized would selectively disrupt the visuospatial attentional processes needed for efficient conjunctive visual search. As expected, relative to sham-lesioned rats, ACh-NBM-lesioned rats took significantly longer to locate the target stimulus on Conjunctive Search, but not Feature Search trials, thus demonstrating that cholinergic contributions to visuospatial attention are important for feature binding in rats.

Emulating the Visual Receptive Field Properties of MST Neurons with a Template Model of Heading Estimation

NASA Technical Reports Server (NTRS)

Perrone, John A.; Stone, Leland S.

1997-01-01

We have previously proposed a computational neural-network model by which the complex patterns of retinal image motion generated during locomotion (optic flow) can be processed by specialized detectors acting as templates for specific instances of self-motion. The detectors in this template model respond to global optic flow by sampling image motion over a large portion of the visual field through networks of local motion sensors with properties similar to neurons found in the middle temporal (MT) area of primate extrastriate visual cortex. The model detectors were designed to extract self-translation (heading), self-rotation, as well as the scene layout (relative distances) ahead of a moving observer, and are arranged in cortical-like heading maps to perform this function. Heading estimation from optic flow has been postulated by some to be implemented within the medial superior temporal (MST) area. Others have questioned whether MST neurons can fulfill this role because some of their receptive-field properties appear inconsistent with a role in heading estimation. To resolve this issue, we systematically compared MST single-unit responses with the outputs of model detectors under matched stimulus conditions. We found that the basic physiological properties of MST neurons can be explained by the template model. We conclude that MST neurons are well suited to support heading estimation and that the template model provides an explicit set of testable hypotheses which can guide future exploration of MST and adjacent areas within the primate superior temporal sulcus.

High-Sensitivity Ionization Trace-Species Detector

NASA Technical Reports Server (NTRS)

Bernius, Mark T.; Chutjian, Ara

1990-01-01

Features include high ion-extraction efficiency, compactness, and light weight. Improved version of previous ionization detector features in-line geometry that enables extraction of almost every ion from region of formation. Focusing electrodes arranged and shaped into compact system of space-charge-limited reversal electron optics and ion-extraction optics. Provides controllability of ionizing electron energies, greater efficiency of ionization, and nearly 100 percent ion-collection efficiency.

A Bubble Chamber Simulator: A New Tool for the Physics Classroom

ERIC Educational Resources Information Center

Gagnon, Michel

2011-01-01

Mainly used in the 1960s, bubble chambers played a major role in particle physics. Now replaced with modern electronic detectors, we believe they remain an important didactic tool to introduce particle physics as they provide visual, appealing and insightful pictures. Sadly, this rare type of detector is mostly accessible through open-door events…

Can responses to basic non-numerical visual features explain neural numerosity responses?

PubMed

Harvey, Ben M; Dumoulin, Serge O

2017-04-01

Humans and many animals can distinguish between stimuli that differ in numerosity, the number of objects in a set. Human and macaque parietal lobes contain neurons that respond to changes in stimulus numerosity. However, basic non-numerical visual features can affect neural responses to and perception of numerosity, and visual features often co-vary with numerosity. Therefore, it is debated whether numerosity or co-varying low-level visual features underlie neural and behavioral responses to numerosity. To test the hypothesis that non-numerical visual features underlie neural numerosity responses in a human parietal numerosity map, we analyze responses to a group of numerosity stimulus configurations that have the same numerosity progression but vary considerably in their non-numerical visual features. Using ultra-high-field (7T) fMRI, we measure responses to these stimulus configurations in an area of posterior parietal cortex whose responses are believed to reflect numerosity-selective activity. We describe an fMRI analysis method to distinguish between alternative models of neural response functions, following a population receptive field (pRF) modeling approach. For each stimulus configuration, we first quantify the relationships between numerosity and several non-numerical visual features that have been proposed to underlie performance in numerosity discrimination tasks. We then determine how well responses to these non-numerical visual features predict the observed fMRI responses, and compare this to the predictions of responses to numerosity. We demonstrate that a numerosity response model predicts observed responses more accurately than models of responses to simple non-numerical visual features. As such, neural responses in cognitive processing need not reflect simpler properties of early sensory inputs. Copyright © 2017 Elsevier Inc. All rights reserved.

Brain functional network connectivity based on a visual task: visual information processing-related brain regions are significantly activated in the task state.

PubMed

Yang, Yan-Li; Deng, Hong-Xia; Xing, Gui-Yang; Xia, Xiao-Luan; Li, Hai-Fang

2015-02-01

It is not clear whether the method used in functional brain-network related research can be applied to explore the feature binding mechanism of visual perception. In this study, we investigated feature binding of color and shape in visual perception. Functional magnetic resonance imaging data were collected from 38 healthy volunteers at rest and while performing a visual perception task to construct brain networks active during resting and task states. Results showed that brain regions involved in visual information processing were obviously activated during the task. The components were partitioned using a greedy algorithm, indicating the visual network existed during the resting state. Z-values in the vision-related brain regions were calculated, confirming the dynamic balance of the brain network. Connectivity between brain regions was determined, and the result showed that occipital and lingual gyri were stable brain regions in the visual system network, the parietal lobe played a very important role in the binding process of color features and shape features, and the fusiform and inferior temporal gyri were crucial for processing color and shape information. Experimental findings indicate that understanding visual feature binding and cognitive processes will help establish computational models of vision, improve image recognition technology, and provide a new theoretical mechanism for feature binding in visual perception.

Direct evidence for attention-dependent influences of the frontal eye-fields on feature-responsive visual cortex.

PubMed

Heinen, Klaartje; Feredoes, Eva; Weiskopf, Nikolaus; Ruff, Christian C; Driver, Jon

2014-11-01

Voluntary selective attention can prioritize different features in a visual scene. The frontal eye-fields (FEF) are one potential source of such feature-specific top-down signals, but causal evidence for influences on visual cortex (as was shown for "spatial" attention) has remained elusive. Here, we show that transcranial magnetic stimulation (TMS) applied to right FEF increased the blood oxygen level-dependent (BOLD) signals in visual areas processing "target feature" but not in "distracter feature"-processing regions. TMS-induced BOLD signals increase in motion-responsive visual cortex (MT+) when motion was attended in a display with moving dots superimposed on face stimuli, but in face-responsive fusiform area (FFA) when faces were attended to. These TMS effects on BOLD signal in both regions were negatively related to performance (on the motion task), supporting the behavioral relevance of this pathway. Our findings provide new causal evidence for the human FEF in the control of nonspatial "feature"-based attention, mediated by dynamic influences on feature-specific visual cortex that vary with the currently attended property. © The Author 2013. Published by Oxford University Press.

Cross-Modal Retrieval With CNN Visual Features: A New Baseline.

PubMed

Wei, Yunchao; Zhao, Yao; Lu, Canyi; Wei, Shikui; Liu, Luoqi; Zhu, Zhenfeng; Yan, Shuicheng

2017-02-01

Recently, convolutional neural network (CNN) visual features have demonstrated their powerful ability as a universal representation for various recognition tasks. In this paper, cross-modal retrieval with CNN visual features is implemented with several classic methods. Specifically, off-the-shelf CNN visual features are extracted from the CNN model, which is pretrained on ImageNet with more than one million images from 1000 object categories, as a generic image representation to tackle cross-modal retrieval. To further enhance the representational ability of CNN visual features, based on the pretrained CNN model on ImageNet, a fine-tuning step is performed by using the open source Caffe CNN library for each target data set. Besides, we propose a deep semantic matching method to address the cross-modal retrieval problem with respect to samples which are annotated with one or multiple labels. Extensive experiments on five popular publicly available data sets well demonstrate the superiority of CNN visual features for cross-modal retrieval.

Infrared and Visual Image Fusion through Fuzzy Measure and Alternating Operators

PubMed Central

Bai, Xiangzhi

2015-01-01

The crucial problem of infrared and visual image fusion is how to effectively extract the image features, including the image regions and details and combine these features into the final fusion result to produce a clear fused image. To obtain an effective fusion result with clear image details, an algorithm for infrared and visual image fusion through the fuzzy measure and alternating operators is proposed in this paper. Firstly, the alternating operators constructed using the opening and closing based toggle operator are analyzed. Secondly, two types of the constructed alternating operators are used to extract the multi-scale features of the original infrared and visual images for fusion. Thirdly, the extracted multi-scale features are combined through the fuzzy measure-based weight strategy to form the final fusion features. Finally, the final fusion features are incorporated with the original infrared and visual images using the contrast enlargement strategy. All the experimental results indicate that the proposed algorithm is effective for infrared and visual image fusion. PMID:26184229

Infrared and Visual Image Fusion through Fuzzy Measure and Alternating Operators.

PubMed

Bai, Xiangzhi

2015-07-15

The crucial problem of infrared and visual image fusion is how to effectively extract the image features, including the image regions and details and combine these features into the final fusion result to produce a clear fused image. To obtain an effective fusion result with clear image details, an algorithm for infrared and visual image fusion through the fuzzy measure and alternating operators is proposed in this paper. Firstly, the alternating operators constructed using the opening and closing based toggle operator are analyzed. Secondly, two types of the constructed alternating operators are used to extract the multi-scale features of the original infrared and visual images for fusion. Thirdly, the extracted multi-scale features are combined through the fuzzy measure-based weight strategy to form the final fusion features. Finally, the final fusion features are incorporated with the original infrared and visual images using the contrast enlargement strategy. All the experimental results indicate that the proposed algorithm is effective for infrared and visual image fusion.

Apparatus for generating x-ray holograms

DOEpatents

Rhodes, C.K.; Boyer, K.; Solem, J.C.; Haddad, W.S.

1990-09-11

Apparatus for x-ray microholography of living biological materials. A Fourier transform holographic configuration is described as being most suitable for the 3-dimensional recording of the physical characteristics of biological specimens. The use of a spherical scatterer as a reference and a charge-coupled device two-dimensional detector array placed in the forward direction relative to the incident x-radiation for viewing electromagnetic radiation simultaneously scattered from both the specimen and the reference scatterer permits the ready reconstruction of the details of the specimen from the fringe pattern detected by the charge-coupled device. For example, by using a nickel reference scatter at 4.5 nm, sufficient reference illumination is provided over a wide enough angle to allow similar resolution in both transverse and longitudinal directions. Both laser and synchrotron radiation sources are feasible for generating microholographs. Operation in the water window (2.4 to 4.5 nm) should provide maximum contrast for features of the specimen and spatial resolution on the order of the wavelength of x-radiation should be possible in all three dimensions, which is sufficient for the visualization of many biological features. It is anticipated that the present apparatus will find utility in other areas as well where microscopic physical details of a specimen are important. A computational procedure which enables the holographic data collected by the detector to be used to correct for misalignments introduced by inexact knowledge of the relative positions of the spherical reference scatterer and the sample under investigation has been developed. If the correction is performed prior to reconstruction, full compensation can be achieved and a faithfully reconstructed image produced. 7 figs.

Apparatus for generating x-ray holograms

DOEpatents

Rhodes, Charles K.; Boyer, Keith; Solem, Johndale C.; Haddad, Waleed S.

1990-01-01

Apparatus for x-ray microholography of living biological materials. A Fourier transform holographic configuration is described as being most suitable for the 3-dimensional recording of the physical characteristics of biological specimens. The use of a spherical scatterer as a reference and a charge-coupled device two-dimensional detector array placed in the forward direction relative to the incident x-radiation for viewing electromagnetic radiation simultaneously scattered from both the specimen and the reference scatterer permits the ready reconstruction of the details of the specimen from the fringe pattern detected by the charge-coupled device. For example, by using a nickel reference scatter at 4.5 nm, sufficient reference illumination is provided over a wide enough angle to allow similar resolution in both transverse and longitudinal directions. Both laser and synchrotron radiation sources are feasible for generating microholographs. Operation in the water window (2.4 to 4.5 nm) should provide maximum contrast for features of the specimen and spatial resolution on the order of the wavelength of x-radiation should be possible in all three dimensions, which is sufficient for the visualization of many biological features. It is anticipated that the present apparatus will find utility in other areas as well where microscopic physical details of a specimen are important. A computational procedure which enables the holographic data collected by the detector to be used to correct for misalignments introduced by inexact knowledge of the relative positions of the spherical reference scatterer and the sample under investigation has been developed. If the correction is performed prior to reconstruction, full compensation can be achieved and a faithfully reconstructed image produced.

Learning to rank using user clicks and visual features for image retrieval.

PubMed

Yu, Jun; Tao, Dacheng; Wang, Meng; Rui, Yong

2015-04-01

The inconsistency between textual features and visual contents can cause poor image search results. To solve this problem, click features, which are more reliable than textual information in justifying the relevance between a query and clicked images, are adopted in image ranking model. However, the existing ranking model cannot integrate visual features, which are efficient in refining the click-based search results. In this paper, we propose a novel ranking model based on the learning to rank framework. Visual features and click features are simultaneously utilized to obtain the ranking model. Specifically, the proposed approach is based on large margin structured output learning and the visual consistency is integrated with the click features through a hypergraph regularizer term. In accordance with the fast alternating linearization method, we design a novel algorithm to optimize the objective function. This algorithm alternately minimizes two different approximations of the original objective function by keeping one function unchanged and linearizing the other. We conduct experiments on a large-scale dataset collected from the Microsoft Bing image search engine, and the results demonstrate that the proposed learning to rank models based on visual features and user clicks outperforms state-of-the-art algorithms.

Visual search for feature and conjunction targets with an attention deficit.

PubMed

Arguin, M; Joanette, Y; Cavanagh, P

1993-01-01

Abstract Brain-damaged subjects who had previously been identified as suffering from a visual attention deficit for contralesional stimulation were tested on a series of visual search tasks. The experiments examined the hypothesis that the processing of single features is preattentive but that feature integration, necessary for the correct perception of conjunctions of features, requires attention (Treisman & Gelade, 1980 Treisman & Sato, 1990). Subjects searched for a feature target (orientation or color) or for a conjunction target (orientation and color) in unilateral displays in which the number of items presented was variable. Ocular fixation was controlled so that trials on which eye movements occurred were cancelled. While brain-damaged subjects with a visual attention disorder (VAD subjects) performed similarly to normal controls in feature search tasks, they showed a marked deficit in conjunction search. Specifically, VAD subjects exhibited an important reduction of their serial search rates for a conjunction target with contralesional displays. In support of Treisman's feature integration theory, a visual attention deficit leads to a marked impairment in feature integration whereas it does not appear to affect feature encoding.

Dynamic binding of visual features by neuronal/stimulus synchrony.

PubMed

Iwabuchi, A

1998-05-01

When people see a visual scene, certain parts of the visual scene are treated as belonging together and we regard them as a perceptual unit, which is called a "figure". People focus on figures, and the remaining parts of the scene are disregarded as "ground". In Gestalt psychology this process is called "figure-ground segregation". According to current perceptual psychology, a figure is formed by binding various visual features in a scene, and developments in neuroscience have revealed that there are many feature-encoding neurons, which respond to such features specifically. It is not known, however, how the brain binds different features of an object into a coherent visual object representation. Recently, the theory of binding by neuronal synchrony, which argues that feature binding is dynamically mediated by neuronal synchrony of feature-encoding neurons, has been proposed. This review article portrays the problem of figure-ground segregation and features binding, summarizes neurophysiological and psychophysical experiments and theory relevant to feature binding by neuronal/stimulus synchrony, and suggests possible directions for future research on this topic.

Event visualization in ATLAS

NASA Astrophysics Data System (ADS)

Bianchi, R. M.; Boudreau, J.; Konstantinidis, N.; Martyniuk, A. C.; Moyse, E.; Thomas, J.; Waugh, B. M.; Yallup, D. P.; ATLAS Collaboration

2017-10-01

At the beginning, HEP experiments made use of photographical images both to record and store experimental data and to illustrate their findings. Then the experiments evolved and needed to find ways to visualize their data. With the availability of computer graphics, software packages to display event data and the detector geometry started to be developed. Here, an overview of the usage of event display tools in HEP is presented. Then the case of the ATLAS experiment is considered in more detail and two widely used event display packages are presented, Atlantis and VP1, focusing on the software technologies they employ, as well as their strengths, differences and their usage in the experiment: from physics analysis to detector development, and from online monitoring to outreach and communication. Towards the end, the other ATLAS visualization tools will be briefly presented as well. Future development plans and improvements in the ATLAS event display packages will also be discussed.

Multiple-Parameter, Low-False-Alarm Fire-Detection Systems

NASA Technical Reports Server (NTRS)

Hunter, Gary W.; Greensburg, Paul; McKnight, Robert; Xu, Jennifer C.; Liu, C. C.; Dutta, Prabir; Makel, Darby; Blake, D.; Sue-Antillio, Jill

2007-01-01

Fire-detection systems incorporating multiple sensors that measure multiple parameters are being developed for use in storage depots, cargo bays of ships and aircraft, and other locations not amenable to frequent, direct visual inspection. These systems are intended to improve upon conventional smoke detectors, now used in such locations, that reliably detect fires but also frequently generate false alarms: for example, conventional smoke detectors based on the blockage of light by smoke particles are also affected by dust particles and water droplets and, thus, are often susceptible to false alarms. In contrast, by utilizing multiple parameters associated with fires, i.e. not only obscuration by smoke particles but also concentrations of multiple chemical species that are commonly generated in combustion, false alarms can be significantly decreased while still detecting fires as reliably as older smoke-detector systems do. The present development includes fabrication of sensors that have, variously, micrometer- or nanometer-sized features so that such multiple sensors can be integrated into arrays that have sizes, weights, and power demands smaller than those of older macroscopic sensors. The sensors include resistors, electrochemical cells, and Schottky diodes that exhibit different sensitivities to the various airborne chemicals of interest. In a system of this type, the sensor readings are digitized and processed by advanced signal-processing hardware and software to extract such chemical indications of fires as abnormally high concentrations of CO and CO2, possibly in combination with H2 and/or hydrocarbons. The system also includes a microelectromechanical systems (MEMS)-based particle detector and classifier device to increase the reliability of measurements of chemical species and particulates. In parallel research, software for modeling the evolution of a fire within an aircraft cargo bay has been developed. The model implemented in the software can describe the concentrations of chemical species and of particulate matter as functions of time. A system of the present developmental type and a conventional fire detector were tested under both fire and false-alarm conditions in a Federal Aviation Administration cargo-compartment- testing facility. Both systems consistently detected fires. However, the conventional fire detector consistently generated false alarms, whereas the developmental system did not generate any false alarms.

Feature Masking in Computer Game Promotes Visual Imagery

ERIC Educational Resources Information Center

Smith, Glenn Gordon; Morey, Jim; Tjoe, Edwin

2007-01-01

Can learning of mental imagery skills for visualizing shapes be accelerated with feature masking? Chemistry, physics fine arts, military tactics, and laparoscopic surgery often depend on mentally visualizing shapes in their absence. Does working with "spatial feature-masks" (skeletal shapes, missing key identifying portions) encourage people to…

Computer-aided Classification of Mammographic Masses Using Visually Sensitive Image Features

PubMed Central

Wang, Yunzhi; Aghaei, Faranak; Zarafshani, Ali; Qiu, Yuchen; Qian, Wei; Zheng, Bin

2017-01-01

Purpose To develop a new computer-aided diagnosis (CAD) scheme that computes visually sensitive image features routinely used by radiologists to develop a machine learning classifier and distinguish between the malignant and benign breast masses detected from digital mammograms. Methods An image dataset including 301 breast masses was retrospectively selected. From each segmented mass region, we computed image features that mimic five categories of visually sensitive features routinely used by radiologists in reading mammograms. We then selected five optimal features in the five feature categories and applied logistic regression models for classification. A new CAD interface was also designed to show lesion segmentation, computed feature values and classification score. Results Areas under ROC curves (AUC) were 0.786±0.026 and 0.758±0.027 when to classify mass regions depicting on two view images, respectively. By fusing classification scores computed from two regions, AUC increased to 0.806±0.025. Conclusion This study demonstrated a new approach to develop CAD scheme based on 5 visually sensitive image features. Combining with a “visual aid” interface, CAD results may be much more easily explainable to the observers and increase their confidence to consider CAD generated classification results than using other conventional CAD approaches, which involve many complicated and visually insensitive texture features. PMID:27911353

How Configural Is the Configural Superiority Effect? A Neuroimaging Investigation of Emergent Features in Visual Cortex

PubMed Central

Fox, Olivia M.; Harel, Assaf; Bennett, Kevin B.

2017-01-01

The perception of a visual stimulus is dependent not only upon local features, but also on the arrangement of those features. When stimulus features are perceptually well organized (e.g., symmetric or parallel), a global configuration with a high degree of salience emerges from the interactions between these features, often referred to as emergent features. Emergent features can be demonstrated in the Configural Superiority Effect (CSE): presenting a stimulus within an organized context relative to its presentation in a disarranged one results in better performance. Prior neuroimaging work on the perception of emergent features regards the CSE as an “all or none” phenomenon, focusing on the contrast between configural and non-configural stimuli. However, it is still not clear how emergent features are processed between these two endpoints. The current study examined the extent to which behavioral and neuroimaging markers of emergent features are responsive to the degree of configurality in visual displays. Subjects were tasked with reporting the anomalous quadrant in a visual search task while being scanned. Degree of configurality was manipulated by incrementally varying the rotational angle of low-level features within the stimulus arrays. Behaviorally, we observed faster response times with increasing levels of configurality. These behavioral changes were accompanied by increases in response magnitude across multiple visual areas in occipito-temporal cortex, primarily early visual cortex and object-selective cortex. Our findings suggest that the neural correlates of emergent features can be observed even in response to stimuli that are not fully configural, and demonstrate that configural information is already present at early stages of the visual hierarchy. PMID:28167924

Improved multi-stage neonatal seizure detection using a heuristic classifier and a data-driven post-processor.

PubMed

Ansari, A H; Cherian, P J; Dereymaeker, A; Matic, V; Jansen, K; De Wispelaere, L; Dielman, C; Vervisch, J; Swarte, R M; Govaert, P; Naulaers, G; De Vos, M; Van Huffel, S

2016-09-01

After identifying the most seizure-relevant characteristics by a previously developed heuristic classifier, a data-driven post-processor using a novel set of features is applied to improve the performance. The main characteristics of the outputs of the heuristic algorithm are extracted by five sets of features including synchronization, evolution, retention, segment, and signal features. Then, a support vector machine and a decision making layer remove the falsely detected segments. Four datasets including 71 neonates (1023h, 3493 seizures) recorded in two different university hospitals, are used to train and test the algorithm without removing the dubious seizures. The heuristic method resulted in a false alarm rate of 3.81 per hour and good detection rate of 88% on the entire test databases. The post-processor, effectively reduces the false alarm rate by 34% while the good detection rate decreases by 2%. This post-processing technique improves the performance of the heuristic algorithm. The structure of this post-processor is generic, improves our understanding of the core visually determined EEG features of neonatal seizures and is applicable for other neonatal seizure detectors. The post-processor significantly decreases the false alarm rate at the expense of a small reduction of the good detection rate. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Internal attention to features in visual short-term memory guides object learning

PubMed Central

Fan, Judith E.; Turk-Browne, Nicholas B.

2013-01-01

Attending to objects in the world affects how we perceive and remember them. What are the consequences of attending to an object in mind? In particular, how does reporting the features of a recently seen object guide visual learning? In three experiments, observers were presented with abstract shapes in a particular color, orientation, and location. After viewing each object, observers were cued to report one feature from visual short-term memory (VSTM). In a subsequent test, observers were cued to report features of the same objects from visual long-term memory (VLTM). We tested whether reporting a feature from VSTM: (1) enhances VLTM for just that feature (practice-benefit hypothesis), (2) enhances VLTM for all features (object-based hypothesis), or (3) simultaneously enhances VLTM for that feature and suppresses VLTM for unreported features (feature-competition hypothesis). The results provided support for the feature-competition hypothesis, whereby the representation of an object in VLTM was biased towards features reported from VSTM and away from unreported features (Experiment 1). This bias could not be explained by the amount of sensory exposure or response learning (Experiment 2) and was amplified by the reporting of multiple features (Experiment 3). Taken together, these results suggest that selective internal attention induces competitive dynamics among features during visual learning, flexibly tuning object representations to align with prior mnemonic goals. PMID:23954925

Internal attention to features in visual short-term memory guides object learning.

PubMed

Fan, Judith E; Turk-Browne, Nicholas B

2013-11-01

Attending to objects in the world affects how we perceive and remember them. What are the consequences of attending to an object in mind? In particular, how does reporting the features of a recently seen object guide visual learning? In three experiments, observers were presented with abstract shapes in a particular color, orientation, and location. After viewing each object, observers were cued to report one feature from visual short-term memory (VSTM). In a subsequent test, observers were cued to report features of the same objects from visual long-term memory (VLTM). We tested whether reporting a feature from VSTM: (1) enhances VLTM for just that feature (practice-benefit hypothesis), (2) enhances VLTM for all features (object-based hypothesis), or (3) simultaneously enhances VLTM for that feature and suppresses VLTM for unreported features (feature-competition hypothesis). The results provided support for the feature-competition hypothesis, whereby the representation of an object in VLTM was biased towards features reported from VSTM and away from unreported features (Experiment 1). This bias could not be explained by the amount of sensory exposure or response learning (Experiment 2) and was amplified by the reporting of multiple features (Experiment 3). Taken together, these results suggest that selective internal attention induces competitive dynamics among features during visual learning, flexibly tuning object representations to align with prior mnemonic goals. Copyright © 2013 Elsevier B.V. All rights reserved.

Towards an Optimal Interest Point Detector for Measurements in Ultrasound Images

NASA Astrophysics Data System (ADS)

Zukal, Martin; Beneš, Radek; Číka, Petr; Říha, Kamil

2013-12-01

This paper focuses on the comparison of different interest point detectors and their utilization for measurements in ultrasound (US) images. Certain medical examinations are based on speckle tracking which strongly relies on features that can be reliably tracked frame to frame. Only significant features (interest points) resistant to noise and brightness changes within US images are suitable for accurate long-lasting tracking. We compare three interest point detectors - Harris-Laplace, Difference of Gaussian (DoG) and Fast Hessian - and identify the most suitable one for use in US images on the basis of an objective criterion. Repeatability rate is assumed to be an objective quality measure for comparison. We have measured repeatability in images corrupted by different types of noise (speckle noise, Gaussian noise) and for changes in brightness. The Harris-Laplace detector outperformed its competitors and seems to be a sound option when choosing a suitable interest point detector for US images. However, it has to be noted that Fast Hessian and DoG detectors achieved better results in terms of processing speed.

CMOS SiPM with integrated amplifier

NASA Astrophysics Data System (ADS)

Schwinger, Alexander; Brockherde, Werner; Hosticka, Bedrich J.; Vogt, Holger

2017-02-01

The integration of silicon photomultiplier (SiPM) and frontend electronics in a suitable optoelectronic CMOS process is a promising approach to increase the versatility of single-photon avalanche diode (SPAD)-based singlephoton detectors. By integrating readout amplifiers, the device output capacitance can be reduced to minimize the waveform tail, which is especially important for large area detectors (>10 × 10mm2). Possible architectures include a single readout amplifier for the whole detector, which reduces the output capacitance to 1:1 pF at minimal reduction in detector active area. On the other hand, including a readout amplifier in every SiPM cell would greatly improve the total output capacitance by minimizing the influence of metal routing parasitic capacitance, but requiring a prohibitive amount of detector area. As tradeoff, the proposed detector features one readout amplifier for each column of the detector matrix to allow for a moderate reduction in output capacitance while allowing the electronics to be placed in the periphery of the active detector area. The presented detector with a total size of 1.7 ♢ 1.0mm2 features 400 cells with a 50 μm pitch, where the signal of each column of 20 SiPM cells is summed in a readout channel. The 20 readout channels are subsequently summed into one output channel, to allow the device to be used as a drop-in replacement for commonly used analog SiPMs.

A Novel Image Retrieval Based on Visual Words Integration of SIFT and SURF

PubMed Central

Ali, Nouman; Bajwa, Khalid Bashir; Sablatnig, Robert; Chatzichristofis, Savvas A.; Iqbal, Zeshan; Rashid, Muhammad; Habib, Hafiz Adnan

2016-01-01

With the recent evolution of technology, the number of image archives has increased exponentially. In Content-Based Image Retrieval (CBIR), high-level visual information is represented in the form of low-level features. The semantic gap between the low-level features and the high-level image concepts is an open research problem. In this paper, we present a novel visual words integration of Scale Invariant Feature Transform (SIFT) and Speeded-Up Robust Features (SURF). The two local features representations are selected for image retrieval because SIFT is more robust to the change in scale and rotation, while SURF is robust to changes in illumination. The visual words integration of SIFT and SURF adds the robustness of both features to image retrieval. The qualitative and quantitative comparisons conducted on Corel-1000, Corel-1500, Corel-2000, Oliva and Torralba and Ground Truth image benchmarks demonstrate the effectiveness of the proposed visual words integration. PMID:27315101

Toward semantic-based retrieval of visual information: a model-based approach

NASA Astrophysics Data System (ADS)

Park, Youngchoon; Golshani, Forouzan; Panchanathan, Sethuraman

2002-07-01

This paper center around the problem of automated visual content classification. To enable classification based image or visual object retrieval, we propose a new image representation scheme called visual context descriptor (VCD) that is a multidimensional vector in which each element represents the frequency of a unique visual property of an image or a region. VCD utilizes the predetermined quality dimensions (i.e., types of features and quantization level) and semantic model templates mined in priori. Not only observed visual cues, but also contextually relevant visual features are proportionally incorporated in VCD. Contextual relevance of a visual cue to a semantic class is determined by using correlation analysis of ground truth samples. Such co-occurrence analysis of visual cues requires transformation of a real-valued visual feature vector (e.g., color histogram, Gabor texture, etc.,) into a discrete event (e.g., terms in text). Good-feature to track, rule of thirds, iterative k-means clustering and TSVQ are involved in transformation of feature vectors into unified symbolic representations called visual terms. Similarity-based visual cue frequency estimation is also proposed and used for ensuring the correctness of model learning and matching since sparseness of sample data causes the unstable results of frequency estimation of visual cues. The proposed method naturally allows integration of heterogeneous visual or temporal or spatial cues in a single classification or matching framework, and can be easily integrated into a semantic knowledge base such as thesaurus, and ontology. Robust semantic visual model template creation and object based image retrieval are demonstrated based on the proposed content description scheme.

The CosmicWatch Desktop Muon Detector: a self-contained, pocket sized particle detector

NASA Astrophysics Data System (ADS)

Axani, S. N.; Frankiewicz, K.; Conrad, J. M.

2018-03-01

The CosmicWatch Desktop Muon Detector is a self-contained, hand-held cosmic ray muon detector that is valuable for astro/particle physics research applications and outreach. The material cost of each detector is under 100 and it takes a novice student approximately four hours to build their first detector. The detectors are powered via a USB connection and the data can either be recorded directly to a computer or to a microSD card. Arduino- and Python-based software is provided to operate the detector and an online application to plot the data in real-time. In this paper, we describe the various design features, evaluate the performance, and illustrate the detectors capabilities by providing several example measurements.

Effects of Spatial and Feature Attention on Disparity-Rendered Structure-From-Motion Stimuli in the Human Visual Cortex

PubMed Central

Ip, Ifan Betina; Bridge, Holly; Parker, Andrew J.

2014-01-01

An important advance in the study of visual attention has been the identification of a non-spatial component of attention that enhances the response to similar features or objects across the visual field. Here we test whether this non-spatial component can co-select individual features that are perceptually bound into a coherent object. We combined human psychophysics and functional magnetic resonance imaging (fMRI) to demonstrate the ability to co-select individual features from perceptually coherent objects. Our study used binocular disparity and visual motion to define disparity structure-from-motion (dSFM) stimuli. Although the spatial attention system induced strong modulations of the fMRI response in visual regions, the non-spatial system’s ability to co-select features of the dSFM stimulus was less pronounced and variable across subjects. Our results demonstrate that feature and global feature attention effects are variable across participants, suggesting that the feature attention system may be limited in its ability to automatically select features within the attended object. Careful comparison of the task design suggests that even minor differences in the perceptual task may be critical in revealing the presence of global feature attention. PMID:24936974

Computing local edge probability in natural scenes from a population of oriented simple cells

PubMed Central

Ramachandra, Chaithanya A.; Mel, Bartlett W.

2013-01-01

A key computation in visual cortex is the extraction of object contours, where the first stage of processing is commonly attributed to V1 simple cells. The standard model of a simple cell—an oriented linear filter followed by a divisive normalization—fits a wide variety of physiological data, but is a poor performing local edge detector when applied to natural images. The brain's ability to finely discriminate edges from nonedges therefore likely depends on information encoded by local simple cell populations. To gain insight into the corresponding decoding problem, we used Bayes's rule to calculate edge probability at a given location/orientation in an image based on a surrounding filter population. Beginning with a set of ∼ 100 filters, we culled out a subset that were maximally informative about edges, and minimally correlated to allow factorization of the joint on- and off-edge likelihood functions. Key features of our approach include a new, efficient method for ground-truth edge labeling, an emphasis on achieving filter independence, including a focus on filters in the region orthogonal rather than tangential to an edge, and the use of a customized parametric model to represent the individual filter likelihood functions. The resulting population-based edge detector has zero parameters, calculates edge probability based on a sum of surrounding filter influences, is much more sharply tuned than the underlying linear filters, and effectively captures fine-scale edge structure in natural scenes. Our findings predict nonmonotonic interactions between cells in visual cortex, wherein a cell may for certain stimuli excite and for other stimuli inhibit the same neighboring cell, depending on the two cells' relative offsets in position and orientation, and their relative activation levels. PMID:24381295

Proton radiography and fluoroscopy of lung tumors: A Monte Carlo study using patient-specific 4DCT phantoms

PubMed Central

Han, Bin; Xu, X. George; Chen, George T. Y.

2011-01-01

Purpose: Monte Carlo methods are used to simulate and optimize a time-resolved proton range telescope (TRRT) in localization of intrafractional and interfractional motions of lung tumor and in quantification of proton range variations. Methods: The Monte Carlo N-Particle eXtended (MCNPX) code with a particle tracking feature was employed to evaluate the TRRT performance, especially in visualizing and quantifying proton range variations during respiration. Protons of 230 MeV were tracked one by one as they pass through position detectors, patient 4DCT phantom, and finally scintillator detectors that measured residual ranges. The energy response of the scintillator telescope was investigated. Mass density and elemental composition of tissues were defined for 4DCT data. Results: Proton water equivalent length (WEL) was deduced by a reconstruction algorithm that incorporates linear proton track and lateral spatial discrimination to improve the image quality. 4DCT data for three patients were used to visualize and measure tumor motion and WEL variations. The tumor trajectories extracted from the WEL map were found to be within ∼1 mm agreement with direct 4DCT measurement. Quantitative WEL variation studies showed that the proton radiograph is a good representation of WEL changes from entrance to distal of the target. Conclusions:MCNPX simulation results showed that TRRT can accurately track the motion of the tumor and detect the WEL variations. Image quality was optimized by choosing proton energy, testing parameters of image reconstruction algorithm, and comparing to ground truth 4DCT. The future study will demonstrate the feasibility of using the time resolved proton radiography as an imaging tool for proton treatments of lung tumors. PMID:21626923

Microradiography with Semiconductor Pixel Detectors

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

Jakubek, Jan; Cejnarova, Andrea; Dammer, Jiri

High resolution radiography (with X-rays, neutrons, heavy charged particles, ...) often exploited also in tomographic mode to provide 3D images stands as a powerful imaging technique for instant and nondestructive visualization of fine internal structure of objects. Novel types of semiconductor single particle counting pixel detectors offer many advantages for radiation imaging: high detection efficiency, energy discrimination or direct energy measurement, noiseless digital integration (counting), high frame rate and virtually unlimited dynamic range. This article shows the application and potential of pixel detectors (such as Medipix2 or TimePix) in different fields of radiation imaging.

Epileptic seizure onset detection based on EEG and ECG data fusion.

PubMed

Qaraqe, Marwa; Ismail, Muhammad; Serpedin, Erchin; Zulfi, Haneef

2016-05-01

This paper presents a novel method for seizure onset detection using fused information extracted from multichannel electroencephalogram (EEG) and single-channel electrocardiogram (ECG). In existing seizure detectors, the analysis of the nonlinear and nonstationary ECG signal is limited to the time-domain or frequency-domain. In this work, heart rate variability (HRV) extracted from ECG is analyzed using a Matching-Pursuit (MP) and Wigner-Ville Distribution (WVD) algorithm in order to effectively extract meaningful HRV features representative of seizure and nonseizure states. The EEG analysis relies on a common spatial pattern (CSP) based feature enhancement stage that enables better discrimination between seizure and nonseizure features. The EEG-based detector uses logical operators to pool SVM seizure onset detections made independently across different EEG spectral bands. Two fusion systems are adopted. In the first system, EEG-based and ECG-based decisions are directly fused to obtain a final decision. The second fusion system adopts an override option that allows for the EEG-based decision to override the fusion-based decision in the event that the detector observes a string of EEG-based seizure decisions. The proposed detectors exhibit an improved performance, with respect to sensitivity and detection latency, compared with the state-of-the-art detectors. Experimental results demonstrate that the second detector achieves a sensitivity of 100%, detection latency of 2.6s, and a specificity of 99.91% for the MAJ fusion case. Copyright © 2016 Elsevier Inc. All rights reserved.

Performance of a Commercial Silicon Drift Detector for X-ray Microanalysis

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

Kenik, Edward A

2008-01-01

Silicon drift detectors (SDDs) are rapidly becoming the energy dispersive spectrometer of choice especially for scanning electron microscopy applications. The complementary features of large active areas (i.e., collection angle) and high count rate capability of these detector contribute to their popularity, as well as the absence of liquid nitrogen cooling of the detector. The performance of an EDAX Apollo 40 SDD on a JEOL 6500F SEM will be discussed.

Looking at Op Art from a computational viewpoint.

PubMed

Zanker, Johannes M

2004-01-01

Arts history tells an exciting story about repeated attempts to represent features that are crucial for the understanding of our environment and which, at the same time, go beyond the inherently two-dimensional nature of a flat painting surface: depth and motion. In the twentieth century, Op artists such as Bridget Riley began to experiment with simple black and white patterns that do not represent motion in an artistic way but actually create vivid dynamic illusions in static pictures. The cause of motion illusions in such paintings is still a matter of debate. The role of involuntary eye movements in this phenomenon is studied here with a computational approach. The possible consequences of shifting the retinal image of synthetic wave gratings, dubbed as 'riloids', were analysed by a two-dimensional array of motion detectors (2DMD model), which generates response maps representing the spatial distribution of motion signals generated by such a stimulus. For a two-frame sequence reflecting a saccadic displacement, these motion signal maps contain extended patches in which local directions change only little. These directions, however, do not usually precisely correspond to the direction of pattern displacement that can be expected from the geometry of the curved gratings as an instance of the so-called 'aperture problem'. The patchy structure of the simulated motion detector response to the displacement of riloids resembles the motion illusion, which is not perceived as a coherent shift of the whole pattern but as a wobbling and jazzing of ill-defined regions. Although other explanations are not excluded, this might support the view that the puzzle of Op Art motion illusions could potentially have an almost trivial solution in terms of small involuntary eye movement leading to image shifts that are picked up by well-known motion detectors in the early visual system. This view can have further consequences for our understanding of how the human visual system usually compensates for eye movements, in order to let us perceive a stable world despite continuous image shifts generated by gaze instability.

Linear and Non-Linear Visual Feature Learning in Rat and Humans

PubMed Central

Bossens, Christophe; Op de Beeck, Hans P.

2016-01-01

The visual system processes visual input in a hierarchical manner in order to extract relevant features that can be used in tasks such as invariant object recognition. Although typically investigated in primates, recent work has shown that rats can be trained in a variety of visual object and shape recognition tasks. These studies did not pinpoint the complexity of the features used by these animals. Many tasks might be solved by using a combination of relatively simple features which tend to be correlated. Alternatively, rats might extract complex features or feature combinations which are nonlinear with respect to those simple features. In the present study, we address this question by starting from a small stimulus set for which one stimulus-response mapping involves a simple linear feature to solve the task while another mapping needs a well-defined nonlinear combination of simpler features related to shape symmetry. We verified computationally that the nonlinear task cannot be trivially solved by a simple V1-model. We show how rats are able to solve the linear feature task but are unable to acquire the nonlinear feature. In contrast, humans are able to use the nonlinear feature and are even faster in uncovering this solution as compared to the linear feature. The implications for the computational capabilities of the rat visual system are discussed. PMID:28066201

STED microscopy visualizes energy deposition of single ions in a solid-state detector beyond diffraction limit

NASA Astrophysics Data System (ADS)

Niklas, M.; Henrich, M.; Jäkel, O.; Engelhardt, J.; Abdollahi, A.; Greilich, S.

2017-05-01

Fluorescent nuclear track detectors (FNTDs) allow for visualization of single-particle traversal in clinical ion beams. The point spread function of the confocal readout has so far hindered a more detailed characterization of the track spots—the ion’s characteristic signature left in the FNTD. Here we report on the readout of the FNTD by optical nanoscopy, namely stimulated emission depletion microscopy. It was firstly possible to visualize the track spots of carbon ions and protons beyond the diffraction limit of conventional light microscopy with a resolving power of approximately 80 nm (confocal: 320 nm). A clear discrimination of the spatial width, defined by the full width half maximum of track spots from particles (proton and carbon ions), with a linear energy transfer (LET) ranging from approximately 2-1016 keV µm-1 was possible. Results suggest that the width depends on LET but not on particle charge within the uncertainties. A discrimination of particle type by width thus does not seem possible (as well as with confocal microscopy). The increased resolution, however, could allow for refined determination of the cross-sectional area facing substantial energy deposition. This work could pave the way towards development of optical nanoscopy-based analysis of radiation-induced cellular response using cell-fluorescent ion track hybrid detectors.

Stimulus information contaminates summation tests of independent neural representations of features

NASA Technical Reports Server (NTRS)

Shimozaki, Steven S.; Eckstein, Miguel P.; Abbey, Craig K.

2002-01-01

Many models of visual processing assume that visual information is analyzed into separable and independent neural codes, or features. A common psychophysical test of independent features is known as a summation study, which measures performance in a detection, discrimination, or visual search task as the number of proposed features increases. Improvement in human performance with increasing number of available features is typically attributed to the summation, or combination, of information across independent neural coding of the features. In many instances, however, increasing the number of available features also increases the stimulus information in the task, as assessed by an optimal observer that does not include the independent neural codes. In a visual search task with spatial frequency and orientation as the component features, a particular set of stimuli were chosen so that all searches had equivalent stimulus information, regardless of the number of features. In this case, human performance did not improve with increasing number of features, implying that the improvement observed with additional features may be due to stimulus information and not the combination across independent features.

The development of organized visual search

PubMed Central

Woods, Adam J.; Goksun, Tilbe; Chatterjee, Anjan; Zelonis, Sarah; Mehta, Anika; Smith, Sabrina E.

2013-01-01

Visual search plays an important role in guiding behavior. Children have more difficulty performing conjunction search tasks than adults. The present research evaluates whether developmental differences in children's ability to organize serial visual search (i.e., search organization skills) contribute to performance limitations in a typical conjunction search task. We evaluated 134 children between the ages of 2 and 17 on separate tasks measuring search for targets defined by a conjunction of features or by distinct features. Our results demonstrated that children organize their visual search better as they get older. As children's skills at organizing visual search improve they become more accurate at locating targets with conjunction of features amongst distractors, but not for targets with distinct features. Developmental limitations in children's abilities to organize their visual search of the environment are an important component of poor conjunction search in young children. In addition, our findings provide preliminary evidence that, like other visuospatial tasks, exposure to reading may influence children's spatial orientation to the visual environment when performing a visual search. PMID:23584560

Feature diagnosticity and task context shape activity in human scene-selective cortex.

PubMed

Lowe, Matthew X; Gallivan, Jason P; Ferber, Susanne; Cant, Jonathan S

2016-01-15

Scenes are constructed from multiple visual features, yet previous research investigating scene processing has often focused on the contributions of single features in isolation. In the real world, features rarely exist independently of one another and likely converge to inform scene identity in unique ways. Here, we utilize fMRI and pattern classification techniques to examine the interactions between task context (i.e., attend to diagnostic global scene features; texture or layout) and high-level scene attributes (content and spatial boundary) to test the novel hypothesis that scene-selective cortex represents multiple visual features, the importance of which varies according to their diagnostic relevance across scene categories and task demands. Our results show for the first time that scene representations are driven by interactions between multiple visual features and high-level scene attributes. Specifically, univariate analysis of scene-selective cortex revealed that task context and feature diagnosticity shape activity differentially across scene categories. Examination using multivariate decoding methods revealed results consistent with univariate findings, but also evidence for an interaction between high-level scene attributes and diagnostic visual features within scene categories. Critically, these findings suggest visual feature representations are not distributed uniformly across scene categories but are shaped by task context and feature diagnosticity. Thus, we propose that scene-selective cortex constructs a flexible representation of the environment by integrating multiple diagnostically relevant visual features, the nature of which varies according to the particular scene being perceived and the goals of the observer. Copyright © 2015 Elsevier Inc. All rights reserved.

The atmosphere as particle detector

NASA Technical Reports Server (NTRS)

Stanev, Todor

1990-01-01

The possibility of using an inflatable, gas-filled balloon as a TeV gamma-ray detector on the moon is considered. By taking an atmosphere of Xenon gas there, or by extracting it on the moon, a layman's detector design is presented. In spite of its shortcomings, the exercise illustrates several of the novel features offered by particle physics on the moon.

The atmosphere as particle detector

NASA Astrophysics Data System (ADS)

Stanev, T.

1990-03-01

The possibility of using an inflatable, gas-filled balloon as a TeV gamma-ray detector on the moon is considered. By taking an atmosphere of Xenon gas there, or by extracting it on the moon, a layman's detector design is presented. In spite of its shortcomings, the exercise illustrates several of the novel features offered by particle physics on the moon.

Visual short-term memory always requires general attention.

PubMed

Morey, Candice C; Bieler, Malte

2013-02-01

The role of attention in visual memory remains controversial; while some evidence has suggested that memory for binding between features demands no more attention than does memory for the same features, other evidence has indicated cognitive costs or mnemonic benefits for explicitly attending to bindings. We attempted to reconcile these findings by examining how memory for binding, for features, and for features during binding is affected by a concurrent attention-demanding task. We demonstrated that performing a concurrent task impairs memory for as few as two visual objects, regardless of whether each object includes one or more features. We argue that this pattern of results reflects an essential role for domain-general attention in visual memory, regardless of the simplicity of the to-be-remembered stimuli. We then discuss the implications of these findings for theories of visual working memory.

Effect of Intense Optical Excitation on Internal Electric Field Evolution in CdTe Gamma-Ray Detectors

NASA Astrophysics Data System (ADS)

Suzuki, K.; Ichinohe, Y.; Seto, S.

2018-03-01

The time-of-flight (TOF) transient currents in radiation detectors made of CdTe and Cd0.9Zn0.1Te (CZT) have been measured at several optical excitation intensities to investigate the effect of drifting carriers on the internal field. Both detectors show so-called space-charge-perturbed (SCP) current under intense optical excitation. A Monte Carlo (MC) simulation combined with an iterative solution of Poisson's equation is used to reproduce the observed currents under several bias voltages and excitation intensities. The SCP theory describes well the transient current in the CZT detector, whereas injection of holes from the anode and a corresponding reduction of the electron lifetime are further required to describe that in the CdTe detector. We visualize the temporal changes in the charge distribution and internal electric field profiles of both detectors.

Radiography by selective detection of scatter field velocity components

NASA Technical Reports Server (NTRS)

Dugan, Edward T. (Inventor); Jacobs, Alan M. (Inventor); Shedlock, Daniel (Inventor)

2007-01-01

A reconfigurable collimated radiation detector, system and related method includes at least one collimated radiation detector. The detector has an adjustable collimator assembly including at least one feature, such as a fin, optically coupled thereto. Adjustments to the adjustable collimator selects particular directions of travel of scattered radiation emitted from an irradiated object which reach the detector. The collimated detector is preferably a collimated detector array, where the collimators are independently adjustable. The independent motion capability provides the capability to focus the image by selection of the desired scatter field components. When an array of reconfigurable collimated detectors is provided, separate image data can be obtained from each of the detectors and the respective images cross-correlated and combined to form an enhanced image.

Three-dimensional optoacoustic mesoscopy of the tumor heterogeneity in vivo using high depth-to-resolution multispectral optoacoustic tomography

NASA Astrophysics Data System (ADS)

Li, Jiao; Zhang, Songhe; Chekkoury, Andrei; Glasl, Sarah; Vetschera, Paul; Koberstein-Schwarz, Benno; Omar, Murad; Ntziachristos, Vasilis

2017-03-01

Multispectral optoacoustic mesoscopy (MSOM) has been recently introduced for cancer imaging, it has the potential for high resolution imaging of cancer development in vivo, at depths beyond the diffusion limit. Based on spectral features, optoacoustic imaging is capable of visualizing angiogenesis and imaging cancer heterogeneity of malignant tumors through endogenous hemoglobin. However, high-resolution structural and functional imaging of whole tumor mass is limited by modest penetration and image quality, due to the insufficient capability of ultrasound detectors and the twodimensional scan geometry. In this study, we introduce a novel multi-spectral optoacoustic mesoscopy (MSOM) for imaging subcutaneous or orthotopic tumors implanted in lab mice, with the high-frequency ultrasound linear array and a conical scanning geometry. Detailed volumetric images of vasculature and oxygen saturation of tissue in the entire tumors are obtained in vivo, at depths up to 10 mm with the desirable spatial resolutions approaching 70μm. This unprecedented performance enables the visualization of vasculature morphology and hypoxia conditions has been verified with ex vivo studies. These findings demonstrate the potential of MSOM for preclinical oncological studies in deep solid tumors to facilitate the characterization of tumor's angiogenesis and the evaluation of treatment strategies.

Fusion of infrared and visible images based on saliency scale-space in frequency domain

NASA Astrophysics Data System (ADS)

Chen, Yanfei; Sang, Nong; Dan, Zhiping

2015-12-01

A fusion algorithm of infrared and visible images based on saliency scale-space in the frequency domain was proposed. Focus of human attention is directed towards the salient targets which interpret the most important information in the image. For the given registered infrared and visible images, firstly, visual features are extracted to obtain the input hypercomplex matrix. Secondly, the Hypercomplex Fourier Transform (HFT) is used to obtain the salient regions of the infrared and visible images respectively, the convolution of the input hypercomplex matrix amplitude spectrum with a low-pass Gaussian kernel of an appropriate scale which is equivalent to an image saliency detector are done. The saliency maps are obtained by reconstructing the 2D signal using the original phase and the amplitude spectrum, filtered at a scale selected by minimizing saliency map entropy. Thirdly, the salient regions are fused with the adoptive weighting fusion rules, and the nonsalient regions are fused with the rule based on region energy (RE) and region sharpness (RS), then the fused image is obtained. Experimental results show that the presented algorithm can hold high spectrum information of the visual image, and effectively get the thermal targets information at different scales of the infrared image.

Visual feature extraction and establishment of visual tags in the intelligent visual internet of things

NASA Astrophysics Data System (ADS)

Zhao, Yiqun; Wang, Zhihui

2015-12-01

The Internet of things (IOT) is a kind of intelligent networks which can be used to locate, track, identify and supervise people and objects. One of important core technologies of intelligent visual internet of things ( IVIOT) is the intelligent visual tag system. In this paper, a research is done into visual feature extraction and establishment of visual tags of the human face based on ORL face database. Firstly, we use the principal component analysis (PCA) algorithm for face feature extraction, then adopt the support vector machine (SVM) for classifying and face recognition, finally establish a visual tag for face which is already classified. We conducted a experiment focused on a group of people face images, the result show that the proposed algorithm have good performance, and can show the visual tag of objects conveniently.

Miniature triaxial metastable ionization detector for gas chromatographic trace analysis of extraterrestrial volatiles

NASA Technical Reports Server (NTRS)

Woeller, F. H.; Kojiro, D. R.; Carle, G. C.

1984-01-01

The present investigation is concerned with a miniature metastable ionization detector featuring an unconventional electrode configuration, whose performance characteristics parallel those of traditional design. The ionization detector is to be incorporated in a flight gas chromatograph (GC) for use in the Space Shuttle. The design of the detector is discussed, taking into account studies which verified the sensitivity of the detector. The triaxial design of the detector is compared with a flat-plate style. The obtained results show that the principal goal of developing a miniature, highly sensitive ionization detector for flight applications was achieved. Improved fabrication techniques will utilize glass-to-metal seals and brazing procedures.

Feature confirmation in object perception: Feature integration theory 26 years on from the Treisman Bartlett lecture.

PubMed

Humphreys, Glyn W

2016-10-01

The Treisman Bartlett lecture, reported in the Quarterly Journal of Experimental Psychology in 1988, provided a major overview of the feature integration theory of attention. This has continued to be a dominant account of human visual attention to this day. The current paper provides a summary of the work reported in the lecture and an update on critical aspects of the theory as applied to visual object perception. The paper highlights the emergence of findings that pose significant challenges to the theory and which suggest that revisions are required that allow for (a) several rather than a single form of feature integration, (b) some forms of feature integration to operate preattentively, (c) stored knowledge about single objects and interactions between objects to modulate perceptual integration, (d) the application of feature-based inhibition to object files where visual features are specified, which generates feature-based spreading suppression and scene segmentation, and (e) a role for attention in feature confirmation rather than feature integration in visual selection. A feature confirmation account of attention in object perception is outlined.

Readout and DAQ for Pixel Detectors

NASA Astrophysics Data System (ADS)

Platkevic, Michal

2010-01-01

Data readout and acquisition control of pixel detectors demand the transfer of significantly a large amounts of bits between the detector and the computer. For this purpose dedicated interfaces are used which are designed with focus on features like speed, small dimensions or flexibility of use such as digital signal processors, field-programmable gate arrays (FPGA) and USB communication ports. This work summarizes the readout and DAQ system built for state-of-the-art pixel detectors of the Medipix family.

Separate Capacities for Storing Different Features in Visual Working Memory

ERIC Educational Resources Information Center

Wang, Benchi; Cao, Xiaohua; Theeuwes, Jan; Olivers, Christian N. L.; Wang, Zhiguo

2017-01-01

Recent empirical and theoretical work suggests that visual features such as color and orientation can be stored or retrieved independently in visual working memory (VWM), even in cases when they belong to the same object. Yet it remains unclear whether different feature dimensions have their own capacity limits, or whether they compete for shared…

Comparison of two portable solid state detectors with an improved collimation and alignment device for mammographic x-ray spectroscopy.

PubMed

Bottigli, U; Golosio, B; Masala, G L; Oliva, P; Stumbo, S; Delogu, P; Fantacci, M E; Abbene, L; Fauci, F; Raso, G

2006-09-01

We describe a portable system for mammographic x-ray spectroscopy, based on a 2 X 2 X 1 mm3 cadmium telluride (CdTe) solid state detector, that is greatly improved over a similar system based on a 3 X 3 X 2 mm3 cadmium zinc telluride (CZT) solid state detector evaluated in an earlier work. The CdTe system utilized new pinhole collimators and an alignment device that facilitated measurement of mammographic x-ray spectra. Mammographic x-ray spectra acquired by each system were comparable. Half value layer measurements obtained using an ion chamber agreed closely with those derived from the x-ray spectra measured by either detector. The faster electronics and other features of the CdTe detector allowed its use with a larger pinhole collimator than could be used with the CZT detector. Additionally, the improved pinhole collimator and alignment features of the apparatus permitted much more rapid setup for acquisition of x-ray spectra than was possible on the system described in the earlier work. These improvements in detector technology, collimation and ease of alignment, as well as low cost, make this apparatus attractive as a tool for both laboratory research and advanced mammography quality control.

High-resolution brain SPECT imaging by combination of parallel and tilted detector heads.

PubMed

Suzuki, Atsuro; Takeuchi, Wataru; Ishitsu, Takafumi; Morimoto, Yuichi; Kobashi, Keiji; Ueno, Yuichiro

2015-10-01

To improve the spatial resolution of brain single-photon emission computed tomography (SPECT), we propose a new brain SPECT system in which the detector heads are tilted towards the rotation axis so that they are closer to the brain. In addition, parallel detector heads are used to obtain the complete projection data set. We evaluated this parallel and tilted detector head system (PT-SPECT) in simulations. In the simulation study, the tilt angle of the detector heads relative to the axis was 45°. The distance from the collimator surface of the parallel detector heads to the axis was 130 mm. The distance from the collimator surface of the tilted detector heads to the origin on the axis was 110 mm. A CdTe semiconductor panel with a 1.4 mm detector pitch and a parallel-hole collimator were employed in both types of detector head. A line source phantom, cold-rod brain-shaped phantom, and cerebral blood flow phantom were evaluated. The projection data were generated by forward-projection of the phantom images using physics models, and Poisson noise at clinical levels was applied to the projection data. The ordered-subsets expectation maximization algorithm with physics models was used. We also evaluated conventional SPECT using four parallel detector heads for the sake of comparison. The evaluation of the line source phantom showed that the transaxial FWHM in the central slice for conventional SPECT ranged from 6.1 to 8.5 mm, while that for PT-SPECT ranged from 5.3 to 6.9 mm. The cold-rod brain-shaped phantom image showed that conventional SPECT could visualize up to 8-mm-diameter rods. By contrast, PT-SPECT could visualize up to 6-mm-diameter rods in upper slices of a cerebrum. The cerebral blood flow phantom image showed that the PT-SPECT system provided higher resolution at the thalamus and caudate nucleus as well as at the longitudinal fissure of the cerebrum compared with conventional SPECT. PT-SPECT provides improved image resolution at not only upper but also at central slices of the cerebrum.

SU-D-204-05: Quantitative Comparison of a High Resolution Micro-Angiographic Fluoroscopic (MAF) Detector with a Standard Flat Panel Detector (FPD) Using the New Metric of Generalized Measured Relative Object Detectability (GM-ROD)

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

Russ, M; Ionita, C; Bednarek, D

Purpose: In endovascular image-guided neuro-interventions, visualization of fine detail is paramount. For example, the ability of the interventionist to visualize the stent struts depends heavily on the x-ray imaging detector performance. Methods: A study to examine the relative performance of the high resolution MAF-CMOS (pixel size 75µm, Nyquist frequency 6.6 cycles/mm) and a standard Flat Panel Detector (pixel size 194µm, Nyquist frequency 2.5 cycles/mm) detectors in imaging a neuro stent was done using the Generalized Measured Relative Object Detectability (GM-ROD) metric. Low quantum noise images of a deployed stent were obtained by averaging 95 frames obtained by both detectors withoutmore » changing other exposure or geometric parameters. The square of the Fourier transform of each image is taken and divided by the generalized normalized noise power spectrum to give an effective measured task-specific signal-to-noise ratio. This expression is then integrated from 0 to each of the detector’s Nyquist frequencies, and the GM-ROD value is determined by taking a ratio of the integrals for the MAF-CMOS to that of the FPD. The lower bound of integration can be varied to emphasize high frequencies in the detector comparisons. Results: The MAF-CMOS detector exhibits vastly superior performance over the FPD when integrating over all frequencies, yielding a GM-ROD value of 63.1. The lower bound of integration was stepped up in increments of 0.5 cycles/mm for higher frequency comparisons. As the lower bound increased, the GM-ROD value was augmented, reflecting the superior performance of the MAF-CMOS in the high frequency regime. Conclusion: GM-ROD is a versatile metric that can provide quantitative detector and task dependent comparisons that can be used as a basis for detector selection. Supported by NIH Grant: 2R01EB002873 and an equipment grant from Toshiba Medical Systems Corporation.« less

Remembering Complex Objects in Visual Working Memory: Do Capacity Limits Restrict Objects or Features?

PubMed Central

Hardman, Kyle; Cowan, Nelson

2014-01-01

Visual working memory stores stimuli from our environment as representations that can be accessed by high-level control processes. This study addresses a longstanding debate in the literature about whether storage limits in visual working memory include a limit to the complexity of discrete items. We examined the issue with a number of change-detection experiments that used complex stimuli which possessed multiple features per stimulus item. We manipulated the number of relevant features of the stimulus objects in order to vary feature load. In all of our experiments, we found that increased feature load led to a reduction in change-detection accuracy. However, we found that feature load alone could not account for the results, but that a consideration of the number of relevant objects was also required. This study supports capacity limits for both feature and object storage in visual working memory. PMID:25089739

Plastic scintillator detector for pulsed flux measurements

NASA Astrophysics Data System (ADS)

Kadilin, V. V.; Kaplun, A. A.; Taraskin, A. A.

2017-01-01

A neutron detector, providing charged particle detection capability, has been designed. The main purpose of the detector is to measure pulsed fluxes of both charged particles and neutrons during scientific experiments. The detector consists of commonly used neutron-sensitive ZnS(Ag) / 6LiF scintillator screens wrapping a layer of polystyrene based scintillator (BC-454, EJ-254 or equivalent boron loaded plastic). This type of detector design is able to log a spatial distribution of events and may be scaled to any size. Different variations of the design were considered and modelled in specialized toolkits. The article presents a review of the detector design features as well as simulation results.

Coding Local and Global Binary Visual Features Extracted From Video Sequences.

PubMed

Baroffio, Luca; Canclini, Antonio; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano

2015-11-01

Binary local features represent an effective alternative to real-valued descriptors, leading to comparable results for many visual analysis tasks while being characterized by significantly lower computational complexity and memory requirements. When dealing with large collections, a more compact representation based on global features is often preferred, which can be obtained from local features by means of, e.g., the bag-of-visual word model. Several applications, including, for example, visual sensor networks and mobile augmented reality, require visual features to be transmitted over a bandwidth-limited network, thus calling for coding techniques that aim at reducing the required bit budget while attaining a target level of efficiency. In this paper, we investigate a coding scheme tailored to both local and global binary features, which aims at exploiting both spatial and temporal redundancy by means of intra- and inter-frame coding. In this respect, the proposed coding scheme can conveniently be adopted to support the analyze-then-compress (ATC) paradigm. That is, visual features are extracted from the acquired content, encoded at remote nodes, and finally transmitted to a central controller that performs the visual analysis. This is in contrast with the traditional approach, in which visual content is acquired at a node, compressed and then sent to a central unit for further processing, according to the compress-then-analyze (CTA) paradigm. In this paper, we experimentally compare the ATC and the CTA by means of rate-efficiency curves in the context of two different visual analysis tasks: 1) homography estimation and 2) content-based retrieval. Our results show that the novel ATC paradigm based on the proposed coding primitives can be competitive with the CTA, especially in bandwidth limited scenarios.

Coding Local and Global Binary Visual Features Extracted From Video Sequences

NASA Astrophysics Data System (ADS)

Baroffio, Luca; Canclini, Antonio; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano

2015-11-01

Binary local features represent an effective alternative to real-valued descriptors, leading to comparable results for many visual analysis tasks, while being characterized by significantly lower computational complexity and memory requirements. When dealing with large collections, a more compact representation based on global features is often preferred, which can be obtained from local features by means of, e.g., the Bag-of-Visual-Word (BoVW) model. Several applications, including for example visual sensor networks and mobile augmented reality, require visual features to be transmitted over a bandwidth-limited network, thus calling for coding techniques that aim at reducing the required bit budget, while attaining a target level of efficiency. In this paper we investigate a coding scheme tailored to both local and global binary features, which aims at exploiting both spatial and temporal redundancy by means of intra- and inter-frame coding. In this respect, the proposed coding scheme can be conveniently adopted to support the Analyze-Then-Compress (ATC) paradigm. That is, visual features are extracted from the acquired content, encoded at remote nodes, and finally transmitted to a central controller that performs visual analysis. This is in contrast with the traditional approach, in which visual content is acquired at a node, compressed and then sent to a central unit for further processing, according to the Compress-Then-Analyze (CTA) paradigm. In this paper we experimentally compare ATC and CTA by means of rate-efficiency curves in the context of two different visual analysis tasks: homography estimation and content-based retrieval. Our results show that the novel ATC paradigm based on the proposed coding primitives can be competitive with CTA, especially in bandwidth limited scenarios.

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.

Framework for Evaluating Loop Invariant Detection Games in Relation to Automated Dynamic Invariant Detectors

DTIC Science & Technology

2015-09-01

Detectability ...............................................................................................37 Figure 20. Excel VBA Codes for Checker...National Vulnerability Database OS Operating System SQL Structured Query Language VC Verification Condition VBA Visual Basic for Applications...checks each of these assertions for detectability by Daikon. The checker is an Excel Visual Basic for Applications ( VBA ) script that checks the

Contrast Sensitivity for Motion Detection and Direction Discrimination in Adolescents with Autism Spectrum Disorders and Their Siblings

ERIC Educational Resources Information Center

Koh, Hwan Cui; Milne, Elizabeth; Dobkins, Karen

2010-01-01

The magnocellular (M) pathway hypothesis proposes that impaired visual motion perception observed in individuals with Autism Spectrum Disorders (ASD) might be mediated by atypical functioning of the subcortical M pathway, as this pathway provides the bulk of visual input to cortical motion detectors. To test this hypothesis, we measured luminance…

Combining local and global limitations of visual search.

PubMed

Põder, Endel

2017-04-01

There are different opinions about the roles of local interactions and central processing capacity in visual search. This study attempts to clarify the problem using a new version of relevant set cueing. A central precue indicates two symmetrical segments (that may contain a target object) within a circular array of objects presented briefly around the fixation point. The number of objects in the relevant segments, and density of objects in the array were varied independently. Three types of search experiments were run: (a) search for a simple visual feature (color, size, and orientation); (b) conjunctions of simple features; and (c) spatial configuration of simple features (rotated Ts). For spatial configuration stimuli, the results were consistent with a fixed global processing capacity and standard crowding zones. For simple features and their conjunctions, the results were different, dependent on the features involved. While color search exhibits virtually no capacity limits or crowding, search for an orientation target was limited by both. Results for conjunctions of features can be partly explained by the results from the respective features. This study shows that visual search is limited by both local interference and global capacity, and the limitations are different for different visual features.

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/.

MSM optical detector on the basis of II-type ZnSe/ZnTe superlattice

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

Kuznetzov, P. I., E-mail: pik218@ire216.msk.su; Averin, S. V., E-mail: sva278@ire216.msk.su; Zhitov, V. A.

2017-02-15

On the basis of a type-II ZnSe/ZnTe superlattice, a MSM (metal—semiconductor–metal) photodetector is fabricated and investigated. The detector features low dark currents and a high sensitivity. The spectral characteristic of the detector provides the possibility of the selective detection of three separate spectral portions of visible and near-infrared radiation.

Real-time self-networking radiation detector apparatus

DOEpatents

Kaplan, Edward [Stony Brook, NY; Lemley, James [Miller Place, NY; Tsang, Thomas Y [Holbrook, NY; Milian, Laurence W [East Patchogue, NY

2007-06-12

The present invention is for a radiation detector apparatus for detecting radiation sources present in cargo shipments. The invention includes the features of integrating a bubble detector sensitive to neutrons and a GPS system into a miniaturized package that can wirelessly signal the presence of radioactive material in shipping containers. The bubble density would be read out if such indicated a harmful source.

Deep Multimodal Distance Metric Learning Using Click Constraints for Image Ranking.

PubMed

Yu, Jun; Yang, Xiaokang; Gao, Fei; Tao, Dacheng

2017-12-01

How do we retrieve images accurately? Also, how do we rank a group of images precisely and efficiently for specific queries? These problems are critical for researchers and engineers to generate a novel image searching engine. First, it is important to obtain an appropriate description that effectively represent the images. In this paper, multimodal features are considered for describing images. The images unique properties are reflected by visual features, which are correlated to each other. However, semantic gaps always exist between images visual features and semantics. Therefore, we utilize click feature to reduce the semantic gap. The second key issue is learning an appropriate distance metric to combine these multimodal features. This paper develops a novel deep multimodal distance metric learning (Deep-MDML) method. A structured ranking model is adopted to utilize both visual and click features in distance metric learning (DML). Specifically, images and their related ranking results are first collected to form the training set. Multimodal features, including click and visual features, are collected with these images. Next, a group of autoencoders is applied to obtain initially a distance metric in different visual spaces, and an MDML method is used to assign optimal weights for different modalities. Next, we conduct alternating optimization to train the ranking model, which is used for the ranking of new queries with click features. Compared with existing image ranking methods, the proposed method adopts a new ranking model to use multimodal features, including click features and visual features in DML. We operated experiments to analyze the proposed Deep-MDML in two benchmark data sets, and the results validate the effects of the method.

Rapid Processing of a Global Feature in the ON Visual Pathways of Behaving Monkeys.

PubMed

Huang, Jun; Yang, Yan; Zhou, Ke; Zhao, Xudong; Zhou, Quan; Zhu, Hong; Yang, Yingshan; Zhang, Chunming; Zhou, Yifeng; Zhou, Wu

2017-01-01

Visual objects are recognized by their features. Whereas, some features are based on simple components (i.e., local features, such as orientation of line segments), some features are based on the whole object (i.e., global features, such as an object having a hole in it). Over the past five decades, behavioral, physiological, anatomical, and computational studies have established a general model of vision, which starts from extracting local features in the lower visual pathways followed by a feature integration process that extracts global features in the higher visual pathways. This local-to-global model is successful in providing a unified account for a vast sets of perception experiments, but it fails to account for a set of experiments showing human visual systems' superior sensitivity to global features. Understanding the neural mechanisms underlying the "global-first" process will offer critical insights into new models of vision. The goal of the present study was to establish a non-human primate model of rapid processing of global features for elucidating the neural mechanisms underlying differential processing of global and local features. Monkeys were trained to make a saccade to a target in the black background, which was different from the distractors (white circle) in color (e.g., red circle target), local features (e.g., white square target), a global feature (e.g., white ring with a hole target) or their combinations (e.g., red square target). Contrary to the predictions of the prevailing local-to-global model, we found that (1) detecting a distinction or a change in the global feature was faster than detecting a distinction or a change in color or local features; (2) detecting a distinction in color was facilitated by a distinction in the global feature, but not in the local features; and (3) detecting the hole was interfered by the local features of the hole (e.g., white ring with a squared hole). These results suggest that monkey ON visual systems have a subsystem that is more sensitive to distinctions in the global feature than local features. They also provide the behavioral constraints for identifying the underlying neural substrates.

Visual words for lip-reading

NASA Astrophysics Data System (ADS)

Hassanat, Ahmad B. A.; Jassim, Sabah

2010-04-01

In this paper, the automatic lip reading problem is investigated, and an innovative approach to providing solutions to this problem has been proposed. This new VSR approach is dependent on the signature of the word itself, which is obtained from a hybrid feature extraction method dependent on geometric, appearance, and image transform features. The proposed VSR approach is termed "visual words". The visual words approach consists of two main parts, 1) Feature extraction/selection, and 2) Visual speech feature recognition. After localizing face and lips, several visual features for the lips where extracted. Such as the height and width of the mouth, mutual information and the quality measurement between the DWT of the current ROI and the DWT of the previous ROI, the ratio of vertical to horizontal features taken from DWT of ROI, The ratio of vertical edges to horizontal edges of ROI, the appearance of the tongue and the appearance of teeth. Each spoken word is represented by 8 signals, one of each feature. Those signals maintain the dynamic of the spoken word, which contains a good portion of information. The system is then trained on these features using the KNN and DTW. This approach has been evaluated using a large database for different people, and large experiment sets. The evaluation has proved the visual words efficiency, and shown that the VSR is a speaker dependent problem.

Enhanced Imaging of Corrosion in Aircraft Structures with Reverse Geometry X-ray(registered tm)

NASA Technical Reports Server (NTRS)

Winfree, William P.; Cmar-Mascis, Noreen A.; Parker, F. Raymond

2000-01-01

The application of Reverse Geometry X-ray to the detection and characterization of corrosion in aircraft structures is presented. Reverse Geometry X-ray is a unique system that utilizes an electronically scanned x-ray source and a discrete detector for real time radiographic imaging of a structure. The scanned source system has several advantages when compared to conventional radiography. First, the discrete x-ray detector can be miniaturized and easily positioned inside a complex structure (such as an aircraft wing) enabling images of each surface of the structure to be obtained separately. Second, using a measurement configuration with multiple detectors enables the simultaneous acquisition of data from several different perspectives without moving the structure or the measurement system. This provides a means for locating the position of flaws and enhances separation of features at the surface from features inside the structure. Data is presented on aircraft specimens with corrosion in the lap joint. Advanced laminographic imaging techniques utilizing data from multiple detectors are demonstrated to be capable of separating surface features from corrosion in the lap joint and locating the corrosion in multilayer structures. Results of this technique are compared to computed tomography cross sections obtained from a microfocus x-ray tomography system. A method is presented for calibration of the detectors of the Reverse Geometry X-ray system to enable quantification of the corrosion to within 2%.

Design and performance of optimal detectors for guided wave structural health monitoring

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

Dib, G.; Udpa, L.

2016-01-01

Ultrasonic guided wave measurements in a long term structural health monitoring system are affected by measurement noise, environmental conditions, transducer aging and malfunction. This results in measurement variability which affects detection performance, especially in complex structures where baseline data comparison is required. This paper derives the optimal detector structure, within the framework of detection theory, where a guided wave signal at the sensor is represented by a single feature value that can be used for comparison with a threshold. Three different types of detectors are derived depending on the underlying structure’s complexity: (i) Simple structures where defect reflections can bemore » identified without the need for baseline data; (ii) Simple structures that require baseline data due to overlap of defect scatter with scatter from structural features; (iii) Complex structure with dense structural features that require baseline data. The detectors are derived by modeling the effects of variabilities and uncertainties as random processes. Analytical solutions for the performance of detectors in terms of the probability of detection and false alarm are derived. A finite element model is used to generate guided wave signals and the performance results of a Monte-Carlo simulation are compared with the theoretical performance. initial results demonstrate that the problems of signal complexity and environmental variability can in fact be exploited to improve detection performance.« less

Real-time pose invariant logo and pattern detection

NASA Astrophysics Data System (ADS)

Sidla, Oliver; Kottmann, Michal; Benesova, Wanda

2011-01-01

The detection of pose invariant planar patterns has many practical applications in computer vision and surveillance systems. The recognition of company logos is used in market studies to examine the visibility and frequency of logos in advertisement. Danger signs on vehicles could be detected to trigger warning systems in tunnels, or brand detection on transport vehicles can be used to count company-specific traffic. We present the results of a study on planar pattern detection which is based on keypoint detection and matching of distortion invariant 2d feature descriptors. Specifically we look at the keypoint detectors of type: i) Lowe's DoG approximation from the SURF algorithm, ii) the Harris Corner Detector, iii) the FAST Corner Detector and iv) Lepetit's keypoint detector. Our study then compares the feature descriptors SURF and compact signatures based on Random Ferns: we use 3 sets of sample images to detect and match 3 logos of different structure to find out which combinations of keypoint detector/feature descriptors work well. A real-world test tries to detect vehicles with a distinctive logo in an outdoor environment under realistic lighting and weather conditions: a camera was mounted on a suitable location for observing the entrance to a parking area so that incoming vehicles could be monitored. In this 2 hour long recording we can successfully detect a specific company logo without false positives.

Uncooled detectors optimized for unattended applications

NASA Astrophysics Data System (ADS)

Malkinson, E.; Fraenkel, A.; Mizrahi, U.; Ben-Ezra, M.; Bikov, L.; Adin, A.; Zabar, Y.; Seter, D.; Kopolovich, Z.

2005-10-01

SCD has recently presented an uncooled detector product line based on the high-end VOx bolometer technology. The first FPA launched, named BIRD - short for Bolometer Infra Red Detector, is a 384x288 (or 320x240) configurable format with 25μm pitch. Typical NETD values for these FPAs range at 50mK with an F/1 aperture and 60 Hz frame rate. These detectors also exhibit a relatively fast thermal time constant of approximately 10 msec, as reported previously. In this paper, the special features of BIRD optimized for unattended sensor applications are presented and discussed. Unattended surveillance using sensors on unattended aerial vehicles (UAV's) or micro air vehicles (MAV's) , unattended ground vehicles (UGV's) or unattended ground sensor (UGS) are growing applications for uncooled detectors. This is due to their low power consumption, low weight, negligible acoustic noise and reduced price. On the other hand, uncooled detectors are vulnerable to ambient drift. Even minor temperature fluctuations are manifested as fixed pattern noise (FPN). As a result, frequent, shutter operation must be applied, with the risk of blocking the scenery in critical time frames and loosing information for various scenarios. In order to increase the time span between shutter operations, SCD has incorporated various features within the FPA and supporting algorithms. This paper will discuss these features and present some illustrative examples. Minimum power consumption is another critical issue for unattended applications. SCD has addressed this topic by introducing the "Power Save" concept. For very low power applications or for TEC-less (Thermo-Electric-Cooler) applications, the flexible dilution architecture enables the system to operate the detector at a number of formats. This, together with a smooth frame rate and format transition capability turns SCD's uncooled detector to be well suited for unattended applications. These issues will be described in detail as well.

Weighted feature selection criteria for visual servoing of a telerobot

NASA Technical Reports Server (NTRS)

Feddema, John T.; Lee, C. S. G.; Mitchell, O. R.

1989-01-01

Because of the continually changing environment of a space station, visual feedback is a vital element of a telerobotic system. A real time visual servoing system would allow a telerobot to track and manipulate randomly moving objects. Methodologies for the automatic selection of image features to be used to visually control the relative position between an eye-in-hand telerobot and a known object are devised. A weighted criteria function with both image recognition and control components is used to select the combination of image features which provides the best control. Simulation and experimental results of a PUMA robot arm visually tracking a randomly moving carburetor gasket with a visual update time of 70 milliseconds are discussed.

Impact of feature saliency on visual category learning.

PubMed

Hammer, Rubi

2015-01-01

People have to sort numerous objects into a large number of meaningful categories while operating in varying contexts. This requires identifying the visual features that best predict the 'essence' of objects (e.g., edibility), rather than categorizing objects based on the most salient features in a given context. To gain this capacity, visual category learning (VCL) relies on multiple cognitive processes. These may include unsupervised statistical learning, that requires observing multiple objects for learning the statistics of their features. Other learning processes enable incorporating different sources of supervisory information, alongside the visual features of the categorized objects, from which the categorical relations between few objects can be deduced. These deductions enable inferring that objects from the same category may differ from one another in some high-saliency feature dimensions, whereas lower-saliency feature dimensions can best differentiate objects from distinct categories. Here I illustrate how feature saliency affects VCL, by also discussing kinds of supervisory information enabling reflective categorization. Arguably, principles debated here are often being ignored in categorization studies.

Impact of feature saliency on visual category learning

PubMed Central

Hammer, Rubi

2015-01-01

People have to sort numerous objects into a large number of meaningful categories while operating in varying contexts. This requires identifying the visual features that best predict the ‘essence’ of objects (e.g., edibility), rather than categorizing objects based on the most salient features in a given context. To gain this capacity, visual category learning (VCL) relies on multiple cognitive processes. These may include unsupervised statistical learning, that requires observing multiple objects for learning the statistics of their features. Other learning processes enable incorporating different sources of supervisory information, alongside the visual features of the categorized objects, from which the categorical relations between few objects can be deduced. These deductions enable inferring that objects from the same category may differ from one another in some high-saliency feature dimensions, whereas lower-saliency feature dimensions can best differentiate objects from distinct categories. Here I illustrate how feature saliency affects VCL, by also discussing kinds of supervisory information enabling reflective categorization. Arguably, principles debated here are often being ignored in categorization studies. PMID:25954220

Pulsed helium ionization detection system

DOEpatents

Ramsey, R.S.; Todd, R.A.

1985-04-09

A helium ionization detection system is provided which produces stable operation of a conventional helium ionization detector while providing improved sensitivity and linearity. Stability is improved by applying pulsed dc supply voltage across the ionization detector, thereby modifying the sampling of the detectors output current. A unique pulse generator is used to supply pulsed dc to the detector which has variable width and interval adjust features that allows up to 500 V to be applied in pulse widths ranging from about 150 nsec to about dc conditions.

Pulsed helium ionization detection system

DOEpatents

Ramsey, Roswitha S.; Todd, Richard A.

1987-01-01

A helium ionization detection system is provided which produces stable operation of a conventional helium ionization detector while providing improved sensitivity and linearity. Stability is improved by applying pulsed dc supply voltage across the ionization detector, thereby modifying the sampling of the detectors output current. A unique pulse generator is used to supply pulsed dc to the detector which has variable width and interval adjust features that allows up to 500 V to be applied in pulse widths ranging from about 150 nsec to about dc conditions.

Spatial and Feature-Based Attention in a Layered Cortical Microcircuit Model

PubMed Central

Wagatsuma, Nobuhiko; Potjans, Tobias C.; Diesmann, Markus; Sakai, Ko; Fukai, Tomoki

2013-01-01

Directing attention to the spatial location or the distinguishing feature of a visual object modulates neuronal responses in the visual cortex and the stimulus discriminability of subjects. However, the spatial and feature-based modes of attention differently influence visual processing by changing the tuning properties of neurons. Intriguingly, neurons' tuning curves are modulated similarly across different visual areas under both these modes of attention. Here, we explored the mechanism underlying the effects of these two modes of visual attention on the orientation selectivity of visual cortical neurons. To do this, we developed a layered microcircuit model. This model describes multiple orientation-specific microcircuits sharing their receptive fields and consisting of layers 2/3, 4, 5, and 6. These microcircuits represent a functional grouping of cortical neurons and mutually interact via lateral inhibition and excitatory connections between groups with similar selectivity. The individual microcircuits receive bottom-up visual stimuli and top-down attention in different layers. A crucial assumption of the model is that feature-based attention activates orientation-specific microcircuits for the relevant feature selectively, whereas spatial attention activates all microcircuits homogeneously, irrespective of their orientation selectivity. Consequently, our model simultaneously accounts for the multiplicative scaling of neuronal responses in spatial attention and the additive modulations of orientation tuning curves in feature-based attention, which have been observed widely in various visual cortical areas. Simulations of the model predict contrasting differences between excitatory and inhibitory neurons in the two modes of attentional modulations. Furthermore, the model replicates the modulation of the psychophysical discriminability of visual stimuli in the presence of external noise. Our layered model with a biologically suggested laminar structure describes the basic circuit mechanism underlying the attention-mode specific modulations of neuronal responses and visual perception. PMID:24324628

An enhanced data visualization method for diesel engine malfunction classification using multi-sensor signals.

PubMed

Li, Yiqing; Wang, Yu; Zi, Yanyang; Zhang, Mingquan

2015-10-21

The various multi-sensor signal features from a diesel engine constitute a complex high-dimensional dataset. The non-linear dimensionality reduction method, t-distributed stochastic neighbor embedding (t-SNE), provides an effective way to implement data visualization for complex high-dimensional data. However, irrelevant features can deteriorate the performance of data visualization, and thus, should be eliminated a priori. This paper proposes a feature subset score based t-SNE (FSS-t-SNE) data visualization method to deal with the high-dimensional data that are collected from multi-sensor signals. In this method, the optimal feature subset is constructed by a feature subset score criterion. Then the high-dimensional data are visualized in 2-dimension space. According to the UCI dataset test, FSS-t-SNE can effectively improve the classification accuracy. An experiment was performed with a large power marine diesel engine to validate the proposed method for diesel engine malfunction classification. Multi-sensor signals were collected by a cylinder vibration sensor and a cylinder pressure sensor. Compared with other conventional data visualization methods, the proposed method shows good visualization performance and high classification accuracy in multi-malfunction classification of a diesel engine.

An Enhanced Data Visualization Method for Diesel Engine Malfunction Classification Using Multi-Sensor Signals

PubMed Central

Li, Yiqing; Wang, Yu; Zi, Yanyang; Zhang, Mingquan

2015-01-01

The various multi-sensor signal features from a diesel engine constitute a complex high-dimensional dataset. The non-linear dimensionality reduction method, t-distributed stochastic neighbor embedding (t-SNE), provides an effective way to implement data visualization for complex high-dimensional data. However, irrelevant features can deteriorate the performance of data visualization, and thus, should be eliminated a priori. This paper proposes a feature subset score based t-SNE (FSS-t-SNE) data visualization method to deal with the high-dimensional data that are collected from multi-sensor signals. In this method, the optimal feature subset is constructed by a feature subset score criterion. Then the high-dimensional data are visualized in 2-dimension space. According to the UCI dataset test, FSS-t-SNE can effectively improve the classification accuracy. An experiment was performed with a large power marine diesel engine to validate the proposed method for diesel engine malfunction classification. Multi-sensor signals were collected by a cylinder vibration sensor and a cylinder pressure sensor. Compared with other conventional data visualization methods, the proposed method shows good visualization performance and high classification accuracy in multi-malfunction classification of a diesel engine. PMID:26506347

Visual feature integration with an attention deficit.

PubMed

Arguin, M; Cavanagh, P; Joanette, Y

1994-01-01

Treisman's feature integration theory proposes that the perception of illusory conjunctions of correctly encoded visual features is due to the failure of an attentional process. This hypothesis was examined by studying brain-damaged subjects who had previously been shown to have difficulty in attending to contralesional stimulation. These subjects exhibited a massive feature integration deficit for contralesional stimulation relative to ipsilesional displays. In contrast, both normal age-matched controls and brain-damaged subjects who did not exhibit any evidence of an attention deficit showed comparable feature integration performance with left- and right-hemifield stimulation. These observations indicate the crucial function of attention for visual feature integration in normal perception.

Features in visual search combine linearly

PubMed Central

Pramod, R. T.; Arun, S. P.

2014-01-01

Single features such as line orientation and length are known to guide visual search, but relatively little is known about how multiple features combine in search. To address this question, we investigated how search for targets differing in multiple features (intensity, length, orientation) from the distracters is related to searches for targets differing in each of the individual features. We tested race models (based on reaction times) and co-activation models (based on reciprocal of reaction times) for their ability to predict multiple feature searches. Multiple feature searches were best accounted for by a co-activation model in which feature information combined linearly (r = 0.95). This result agrees with the classic finding that these features are separable i.e., subjective dissimilarity ratings sum linearly. We then replicated the classical finding that the length and width of a rectangle are integral features—in other words, they combine nonlinearly in visual search. However, to our surprise, upon including aspect ratio as an additional feature, length and width combined linearly and this model outperformed all other models. Thus, length and width of a rectangle became separable when considered together with aspect ratio. This finding predicts that searches involving shapes with identical aspect ratio should be more difficult than searches where shapes differ in aspect ratio. We confirmed this prediction on a variety of shapes. We conclude that features in visual search co-activate linearly and demonstrate for the first time that aspect ratio is a novel feature that guides visual search. PMID:24715328

The feature-weighted receptive field: an interpretable encoding model for complex feature spaces.

PubMed

St-Yves, Ghislain; Naselaris, Thomas

2017-06-20

We introduce the feature-weighted receptive field (fwRF), an encoding model designed to balance expressiveness, interpretability and scalability. The fwRF is organized around the notion of a feature map-a transformation of visual stimuli into visual features that preserves the topology of visual space (but not necessarily the native resolution of the stimulus). The key assumption of the fwRF model is that activity in each voxel encodes variation in a spatially localized region across multiple feature maps. This region is fixed for all feature maps; however, the contribution of each feature map to voxel activity is weighted. Thus, the model has two separable sets of parameters: "where" parameters that characterize the location and extent of pooling over visual features, and "what" parameters that characterize tuning to visual features. The "where" parameters are analogous to classical receptive fields, while "what" parameters are analogous to classical tuning functions. By treating these as separable parameters, the fwRF model complexity is independent of the resolution of the underlying feature maps. This makes it possible to estimate models with thousands of high-resolution feature maps from relatively small amounts of data. Once a fwRF model has been estimated from data, spatial pooling and feature tuning can be read-off directly with no (or very little) additional post-processing or in-silico experimentation. We describe an optimization algorithm for estimating fwRF models from data acquired during standard visual neuroimaging experiments. We then demonstrate the model's application to two distinct sets of features: Gabor wavelets and features supplied by a deep convolutional neural network. We show that when Gabor feature maps are used, the fwRF model recovers receptive fields and spatial frequency tuning functions consistent with known organizational principles of the visual cortex. We also show that a fwRF model can be used to regress entire deep convolutional networks against brain activity. The ability to use whole networks in a single encoding model yields state-of-the-art prediction accuracy. Our results suggest a wide variety of uses for the feature-weighted receptive field model, from retinotopic mapping with natural scenes, to regressing the activities of whole deep neural networks onto measured brain activity. Copyright © 2017. Published by Elsevier Inc.

The Top...is it There? A Survey of the CDF and D0 Experiments

DOE R&D Accomplishments Database

Tollestrup, A. V.

1994-12-01

This paper describes: (1) features that the top quark must have if it exists, and how those features are inferred from various experiments; (2) how top quarks may be produced; (3) what must be accomplished to directly establish that the top quark has been produced in an experiment. Relevant features of the CDF and D0 detectors are described, as are methods useful in a top-quark search for identifying and detecting various kinds of particles. The author reviews data found by both CDF and D0, and discusses differences between the detectors and the data found with each.

Feature and Region Selection for Visual Learning.

PubMed

Zhao, Ji; Wang, Liantao; Cabral, Ricardo; De la Torre, Fernando

2016-03-01

Visual learning problems, such as object classification and action recognition, are typically approached using extensions of the popular bag-of-words (BoWs) model. Despite its great success, it is unclear what visual features the BoW model is learning. Which regions in the image or video are used to discriminate among classes? Which are the most discriminative visual words? Answering these questions is fundamental for understanding existing BoW models and inspiring better models for visual recognition. To answer these questions, this paper presents a method for feature selection and region selection in the visual BoW model. This allows for an intermediate visualization of the features and regions that are important for visual learning. The main idea is to assign latent weights to the features or regions, and jointly optimize these latent variables with the parameters of a classifier (e.g., support vector machine). There are four main benefits of our approach: 1) our approach accommodates non-linear additive kernels, such as the popular χ(2) and intersection kernel; 2) our approach is able to handle both regions in images and spatio-temporal regions in videos in a unified way; 3) the feature selection problem is convex, and both problems can be solved using a scalable reduced gradient method; and 4) we point out strong connections with multiple kernel learning and multiple instance learning approaches. Experimental results in the PASCAL VOC 2007, MSR Action Dataset II and YouTube illustrate the benefits of our approach.

Coding visual features extracted from video sequences.

PubMed

Baroffio, Luca; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano

2014-05-01

Visual features are successfully exploited in several applications (e.g., visual search, object recognition and tracking, etc.) due to their ability to efficiently represent image content. Several visual analysis tasks require features to be transmitted over a bandwidth-limited network, thus calling for coding techniques to reduce the required bit budget, while attaining a target level of efficiency. In this paper, we propose, for the first time, a coding architecture designed for local features (e.g., SIFT, SURF) extracted from video sequences. To achieve high coding efficiency, we exploit both spatial and temporal redundancy by means of intraframe and interframe coding modes. In addition, we propose a coding mode decision based on rate-distortion optimization. The proposed coding scheme can be conveniently adopted to implement the analyze-then-compress (ATC) paradigm in the context of visual sensor networks. That is, sets of visual features are extracted from video frames, encoded at remote nodes, and finally transmitted to a central controller that performs visual analysis. This is in contrast to the traditional compress-then-analyze (CTA) paradigm, in which video sequences acquired at a node are compressed and then sent to a central unit for further processing. In this paper, we compare these coding paradigms using metrics that are routinely adopted to evaluate the suitability of visual features in the context of content-based retrieval, object recognition, and tracking. Experimental results demonstrate that, thanks to the significant coding gains achieved by the proposed coding scheme, ATC outperforms CTA with respect to all evaluation metrics.

TU-F-CAMPUS-I-05: Investigation of An EMCCD Detector with Variable Gain in a Micro-CT System

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

Krishnakumar, S Bysani; Ionita, C; Rudin, S

Purpose: To investigate the performance of a newly built Electron Multiplying Charged Coupled Device (EMCCD) based Micro-CT system, with variable detector gain, using a phantom containing contrast agent of different concentrations. Methods: We built a micro- CT system with an EMCCD having 8 microns pixels and on-chip variable gain. We tested the system using a phantom containing five tubes filled with different iodine contrast solutions (30% to 70%). First, we scanned the phantom using various x-ray exposures values at 40 kVp and constant detector gain. Next, for the same tube currents, the detector gain was increased to maintain the airmore » value of the projection image constant. A standard FDK algorithm was used to reconstruct the data. Performance was analyzed by comparing the signal-to-noise ratio (SNR) measurements for increased gain with those for the low constant gain at each exposure. Results: The high detector gain reconstructed data SNR was always greater than the low gain data SNR for all x-ray settings and for all iodine features. The largest increases were observed for low contrast features, 30% iodine concentration, where the SNR improvement approached 2. Conclusion: One of the first implementations of an EMCCD based micro- CT system was presented and used to image a phantom with various iodine solution concentrations. The analysis of the reconstructed volumes showed a significant improvement of the SNR especially for low contrast features. The unique on-chip gain feature is a substantial benefit allowing the use of the system at very low x-ray exposures per frame.Partial support: NIH grant R01EB002873 and Toshiba Medical Systems Corp. Partial support: NIH grant R01EB002873 and Toshiba Medical Systems Corp.« less

Assembling and Using an LED-Based Detector to Monitor Absorbance Changes during Acid-Base Titrations

ERIC Educational Resources Information Center

Santos, Willy G.; Cavalheiro, E´der T. G.

2015-01-01

A simple photometric assembly based in an LED as a light source and a photodiode as a detector is proposed in order to follow the absorbance changes as a function of the titrant volume added during the course of acid-base titrations in the presence of a suitable visual indicator. The simplicity and low cost of the electronic device allow the…

SpectraPLOT, Visualization Package with a User-Friendly Graphical Interface

NASA Astrophysics Data System (ADS)

Sebald, James; Macfarlane, Joseph; Golovkin, Igor

2017-10-01

SPECT3D is a collisional-radiative spectral analysis package designed to compute detailed emission, absorption, or x-ray scattering spectra, filtered images, XRD signals, and other synthetic diagnostics. The spectra and images are computed for virtual detectors by post-processing the results of hydrodynamics simulations in 1D, 2D, and 3D geometries. SPECT3D can account for a variety of instrumental response effects so that direct comparisons between simulations and experimental measurements can be made. SpectraPLOT is a user-friendly graphical interface for viewing a wide variety of results from SPECT3D simulations, and applying various instrumental effects to the simulated images and spectra. We will present SpectraPLOT's ability to display a variety of data, including spectra, images, light curves, streaked spectra, space-resolved spectra, and drilldown plasma property plots, for an argon-doped capsule implosion experiment example. Future SpectraPLOT features and enhancements will also be discussed.

Polarized-pixel performance model for DoFP polarimeter

NASA Astrophysics Data System (ADS)

Feng, Bin; Shi, Zelin; Liu, Haizheng; Liu, Li; Zhao, Yaohong; Zhang, Junchao

2018-06-01

A division of a focal plane (DoFP) polarimeter is manufactured by placing a micropolarizer array directly onto the focal plane array (FPA) of a detector. Each element of the DoFP polarimeter is a polarized pixel. This paper proposes a performance model for a polarized pixel. The proposed model characterizes the optical and electronic performance of a polarized pixel by three parameters. They are respectively major polarization responsivity, minor polarization responsivity and polarization orientation. Each parameter corresponds to an intuitive physical feature of a polarized pixel. This paper further extends this model to calibrate polarization images from a DoFP (division of focal plane) polarimeter. This calibration work is evaluated quantitatively by a developed DoFP polarimeter under varying illumination intensity and angle of linear polarization. The experiment proves that our model reduces nonuniformity to 6.79% of uncalibrated DoLP (degree of linear polarization) images, and significantly improves the visual effect of DoLP images.

Forensic detection of noise addition in digital images

NASA Astrophysics Data System (ADS)

Cao, Gang; Zhao, Yao; Ni, Rongrong; Ou, Bo; Wang, Yongbin

2014-03-01

We proposed a technique to detect the global addition of noise to a digital image. As an anti-forensics tool, noise addition is typically used to disguise the visual traces of image tampering or to remove the statistical artifacts left behind by other operations. As such, the blind detection of noise addition has become imperative as well as beneficial to authenticate the image content and recover the image processing history, which is the goal of general forensics techniques. Specifically, the special image blocks, including constant and strip ones, are used to construct the features for identifying noise addition manipulation. The influence of noising on blockwise pixel value distribution is formulated and analyzed formally. The methodology of detectability recognition followed by binary decision is proposed to ensure the applicability and reliability of noising detection. Extensive experimental results demonstrate the efficacy of our proposed noising detector.

Cross-Modal Facilitation in Speech Prosody

ERIC Educational Resources Information Center

Foxton, Jessica M.; Riviere, Louis-David; Barone, Pascal

2010-01-01

Speech prosody has traditionally been considered solely in terms of its auditory features, yet correlated visual features exist, such as head and eyebrow movements. This study investigated the extent to which visual prosodic features are able to affect the perception of the auditory features. Participants were presented with videos of a speaker…

Visualization of historical data for the ATLAS detector controls - DDV

NASA Astrophysics Data System (ADS)

Maciejewski, J.; Schlenker, S.

2017-10-01

The ATLAS experiment is one of four detectors located on the Large Hardon Collider (LHC) based at CERN. Its detector control system (DCS) stores the slow control data acquired within the back-end of distributed WinCC OA applications, which enables the data to be retrieved for future analysis, debugging and detector development in an Oracle relational database. The ATLAS DCS Data Viewer (DDV) is a client-server application providing access to the historical data outside of the experiment network. The server builds optimized SQL queries, retrieves the data from the database and serves it to the clients via HTTP connections. The server also implements protection methods to prevent malicious use of the database. The client is an AJAX-type web application based on the Vaadin (framework build around the Google Web Toolkit (GWT)) which gives users the possibility to access the data with ease. The DCS metadata can be selected using a column-tree navigation or a search engine supporting regular expressions. The data is visualized by a selection of output modules such as a java script value-over time plots or a lazy loading table widget. Additional plugins give the users the possibility to retrieve the data in ROOT format or as an ASCII file. Control system alarms can also be visualized in a dedicated table if necessary. Python mock-up scripts can be generated by the client, allowing the user to query the pythonic DDV server directly, such that the users can embed the scripts into more complex analysis programs. Users are also able to store searches and output configurations as XML on the server to share with others via URL or to embed in HTML.

Attentive Tracking Disrupts Feature Binding in Visual Working Memory

PubMed Central

Fougnie, Daryl; Marois, René

2009-01-01

One of the most influential theories in visual cognition proposes that attention is necessary to bind different visual features into coherent object percepts (Treisman & Gelade, 1980). While considerable evidence supports a role for attention in perceptual feature binding, whether attention plays a similar function in visual working memory (VWM) remains controversial. To test the attentional requirements of VWM feature binding, here we gave participants an attention-demanding multiple object tracking task during the retention interval of a VWM task. Results show that the tracking task disrupted memory for color-shape conjunctions above and beyond any impairment to working memory for object features, and that this impairment was larger when the VWM stimuli were presented at different spatial locations. These results demonstrate that the role of visuospatial attention in feature binding is not unique to perception, but extends to the working memory of these perceptual representations as well. PMID:19609460

Generic decoding of seen and imagined objects using hierarchical visual features.

PubMed

Horikawa, Tomoyasu; Kamitani, Yukiyasu

2017-05-22

Object recognition is a key function in both human and machine vision. While brain decoding of seen and imagined objects has been achieved, the prediction is limited to training examples. We present a decoding approach for arbitrary objects using the machine vision principle that an object category is represented by a set of features rendered invariant through hierarchical processing. We show that visual features, including those derived from a deep convolutional neural network, can be predicted from fMRI patterns, and that greater accuracy is achieved for low-/high-level features with lower-/higher-level visual areas, respectively. Predicted features are used to identify seen/imagined object categories (extending beyond decoder training) from a set of computed features for numerous object images. Furthermore, decoding of imagined objects reveals progressive recruitment of higher-to-lower visual representations. Our results demonstrate a homology between human and machine vision and its utility for brain-based information retrieval.

Working memory resources are shared across sensory modalities.

PubMed

Salmela, V R; Moisala, M; Alho, K

2014-10-01

A common assumption in the working memory literature is that the visual and auditory modalities have separate and independent memory stores. Recent evidence on visual working memory has suggested that resources are shared between representations, and that the precision of representations sets the limit for memory performance. We tested whether memory resources are also shared across sensory modalities. Memory precision for two visual (spatial frequency and orientation) and two auditory (pitch and tone duration) features was measured separately for each feature and for all possible feature combinations. Thus, only the memory load was varied, from one to four features, while keeping the stimuli similar. In Experiment 1, two gratings and two tones-both containing two varying features-were presented simultaneously. In Experiment 2, two gratings and two tones-each containing only one varying feature-were presented sequentially. The memory precision (delayed discrimination threshold) for a single feature was close to the perceptual threshold. However, as the number of features to be remembered was increased, the discrimination thresholds increased more than twofold. Importantly, the decrease in memory precision did not depend on the modality of the other feature(s), or on whether the features were in the same or in separate objects. Hence, simultaneously storing one visual and one auditory feature had an effect on memory precision equal to those of simultaneously storing two visual or two auditory features. The results show that working memory is limited by the precision of the stored representations, and that working memory can be described as a resource pool that is shared across modalities.

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

Pinilla, Maria Isabel

This report seeks to study and benchmark code predictions against experimental data; determine parameters to match MCNP-simulated detector response functions to experimental stilbene measurements; add stilbene processing capabilities to DRiFT; and improve NEUANCE detector array modeling and analysis using new MCNP6 and DRiFT features.

Visual scan-path analysis with feature space transient fixation moments

NASA Astrophysics Data System (ADS)

Dempere-Marco, Laura; Hu, Xiao-Peng; Yang, Guang-Zhong

2003-05-01

The study of eye movements provides useful insight into the cognitive processes underlying visual search tasks. The analysis of the dynamics of eye movements has often been approached from a purely spatial perspective. In many cases, however, it may not be possible to define meaningful or consistent dynamics without considering the features underlying the scan paths. In this paper, the definition of the feature space has been attempted through the concept of visual similarity and non-linear low dimensional embedding, which defines a mapping from the image space into a low dimensional feature manifold that preserves the intrinsic similarity of image patterns. This has enabled the definition of perceptually meaningful features without the use of domain specific knowledge. Based on this, this paper introduces a new concept called Feature Space Transient Fixation Moments (TFM). The approach presented tackles the problem of feature space representation of visual search through the use of TFM. We demonstrate the practical values of this concept for characterizing the dynamics of eye movements in goal directed visual search tasks. We also illustrate how this model can be used to elucidate the fundamental steps involved in skilled search tasks through the evolution of transient fixation moments.

Advantages of EEG phase patterns for the detection of gait intention in healthy and stroke subjects

NASA Astrophysics Data System (ADS)

Ioana Sburlea, Andreea; Montesano, Luis; Minguez, Javier

2017-06-01

Objective. One use of EEG-based brain-computer interfaces (BCIs) in rehabilitation is the detection of movement intention. In this paper we investigate for the first time the instantaneous phase of movement related cortical potential (MRCP) and its application to the detection of gait intention. Approach. We demonstrate the utility of MRCP phase in two independent datasets, in which 10 healthy subjects and 9 chronic stroke patients executed a self-initiated gait task in three sessions. Phase features were compared to more conventional amplitude and power features. Main results. The neurophysiology analysis showed that phase features have higher signal-to-noise ratio than the other features. Also, BCI detectors of gait intention based on phase, amplitude, and their combination were evaluated under three conditions: session-specific calibration, intersession transfer, and intersubject transfer. Results show that the phase based detector is the most accurate for session-specific calibration (movement intention was correctly detected in 66.5% of trials in healthy subjects, and in 63.3% in stroke patients). However, in intersession and intersubject transfer, the detector that combines amplitude and phase features is the most accurate one and the only that retains its accuracy (62.5% in healthy subjects and 59% in stroke patients) w.r.t. session-specific calibration. Significance. MRCP phase features improve the detection of gait intention and could be used in practice to remove time-consuming BCI recalibration.

SiNC: Saliency-injected neural codes for representation and efficient retrieval of medical radiographs

PubMed Central

Sajjad, Muhammad; Mehmood, Irfan; Baik, Sung Wook

2017-01-01

Medical image collections contain a wealth of information which can assist radiologists and medical experts in diagnosis and disease detection for making well-informed decisions. However, this objective can only be realized if efficient access is provided to semantically relevant cases from the ever-growing medical image repositories. In this paper, we present an efficient method for representing medical images by incorporating visual saliency and deep features obtained from a fine-tuned convolutional neural network (CNN) pre-trained on natural images. Saliency detector is employed to automatically identify regions of interest like tumors, fractures, and calcified spots in images prior to feature extraction. Neuronal activation features termed as neural codes from different CNN layers are comprehensively studied to identify most appropriate features for representing radiographs. This study revealed that neural codes from the last fully connected layer of the fine-tuned CNN are found to be the most suitable for representing medical images. The neural codes extracted from the entire image and salient part of the image are fused to obtain the saliency-injected neural codes (SiNC) descriptor which is used for indexing and retrieval. Finally, locality sensitive hashing techniques are applied on the SiNC descriptor to acquire short binary codes for allowing efficient retrieval in large scale image collections. Comprehensive experimental evaluations on the radiology images dataset reveal that the proposed framework achieves high retrieval accuracy and efficiency for scalable image retrieval applications and compares favorably with existing approaches. PMID:28771497

Visual and semi-automatic non-invasive detection of interictal fast ripples: A potential biomarker of epilepsy in children with tuberous sclerosis complex.

PubMed

Bernardo, Danilo; Nariai, Hiroki; Hussain, Shaun A; Sankar, Raman; Salamon, Noriko; Krueger, Darcy A; Sahin, Mustafa; Northrup, Hope; Bebin, E Martina; Wu, Joyce Y

2018-04-03

We aim to establish that interictal fast ripples (FR; 250-500 Hz) are detectable on scalp EEG, and to investigate their association to epilepsy. Scalp EEG recordings of a subset of children with tuberous sclerosis complex (TSC)-associated epilepsy from two large multicenter observational TSC studies were analyzed and compared to control children without epilepsy or any other brain-based diagnoses. FR were identified both by human visual review and compared with semi-automated review utilizing a deep learning-based FR detector. Seven out of 7 children with TSC-associated epilepsy had scalp FR compared to 0 out of 4 children in the control group (p = 0.003). The automatic detector has a sensitivity of 98% and false positive rate with average of 11.2 false positives per minute. Non-invasive detection of interictal scalp FR was feasible, by both visual and semi-automatic detection. Interictal scalp FR occurred exclusively in children with TSC-associated epilepsy and were absent in controls without epilepsy. The proposed detector achieves high sensitivity of FR detection; however, expert review of the results to reduce false positives is advised. Interictal FR are detectable on scalp EEG and may potentially serve as a biomarker of epilepsy in children with TSC. Copyright © 2018 International Federation of Clinical Neurophysiology. All rights reserved.

Visual Saliency Detection Based on Multiscale Deep CNN Features.

PubMed

Guanbin Li; Yizhou Yu

2016-11-01

Visual saliency is a fundamental problem in both cognitive and computational sciences, including computer vision. In this paper, we discover that a high-quality visual saliency model can be learned from multiscale features extracted using deep convolutional neural networks (CNNs), which have had many successes in visual recognition tasks. For learning such saliency models, we introduce a neural network architecture, which has fully connected layers on top of CNNs responsible for feature extraction at three different scales. The penultimate layer of our neural network has been confirmed to be a discriminative high-level feature vector for saliency detection, which we call deep contrast feature. To generate a more robust feature, we integrate handcrafted low-level features with our deep contrast feature. To promote further research and evaluation of visual saliency models, we also construct a new large database of 4447 challenging images and their pixelwise saliency annotations. Experimental results demonstrate that our proposed method is capable of achieving the state-of-the-art performance on all public benchmarks, improving the F-measure by 6.12% and 10%, respectively, on the DUT-OMRON data set and our new data set (HKU-IS), and lowering the mean absolute error by 9% and 35.3%, respectively, on these two data sets.

Stream specificity and asymmetries in feature binding and content-addressable access in visual encoding and memory.

PubMed

Huynh, Duong L; Tripathy, Srimant P; Bedell, Harold E; Ögmen, Haluk

2015-01-01

Human memory is content addressable-i.e., contents of the memory can be accessed using partial information about the bound features of a stored item. In this study, we used a cross-feature cuing technique to examine how the human visual system encodes, binds, and retains information about multiple stimulus features within a set of moving objects. We sought to characterize the roles of three different features (position, color, and direction of motion, the latter two of which are processed preferentially within the ventral and dorsal visual streams, respectively) in the construction and maintenance of object representations. We investigated the extent to which these features are bound together across the following processing stages: during stimulus encoding, sensory (iconic) memory, and visual short-term memory. Whereas all features examined here can serve as cues for addressing content, their effectiveness shows asymmetries and varies according to cue-report pairings and the stage of information processing and storage. Position-based indexing theories predict that position should be more effective as a cue compared to other features. While we found a privileged role for position as a cue at the stimulus-encoding stage, position was not the privileged cue at the sensory and visual short-term memory stages. Instead, the pattern that emerged from our findings is one that mirrors the parallel processing streams in the visual system. This stream-specific binding and cuing effectiveness manifests itself in all three stages of information processing examined here. Finally, we find that the Leaky Flask model proposed in our previous study is applicable to all three features.

Remembering complex objects in visual working memory: do capacity limits restrict objects or features?

PubMed

Hardman, Kyle O; Cowan, Nelson

2015-03-01

Visual working memory stores stimuli from our environment as representations that can be accessed by high-level control processes. This study addresses a longstanding debate in the literature about whether storage limits in visual working memory include a limit to the complexity of discrete items. We examined the issue with a number of change-detection experiments that used complex stimuli that possessed multiple features per stimulus item. We manipulated the number of relevant features of the stimulus objects in order to vary feature load. In all of our experiments, we found that increased feature load led to a reduction in change-detection accuracy. However, we found that feature load alone could not account for the results but that a consideration of the number of relevant objects was also required. This study supports capacity limits for both feature and object storage in visual working memory. PsycINFO Database Record (c) 2015 APA, all rights reserved.

The Role of Attention in the Maintenance of Feature Bindings in Visual Short-term Memory

ERIC Educational Resources Information Center

Johnson, Jeffrey S.; Hollingworth, Andrew; Luck, Steven J.

2008-01-01

This study examined the role of attention in maintaining feature bindings in visual short-term memory. In a change-detection paradigm, participants attempted to detect changes in the colors and orientations of multiple objects; the changes consisted of new feature values in a feature-memory condition and changes in how existing feature values were…

Is Posner's "beam" the same as Treisman's "glue"?: On the relation between visual orienting and feature integration theory.

PubMed

Briand, K A; Klein, R M

1987-05-01

In the present study we investigated whether the visually allocated "beam" studied by Posner and others is the same visual attentional resource that performs the role of feature integration in Treisman's model. Subjects were cued to attend to a certain spatial location by a visual cue, and performance at expected and unexpected stimulus locations was compared. Subjects searched for a target letter (R) with distractor letters that either could give rise to illusory conjunctions (PQ) or could not (PB). Results from three separate experiments showed that orienting attention in response to central cues (endogenous orienting) showed similar effects for both conjunction and feature search. However, when attention was oriented with peripheral visual cues (exogenous orienting), conjunction search showed larger effects of attention than did feature search. It is suggested that the attentional systems that are oriented in response to central and peripheral cues may not be the same and that only the latter performs a role in feature integration. Possibilities for future research are discussed.

Noise Gating Solar Images

NASA Astrophysics Data System (ADS)

DeForest, Craig; Seaton, Daniel B.; Darnell, John A.

2017-08-01

I present and demonstrate a new, general purpose post-processing technique, "3D noise gating", that can reduce image noise by an order of magnitude or more without effective loss of spatial or temporal resolution in typical solar applications.Nearly all scientific images are, ultimately, limited by noise. Noise can be direct Poisson "shot noise" from photon counting effects, or introduced by other means such as detector read noise. Noise is typically represented as a random variable (perhaps with location- or image-dependent characteristics) that is sampled once per pixel or once per resolution element of an image sequence. Noise limits many aspects of image analysis, including photometry, spatiotemporal resolution, feature identification, morphology extraction, and background modeling and separation.Identifying and separating noise from image signal is difficult. The common practice of blurring in space and/or time works because most image "signal" is concentrated in the low Fourier components of an image, while noise is evenly distributed. Blurring in space and/or time attenuates the high spatial and temporal frequencies, reducing noise at the expense of also attenuating image detail. Noise-gating exploits the same property -- "coherence" -- that we use to identify features in images, to separate image features from noise.Processing image sequences through 3-D noise gating results in spectacular (more than 10x) improvements in signal-to-noise ratio, while not blurring bright, resolved features in either space or time. This improves most types of image analysis, including feature identification, time sequence extraction, absolute and relative photometry (including differential emission measure analysis), feature tracking, computer vision, correlation tracking, background modeling, cross-scale analysis, visual display/presentation, and image compression.I will introduce noise gating, describe the method, and show examples from several instruments (including SDO/AIA , SDO/HMI, STEREO/SECCHI, and GOES-R/SUVI) that explore the benefits and limits of the technique.

EMD-Based Symbolic Dynamic Analysis for the Recognition of Human and Nonhuman Pyroelectric Infrared Signals.

PubMed

Zhao, Jiaduo; Gong, Weiguo; Tang, Yuzhen; Li, Weihong

2016-01-20

In this paper, we propose an effective human and nonhuman pyroelectric infrared (PIR) signal recognition method to reduce PIR detector false alarms. First, using the mathematical model of the PIR detector, we analyze the physical characteristics of the human and nonhuman PIR signals; second, based on the analysis results, we propose an empirical mode decomposition (EMD)-based symbolic dynamic analysis method for the recognition of human and nonhuman PIR signals. In the proposed method, first, we extract the detailed features of a PIR signal into five symbol sequences using an EMD-based symbolization method, then, we generate five feature descriptors for each PIR signal through constructing five probabilistic finite state automata with the symbol sequences. Finally, we use a weighted voting classification strategy to classify the PIR signals with their feature descriptors. Comparative experiments show that the proposed method can effectively classify the human and nonhuman PIR signals and reduce PIR detector's false alarms.

NASA/NOAA: Earth Science Electronic Theater 1999. Earth Science Observations, Analysis and Visualization: Roots in the 60s - Vision for the Next Millennium

NASA Technical Reports Server (NTRS)

Hasler, A. Fritz

1999-01-01

The Etheater presents visualizations which span the period from the original Suomi/Hasler animations of the first ATS-1 GEO weather satellite images in 1966, to the latest 1999 NASA Earth Science Vision for the next 25 years. Hot off the SGI-Onyx Graphics-Supercomputer are NASA''s visualizations of Hurricanes Mitch, Georges, Fran and Linda. These storms have been recently featured on the covers of National Geographic, Time, Newsweek and Popular Science. Highlights will be shown from the NASA hurricane visualization resource video tape that has been used repeatedly this season on National and International network TV. Results will be presented from a new paper on automatic wind measurements in Hurricane Luis from 1-min GOES images that appeared in the November BAMS. The visualizations are produced by the NASA Goddard Visualization & Analysis Laboratory, and Scientific Visualization Studio, as well as other Goddard and NASA groups using NASA, NOAA, ESA, and NASDA Earth science datasets. Visualizations will be shown from the Earth Science ETheater 1999 recently presented in Tokyo, Paris, Munich, Sydney, Melbourne, Honolulu, Washington, New York, and Dallas. The presentation Jan 11-14 at the AMS meeting in Dallas used a 4-CPU SGI/CRAY Onyx Infinite Reality Super Graphics Workstation with 8 GB RAM and a Terabyte Disk at 3840 X 1024 resolution with triple synchronized BarcoReality 9200 projectors on a 60ft wide screen. Visualizations will also be featured from the new Earth Today Exhibit which was opened by Vice President Gore on July 2, 1998 at the Smithsonian Air & Space Museum in Washington, as well as those presented for possible use at the American Museum of Natural History (NYC), Disney EPCOT, and other venues. New methods are demonstrated for visualizing, interpreting, comparing, organizing and analyzing immense HyperImage remote sensing datasets and three dimensional numerical model results. We call the data from many new Earth sensing satellites, HyperImage datasets, because they have such high resolution in the spectral, temporal, spatial, and dynamic range domains. The traditional numerical spreadsheet paradigm has been extended to develop a scientific visualization approach for processing HyperImage datasets and 3D model results interactively. The advantages of extending the powerful spreadsheet style of computation to multiple sets of images and organizing image processing were demonstrated using the Distributed Image SpreadSheet (DISS). The DISS is being used as a high performance testbed Next Generation Internet (NGI) VisAnalysis of: 1) El Nino SSTs and NDVI response 2) Latest GOES 10 5-min rapid Scans of 26 day 5000 frame movie of March & April 198 weather and tornadic storms 3) TRMM rainfall and lightning 4)GOES 9 satellite images/winds and NOAA aircraft radar of hurricane Luis, 5) lightning detector data merged with GOES image sequences, 6) Japanese GMS, TRMM, & ADEOS data 7) Chinese FY2 data 8) Meteosat & ERS/ATSR data 9) synchronized manipulation of multiple 3D numerical model views; etc. will be illustrated. The Image SpreadSheet has been highly successful in producing Earth science visualizations for public outreach.

Unconscious analyses of visual scenes based on feature conjunctions.

PubMed

Tachibana, Ryosuke; Noguchi, Yasuki

2015-06-01

To efficiently process a cluttered scene, the visual system analyzes statistical properties or regularities of visual elements embedded in the scene. It is controversial, however, whether those scene analyses could also work for stimuli unconsciously perceived. Here we show that our brain performs the unconscious scene analyses not only using a single featural cue (e.g., orientation) but also based on conjunctions of multiple visual features (e.g., combinations of color and orientation information). Subjects foveally viewed a stimulus array (duration: 50 ms) where 4 types of bars (red-horizontal, red-vertical, green-horizontal, and green-vertical) were intermixed. Although a conscious perception of those bars was inhibited by a subsequent mask stimulus, the brain correctly analyzed the information about color, orientation, and color-orientation conjunctions of those invisible bars. The information of those features was then used for the unconscious configuration analysis (statistical processing) of the central bars, which induced a perceptual bias and illusory feature binding in visible stimuli at peripheral locations. While statistical analyses and feature binding are normally 2 key functions of the visual system to construct coherent percepts of visual scenes, our results show that a high-level analysis combining those 2 functions is correctly performed by unconscious computations in the brain. (c) 2015 APA, all rights reserved).

Cambio

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

Johnson, William

2015-10-19

Cambio opens data files from common gamma radiation detectors, displays a visual representation of it, and allows the user to edit the meta-data, as well as convert the data to a different file format.

Design and Operation of A Setup with A Camera and Adjustable Mirror to Inspect the Sense-Wire Planes of the Time Projection Chamber Inside the MicroBooNE Cryostat

DOE PAGES

Carls, Benjamin; Horton-Smith, Glenn; James, Catherine C.; ...

2015-08-26

Detectors in particle physics, particularly when including cryogenic components, are often enclosed in vessels that do not provide any physical or visual access to the detectors themselves after installation. However, it can be desirable for experiments to visually investigate the inside of the vessel. The MicroBooNE cryostat hosts a TPC with sense-wire planes, which had to be inspected for damage such as breakage or sagging. This inspection was performed after the transportation of the vessel with the enclosed detector to its final location, but before filling with liquid argon. Our paper describes an approach to view the inside of themore » MicroBooNE cryostat with a setup of a camera and a mirror through one of its cryogenic service nozzles. The paper also describes the camera and mirror chosen for the operation, the illumination, and the mechanical structure of the setup. It explains how the system was operated and demonstrates its performance.« less

Increasing Electrochemiluminescence Intensity of a Wireless Electrode Array Chip by Thousands of Times Using a Diode for Sensitive Visual Detection by a Digital Camera.

PubMed

Qi, Liming; Xia, Yong; Qi, Wenjing; Gao, Wenyue; Wu, Fengxia; Xu, Guobao

2016-01-19

Both a wireless electrochemiluminescence (ECL) electrode microarray chip and the dramatic increase in ECL by embedding a diode in an electromagnetic receiver coil have been first reported. The newly designed device consists of a chip and a transmitter. The chip has an electromagnetic receiver coil, a mini-diode, and a gold electrode array. The mini-diode can rectify alternating current into direct current and thus enhance ECL intensities by 18 thousand times, enabling a sensitive visual detection using common cameras or smart phones as low cost detectors. The detection limit of hydrogen peroxide using a digital camera is comparable to that using photomultiplier tube (PMT)-based detectors. Coupled with a PMT-based detector, the device can detect luminol with higher sensitivity with linear ranges from 10 nM to 1 mM. Because of the advantages including high sensitivity, high throughput, low cost, high portability, and simplicity, it is promising in point of care testing, drug screening, and high throughput analysis.

Finding the Secret of Image Saliency in the Frequency Domain.

PubMed

Li, Jia; Duan, Ling-Yu; Chen, Xiaowu; Huang, Tiejun; Tian, Yonghong

2015-12-01

There are two sides to every story of visual saliency modeling in the frequency domain. On the one hand, image saliency can be effectively estimated by applying simple operations to the frequency spectrum. On the other hand, it is still unclear which part of the frequency spectrum contributes the most to popping-out targets and suppressing distractors. Toward this end, this paper tentatively explores the secret of image saliency in the frequency domain. From the results obtained in several qualitative and quantitative experiments, we find that the secret of visual saliency may mainly hide in the phases of intermediate frequencies. To explain this finding, we reinterpret the concept of discrete Fourier transform from the perspective of template-based contrast computation and thus develop several principles for designing the saliency detector in the frequency domain. Following these principles, we propose a novel approach to design the saliency detector under the assistance of prior knowledge obtained through both unsupervised and supervised learning processes. Experimental results on a public image benchmark show that the learned saliency detector outperforms 18 state-of-the-art approaches in predicting human fixations.

The Convolutional Visual Network for Identification and Reconstruction of NOvA Events

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

Psihas, Fernanda

In 2016 the NOvA experiment released results for the observation of oscillations in the vμ and ve channels as well as ve cross section measurements using neutrinos from Fermilab’s NuMI beam. These and other measurements in progress rely on the accurate identification and reconstruction of the neutrino flavor and energy recorded by our detectors. This presentation describes the first application of convolutional neural network technology for event identification and reconstruction in particle detectors like NOvA. The Convolutional Visual Network (CVN) Algorithm was developed for identification, categorization, and reconstruction of NOvA events. It increased the selection efficiency of the ve appearancemore » signal by 40% and studies show potential impact to the vμ disappearance analysis.« less

Irrelevant reward and selection histories have different influences on task-relevant attentional selection.

PubMed

MacLean, Mary H; Giesbrecht, Barry

2015-07-01

Task-relevant and physically salient features influence visual selective attention. In the present study, we investigated the influence of task-irrelevant and physically nonsalient reward-associated features on visual selective attention. Two hypotheses were tested: One predicts that the effects of target-defining task-relevant and task-irrelevant features interact to modulate visual selection; the other predicts that visual selection is determined by the independent combination of relevant and irrelevant feature effects. These alternatives were tested using a visual search task that contained multiple targets, placing a high demand on the need for selectivity, and that was data-limited and required unspeeded responses, emphasizing early perceptual selection processes. One week prior to the visual search task, participants completed a training task in which they learned to associate particular colors with a specific reward value. In the search task, the reward-associated colors were presented surrounding targets and distractors, but were neither physically salient nor task-relevant. In two experiments, the irrelevant reward-associated features influenced performance, but only when they were presented in a task-relevant location. The costs induced by the irrelevant reward-associated features were greater when they oriented attention to a target than to a distractor. In a third experiment, we examined the effects of selection history in the absence of reward history and found that the interaction between task relevance and selection history differed, relative to when the features had previously been associated with reward. The results indicate that under conditions that demand highly efficient perceptual selection, physically nonsalient task-irrelevant and task-relevant factors interact to influence visual selective attention.

Correlation Between Bulk Material Defects and Spectroscopic Response in Cadmium Zinc Telluride Detectors

NASA Technical Reports Server (NTRS)

Parker, Bradford H.; Stahle, C. M.; Barthelmy, S. D.; Parsons, A. M.; Tueller, J.; VanSant, J. T.; Munoz, B. F.; Snodgrass, S. J.; Mullinix, R. E.

1999-01-01

One of the critical challenges for large area cadmium zinc telluride (CdZnTe) detector arrays is obtaining material capable of uniform imaging and spectroscopic response. Two complementary nondestructive techniques for characterizing bulk CdZnTe have been developed to identify material with a uniform response. The first technique, infrared transmission imaging, allows for rapid visualization of bulk defects. The second technique, x-ray spectral mapping, provides a map of the material spectroscopic response when it is configured as a planar detector. The two techniques have been used to develop a correlation between bulk defect type and detector performance. The correlation allows for the use of infrared imaging to rapidly develop wafer mining maps. The mining of material free of detrimental defects has the potential to dramatically increase the yield and quality of large area CdZnTe detector arrays.

Classification of visual and linguistic tasks using eye-movement features.

PubMed

Coco, Moreno I; Keller, Frank

2014-03-07

The role of the task has received special attention in visual-cognition research because it can provide causal explanations of goal-directed eye-movement responses. The dependency between visual attention and task suggests that eye movements can be used to classify the task being performed. A recent study by Greene, Liu, and Wolfe (2012), however, fails to achieve accurate classification of visual tasks based on eye-movement features. In the present study, we hypothesize that tasks can be successfully classified when they differ with respect to the involvement of other cognitive domains, such as language processing. We extract the eye-movement features used by Greene et al. as well as additional features from the data of three different tasks: visual search, object naming, and scene description. First, we demonstrated that eye-movement responses make it possible to characterize the goals of these tasks. Then, we trained three different types of classifiers and predicted the task participants performed with an accuracy well above chance (a maximum of 88% for visual search). An analysis of the relative importance of features for classification accuracy reveals that just one feature, i.e., initiation time, is sufficient for above-chance performance (a maximum of 79% accuracy in object naming). Crucially, this feature is independent of task duration, which differs systematically across the three tasks we investigated. Overall, the best task classification performance was obtained with a set of seven features that included both spatial information (e.g., entropy of attention allocation) and temporal components (e.g., total fixation on objects) of the eye-movement record. This result confirms the task-dependent allocation of visual attention and extends previous work by showing that task classification is possible when tasks differ in the cognitive processes involved (purely visual tasks such as search vs. communicative tasks such as scene description).

Small blob identification in medical images using regional features from optimum scale.

PubMed

Zhang, Min; Wu, Teresa; Bennett, Kevin M

2015-04-01

Recent advances in medical imaging technology have greatly enhanced imaging-based diagnosis which requires computational effective and accurate algorithms to process the images (e.g., measure the objects) for quantitative assessment. In this research, we are interested in one type of imaging objects: small blobs. Examples of small blob objects are cells in histopathology images, glomeruli in MR images, etc. This problem is particularly challenging because the small blobs often have in homogeneous intensity distribution and an indistinct boundary against the background. Yet, in general, these blobs have similar sizes. Motivated by this finding, we propose a novel detector termed Hessian-based Laplacian of Gaussian (HLoG) using scale space theory as the foundation. Like most imaging detectors, an image is first smoothed via LoG. Hessian analysis is then launched to identify the single optimal scale on which a presegmentation is conducted. The advantage of the Hessian process is that it is capable of delineating the blobs. As a result, regional features can be retrieved. These features enable an unsupervised clustering algorithm for postpruning which should be more robust and sensitive than the traditional threshold-based postpruning commonly used in most imaging detectors. To test the performance of the proposed HLoG, two sets of 2-D grey medical images are studied. HLoG is compared against three state-of-the-art detectors: generalized LoG, Radial-Symmetry and LoG using precision, recall, and F-score metrics.We observe that HLoG statistically outperforms the compared detectors.

Self-Calibration and Laser Energy Monitor Validations for a Double-Pulsed 2-Micron CO2 Integrated Path Differential Absorption Lidar Application

NASA Technical Reports Server (NTRS)

Refaat, Tamer F.; Singh, Upendra N.; Petros, Mulugeta; Remus, Ruben; Yu, Jirong

2015-01-01

Double-pulsed 2-micron integrated path differential absorption (IPDA) lidar is well suited for atmospheric CO2 remote sensing. The IPDA lidar technique relies on wavelength differentiation between strong and weak absorbing features of the gas normalized to the transmitted energy. In the double-pulse case, each shot of the transmitter produces two successive laser pulses separated by a short interval. Calibration of the transmitted pulse energies is required for accurate CO2 measurement. Design and calibration of a 2-micron double-pulse laser energy monitor is presented. The design is based on an InGaAs pin quantum detector. A high-speed photo-electromagnetic quantum detector was used for laser-pulse profile verification. Both quantum detectors were calibrated using a reference pyroelectric thermal detector. Calibration included comparing the three detection technologies in the single-pulsed mode, then comparing the quantum detectors in the double-pulsed mode. In addition, a self-calibration feature of the 2-micron IPDA lidar is presented. This feature allows one to monitor the transmitted laser energy, through residual scattering, with a single detection channel. This reduces the CO2 measurement uncertainty. IPDA lidar ground validation for CO2 measurement is presented for both calibrated energy monitor and self-calibration options. The calibrated energy monitor resulted in a lower CO2 measurement bias, while self-calibration resulted in a better CO2 temporal profiling when compared to the in situ sensor.

Deep Residual Network Predicts Cortical Representation and Organization of Visual Features for Rapid Categorization.

PubMed

Wen, Haiguang; Shi, Junxing; Chen, Wei; Liu, Zhongming

2018-02-28

The brain represents visual objects with topographic cortical patterns. To address how distributed visual representations enable object categorization, we established predictive encoding models based on a deep residual network, and trained them to predict cortical responses to natural movies. Using this predictive model, we mapped human cortical representations to 64,000 visual objects from 80 categories with high throughput and accuracy. Such representations covered both the ventral and dorsal pathways, reflected multiple levels of object features, and preserved semantic relationships between categories. In the entire visual cortex, object representations were organized into three clusters of categories: biological objects, non-biological objects, and background scenes. In a finer scale specific to each cluster, object representations revealed sub-clusters for further categorization. Such hierarchical clustering of category representations was mostly contributed by cortical representations of object features from middle to high levels. In summary, this study demonstrates a useful computational strategy to characterize the cortical organization and representations of visual features for rapid categorization.

Calibration of RGBD camera and cone-beam CT for 3D intra-operative mixed reality visualization.

PubMed

Lee, Sing Chun; Fuerst, Bernhard; Fotouhi, Javad; Fischer, Marius; Osgood, Greg; Navab, Nassir

2016-06-01

This work proposes a novel algorithm to register cone-beam computed tomography (CBCT) volumes and 3D optical (RGBD) camera views. The co-registered real-time RGBD camera and CBCT imaging enable a novel augmented reality solution for orthopedic surgeries, which allows arbitrary views using digitally reconstructed radiographs overlaid on the reconstructed patient's surface without the need to move the C-arm. An RGBD camera is rigidly mounted on the C-arm near the detector. We introduce a calibration method based on the simultaneous reconstruction of the surface and the CBCT scan of an object. The transformation between the two coordinate spaces is recovered using Fast Point Feature Histogram descriptors and the Iterative Closest Point algorithm. Several experiments are performed to assess the repeatability and the accuracy of this method. Target registration error is measured on multiple visual and radio-opaque landmarks to evaluate the accuracy of the registration. Mixed reality visualizations from arbitrary angles are also presented for simulated orthopedic surgeries. To the best of our knowledge, this is the first calibration method which uses only tomographic and RGBD reconstructions. This means that the method does not impose a particular shape of the phantom. We demonstrate a marker-less calibration of CBCT volumes and 3D depth cameras, achieving reasonable registration accuracy. This design requires a one-time factory calibration, is self-contained, and could be integrated into existing mobile C-arms to provide real-time augmented reality views from arbitrary angles.

Automated response matching for organic scintillation detector arrays

NASA Astrophysics Data System (ADS)

Aspinall, M. D.; Joyce, M. J.; Cave, F. D.; Plenteda, R.; Tomanin, A.

2017-07-01

This paper identifies a digitizer technology with unique features that facilitates feedback control for the realization of a software-based technique for automatically calibrating detector responses. Three such auto-calibration techniques have been developed and are described along with an explanation of the main configuration settings and potential pitfalls. Automating this process increases repeatability, simplifies user operation, enables remote and periodic system calibration where consistency across detectors' responses are critical.

Novel Drift Structures for Silicon and Compound Semiconductor X-Ray and Gamma-Ray Detectors

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

Bradley E. Patt; Jan S. Iwanczyk

Recently developed silicon- and compound-semiconductor-based drift detector structures have produced excellent performance for charged particles, X rays, and gamma rays and for low-signal visible light detection. The silicon drift detector (SDD) structures that we discuss relate to direct X-ray detectors and scintillation photon detectors coupled with scintillators for gamma rays. Recent designs include several novel features that ensure very low dark current (both bulk silicon dark current and surface dark current) and hence low noise. In addition, application of thin window technology ensures a very high quantum efficiency entrance window on the drift photodetector.

Anisotropic-Scale Junction Detection and Matching for Indoor Images.

PubMed

Xue, Nan; Xia, Gui-Song; Bai, Xiang; Zhang, Liangpei; Shen, Weiming

Junctions play an important role in characterizing local geometrical structures of images, and the detection of which is a longstanding but challenging task. Existing junction detectors usually focus on identifying the location and orientations of junction branches while ignoring their scales, which, however, contain rich geometries of images. This paper presents a novel approach for junction detection and characterization, which especially exploits the locally anisotropic geometries of a junction and estimates its scales by relying on an a-contrario model. The output junctions are with anisotropic scales, saying that a scale parameter is associated with each branch of a junction and are thus named as anisotropic-scale junctions (ASJs). We then apply the new detected ASJs for matching indoor images, where there are dramatic changes of viewpoints and the detected local visual features, e.g., key-points, are usually insufficient and lack distinctive ability. We propose to use the anisotropic geometries of our junctions to improve the matching precision of indoor images. The matching results on sets of indoor images demonstrate that our approach achieves the state-of-the-art performance on indoor image matching.Junctions play an important role in characterizing local geometrical structures of images, and the detection of which is a longstanding but challenging task. Existing junction detectors usually focus on identifying the location and orientations of junction branches while ignoring their scales, which, however, contain rich geometries of images. This paper presents a novel approach for junction detection and characterization, which especially exploits the locally anisotropic geometries of a junction and estimates its scales by relying on an a-contrario model. The output junctions are with anisotropic scales, saying that a scale parameter is associated with each branch of a junction and are thus named as anisotropic-scale junctions (ASJs). We then apply the new detected ASJs for matching indoor images, where there are dramatic changes of viewpoints and the detected local visual features, e.g., key-points, are usually insufficient and lack distinctive ability. We propose to use the anisotropic geometries of our junctions to improve the matching precision of indoor images. The matching results on sets of indoor images demonstrate that our approach achieves the state-of-the-art performance on indoor image matching.

Observation and analysis of microcirculation using high-spatial-resolution image detectors and synchrotron radiation

NASA Astrophysics Data System (ADS)

Umetani, Keiji; Yagi, Naoto; Suzuki, Yoshio; Ogasawara, Yasuo; Kajiya, Fumihiko; Matsumoto, Takeshi; Tachibana, Hiroyuki; Goto, Masami; Yamashita, Takenori; Imai, Shigeki; Kajihara, Yasumasa

2000-04-01

A microangiography system using monochromatized synchrotron radiation has been investigated as a diagnostic tool for circulatory disorders and early stage malignant tumors. The monochromatized X-rays with energies just above the contrast agent K-absorption edge energy can produce the highest contrast image of the contrast agent in small blood vessels. At SPring-8, digital microradiography with 6 - 24 micrometer pixel sizes has been carried out using two types of detectors designed for X-ray indirect and direct detection. The indirect-sensing detectors are fluorescent-screen optical-lens coupling systems using a high-sensitivity pickup-tube camera and a CCD camera. An X-ray image on the fluorescent screen is focused on the photoconductive layer of the pickup tube and the photosensitive area of the CCD by a small F number lens. The direct-sensing detector consists of an X-ray direct- sensing pickup tube with a beryllium faceplate for X-ray incidence to the photoconductive layer. Absorbed X-rays in the photoconductive layer are directly converted to photoelectrons and then signal charges are readout by electron beam scanning. The direct-sensing detector was expected to have higher spatial resolution in comparison with the indict-sensing detectors. Performance of the X-ray image detectors was examined at the bending magnet beamline BL20B2 using monochromatized X-ray at SPring-8. Image signals from the camera are converted into digital format by an analog-to- digital converter and stored in a frame memory with image format of 1024 X 1024 pixels. In preliminary experiments, tumor vessel specimens using barium contrast agent were prepared for taking static images. The growth pattern of tumor-induced vessels was clearly visualized. Heart muscle specimens were prepared for imaging of 3-dimensional microtomography using the fluorescent-screen CCD camera system. The complex structure of small blood vessels with diameters of 30 - 40 micrometer was visualized as a 3- dimensional CT image.

Freezing of Gait Detection in Parkinson's Disease: A Subject-Independent Detector Using Anomaly Scores.

PubMed

Pham, Thuy T; Moore, Steven T; Lewis, Simon John Geoffrey; Nguyen, Diep N; Dutkiewicz, Eryk; Fuglevand, Andrew J; McEwan, Alistair L; Leong, Philip H W

2017-11-01

Freezing of gait (FoG) is common in Parkinsonian gait and strongly relates to falls. Current clinical FoG assessments are patients' self-report diaries and experts' manual video analysis. Both are subjective and yield moderate reliability. Existing detection algorithms have been predominantly designed in subject-dependent settings. In this paper, we aim to develop an automated FoG detector for subject independent. After extracting highly relevant features, we apply anomaly detection techniques to detect FoG events. Specifically, feature selection is performed using correlation and clusterability metrics. From a list of 244 feature candidates, 36 candidates were selected using saliency and robustness criteria. We develop an anomaly score detector with adaptive thresholding to identify FoG events. Then, using accuracy metrics, we reduce the feature list to seven candidates. Our novel multichannel freezing index was the most selective across all window sizes, achieving sensitivity (specificity) of (). On the other hand, freezing index from the vertical axis was the best choice for a single input, achieving sensitivity (specificity) of () for ankle and () for back sensors. Our subject-independent method is not only significantly more accurate than those previously reported, but also uses a much smaller window (e.g., versus ) and/or lower tolerance (e.g., versus ).Freezing of gait (FoG) is common in Parkinsonian gait and strongly relates to falls. Current clinical FoG assessments are patients' self-report diaries and experts' manual video analysis. Both are subjective and yield moderate reliability. Existing detection algorithms have been predominantly designed in subject-dependent settings. In this paper, we aim to develop an automated FoG detector for subject independent. After extracting highly relevant features, we apply anomaly detection techniques to detect FoG events. Specifically, feature selection is performed using correlation and clusterability metrics. From a list of 244 feature candidates, 36 candidates were selected using saliency and robustness criteria. We develop an anomaly score detector with adaptive thresholding to identify FoG events. Then, using accuracy metrics, we reduce the feature list to seven candidates. Our novel multichannel freezing index was the most selective across all window sizes, achieving sensitivity (specificity) of (). On the other hand, freezing index from the vertical axis was the best choice for a single input, achieving sensitivity (specificity) of () for ankle and () for back sensors. Our subject-independent method is not only significantly more accurate than those previously reported, but also uses a much smaller window (e.g., versus ) and/or lower tolerance (e.g., versus ).

Spatial and temporal coherence in perceptual binding

PubMed Central

Blake, Randolph; Yang, Yuede

1997-01-01

Component visual features of objects are registered by distributed patterns of activity among neurons comprising multiple pathways and visual areas. How these distributed patterns of activity give rise to unified representations of objects remains unresolved, although one recent, controversial view posits temporal coherence of neural activity as a binding agent. Motivated by the possible role of temporal coherence in feature binding, we devised a novel psychophysical task that requires the detection of temporal coherence among features comprising complex visual images. Results show that human observers can more easily detect synchronized patterns of temporal contrast modulation within hybrid visual images composed of two components when those components are drawn from the same original picture. Evidently, time-varying changes within spatially coherent features produce more salient neural signals. PMID:9192701

A BODIPY-Based Fluorescent Probe to Visually Detect Phosgene: Toward the Development of a Handheld Phosgene Detector.

PubMed

Sayar, Melike; Karakuş, Erman; Güner, Tuğrul; Yildiz, Busra; Yildiz, Umit Hakan; Emrullahoğlu, Mustafa

2018-03-02

A boron-dipyrromethene (BODIPY)-based fluorescent probe with a phosgene-specific reactive motif shows remarkable selectivity toward phosgene, in the presence of which the nonfluorescent dye rapidly transforms into a new structure and induces a fluorescent response clearly observable to the naked eye under ultraviolet light. Given that dynamic, a prototypical handheld phosgene detector with a promising sensing capability that expedites the detection of gaseous phosgene without sophisticated instrumentation was developed. The proposed method using the handheld detector involves a rapid response period suitable for issuing early warnings during emergency situations. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Simulation of the Interactions Between Gamma-Rays and Detectors Using BSIMUL

NASA Technical Reports Server (NTRS)

Haywood, S. E.; Rester, A. C., Jr.

1996-01-01

Progress made during 1995 on the Monte-Carlo gamma-ray spectrum simulation program BSIMUL is discussed. Several features have been added, including the ability to model shield that are tapered cylinders. Several simulations were made on the Near Earth Asteroid Rendezvous detector.

Imaging characterization of a new gamma ray detector based on CRY019 scintillation crystal for PET and SPECT applications

NASA Astrophysics Data System (ADS)

Polito, C.; Pani, R.; Trigila, C.; Cinti, M. N.; Fabbri, A.; Frantellizzi, V.; De Vincentis, G.; Pellegrini, R.; Pani, R.

2017-02-01

In the last 40 years, in the field of Molecular Medicine imaging there has been a huge growth in the employment and in the improvement of detectors for PET and SPECT applications in order to reach accurate diagnosis of the diseases. The most important feature required to these detectors is an high quality of images that is usually obtained benefitting from the development of a wide number of new scintillation crystals with high imaging performances. In this contest, features like high detection efficiency, short decay time, great spectral match with photodetectors, absence of afterglow and low costs are surely attractive. However, there are other factors playing an important role in the realization of high quality images such as energy and spatial resolutions, position linearity and contrast resolution. With the aim to realize an high performace gamma ray detector for PET and SPECT applications, this work is focused on the evaluation of the imaging characteristics of a recently developed scintillation crystal, CRY019.

Differences in Visual-Spatial Input May Underlie Different Compression Properties of Firing Fields for Grid Cell Modules in Medial Entorhinal Cortex

PubMed Central

Raudies, Florian; Hasselmo, Michael E.

2015-01-01

Firing fields of grid cells in medial entorhinal cortex show compression or expansion after manipulations of the location of environmental barriers. This compression or expansion could be selective for individual grid cell modules with particular properties of spatial scaling. We present a model for differences in the response of modules to barrier location that arise from different mechanisms for the influence of visual features on the computation of location that drives grid cell firing patterns. These differences could arise from differences in the position of visual features within the visual field. When location was computed from the movement of visual features on the ground plane (optic flow) in the ventral visual field, this resulted in grid cell spatial firing that was not sensitive to barrier location in modules modeled with small spacing between grid cell firing fields. In contrast, when location was computed from static visual features on walls of barriers, i.e. in the more dorsal visual field, this resulted in grid cell spatial firing that compressed or expanded based on the barrier locations in modules modeled with large spacing between grid cell firing fields. This indicates that different grid cell modules might have differential properties for computing location based on visual cues, or the spatial radius of sensitivity to visual cues might differ between modules. PMID:26584432

Machine assisted histogram classification

NASA Astrophysics Data System (ADS)

Benyó, B.; Gaspar, C.; Somogyi, P.

2010-04-01

LHCb is one of the four major experiments under completion at the Large Hadron Collider (LHC). Monitoring the quality of the acquired data is important, because it allows the verification of the detector performance. Anomalies, such as missing values or unexpected distributions can be indicators of a malfunctioning detector, resulting in poor data quality. Spotting faulty or ageing components can be either done visually using instruments, such as the LHCb Histogram Presenter, or with the help of automated tools. In order to assist detector experts in handling the vast monitoring information resulting from the sheer size of the detector, we propose a graph based clustering tool combined with machine learning algorithm and demonstrate its use by processing histograms representing 2D hitmaps events. We prove the concept by detecting ion feedback events in the LHCb experiment's RICH subdetector.

Feature-based memory-driven attentional capture: visual working memory content affects visual attention.

PubMed

Olivers, Christian N L; Meijer, Frank; Theeuwes, Jan

2006-10-01

In 7 experiments, the authors explored whether visual attention (the ability to select relevant visual information) and visual working memory (the ability to retain relevant visual information) share the same content representations. The presence of singleton distractors interfered more strongly with a visual search task when it was accompanied by an additional memory task. Singleton distractors interfered even more when they were identical or related to the object held in memory, but only when it was difficult to verbalize the memory content. Furthermore, this content-specific interaction occurred for features that were relevant to the memory task but not for irrelevant features of the same object or for once-remembered objects that could be forgotten. Finally, memory-related distractors attracted more eye movements but did not result in longer fixations. The results demonstrate memory-driven attentional capture on the basis of content-specific representations. Copyright 2006 APA.

Hierarchical acquisition of visual specificity in spatial contextual cueing.

PubMed

Lie, Kin-Pou

2015-01-01

Spatial contextual cueing refers to visual search performance's being improved when invariant associations between target locations and distractor spatial configurations are learned incidentally. Using the instance theory of automatization and the reverse hierarchy theory of visual perceptual learning, this study explores the acquisition of visual specificity in spatial contextual cueing. Two experiments in which detailed visual features were irrelevant for distinguishing between spatial contexts found that spatial contextual cueing was visually generic in difficult trials when the trials were not preceded by easy trials (Experiment 1) but that spatial contextual cueing progressed to visual specificity when difficult trials were preceded by easy trials (Experiment 2). These findings support reverse hierarchy theory, which predicts that even when detailed visual features are irrelevant for distinguishing between spatial contexts, spatial contextual cueing can progress to visual specificity if the stimuli remain constant, the task is difficult, and difficult trials are preceded by easy trials. However, these findings are inconsistent with instance theory, which predicts that when detailed visual features are irrelevant for distinguishing between spatial contexts, spatial contextual cueing will not progress to visual specificity. This study concludes that the acquisition of visual specificity in spatial contextual cueing is more plausibly hierarchical, rather than instance-based.

Area 18 of the cat: the first step in processing visual movement information.

PubMed

Orban, G A

1977-01-01

In cats, responses of area 18 neurons to different moving patterns were measured. The influence of three movement parameters--direction, angular velocity, and amplitude of movement--were tested. The results indicate that in area 18 no ideal movement detector exists, but that simple and complex cells each perform complementary operations of primary visual areas, i.e. analysis and detection of movement.

Object recognition with hierarchical discriminant saliency networks.

PubMed

Han, Sunhyoung; Vasconcelos, Nuno

2014-01-01

The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and computer vision literatures. This demonstrates benefits for all the functional enhancements of the HDSN, the class tuning inherent to discriminant saliency, and saliency layers based on templates of increasing target selectivity and invariance. Altogether, these experiments suggest that there are non-trivial benefits in integrating attention and recognition.

Animated analysis of geoscientific datasets: An interactive graphical application

NASA Astrophysics Data System (ADS)

Morse, Peter; Reading, Anya; Lueg, Christopher

2017-12-01

Geoscientists are required to analyze and draw conclusions from increasingly large volumes of data. There is a need to recognise and characterise features and changing patterns of Earth observables within such large datasets. It is also necessary to identify significant subsets of the data for more detailed analysis. We present an innovative, interactive software tool and workflow to visualise, characterise, sample and tag large geoscientific datasets from both local and cloud-based repositories. It uses an animated interface and human-computer interaction to utilise the capacity of human expert observers to identify features via enhanced visual analytics. 'Tagger' enables users to analyze datasets that are too large in volume to be drawn legibly on a reasonable number of single static plots. Users interact with the moving graphical display, tagging data ranges of interest for subsequent attention. The tool provides a rapid pre-pass process using fast GPU-based OpenGL graphics and data-handling and is coded in the Quartz Composer visual programing language (VPL) on Mac OSX. It makes use of interoperable data formats, and cloud-based (or local) data storage and compute. In a case study, Tagger was used to characterise a decade (2000-2009) of data recorded by the Cape Sorell Waverider Buoy, located approximately 10 km off the west coast of Tasmania, Australia. These data serve as a proxy for the understanding of Southern Ocean storminess, which has both local and global implications. This example shows use of the tool to identify and characterise 4 different types of storm and non-storm events during this time. Events characterised in this way are compared with conventional analysis, noting advantages and limitations of data analysis using animation and human interaction. Tagger provides a new ability to make use of humans as feature detectors in computer-based analysis of large-volume geosciences and other data.

STDP-based spiking deep convolutional neural networks for object recognition.

PubMed

Kheradpisheh, Saeed Reza; Ganjtabesh, Mohammad; Thorpe, Simon J; Masquelier, Timothée

2018-03-01

Previous studies have shown that spike-timing-dependent plasticity (STDP) can be used in spiking neural networks (SNN) to extract visual features of low or intermediate complexity in an unsupervised manner. These studies, however, used relatively shallow architectures, and only one layer was trainable. Another line of research has demonstrated - using rate-based neural networks trained with back-propagation - that having many layers increases the recognition robustness, an approach known as deep learning. We thus designed a deep SNN, comprising several convolutional (trainable with STDP) and pooling layers. We used a temporal coding scheme where the most strongly activated neurons fire first, and less activated neurons fire later or not at all. The network was exposed to natural images. Thanks to STDP, neurons progressively learned features corresponding to prototypical patterns that were both salient and frequent. Only a few tens of examples per category were required and no label was needed. After learning, the complexity of the extracted features increased along the hierarchy, from edge detectors in the first layer to object prototypes in the last layer. Coding was very sparse, with only a few thousands spikes per image, and in some cases the object category could be reasonably well inferred from the activity of a single higher-order neuron. More generally, the activity of a few hundreds of such neurons contained robust category information, as demonstrated using a classifier on Caltech 101, ETH-80, and MNIST databases. We also demonstrate the superiority of STDP over other unsupervised techniques such as random crops (HMAX) or auto-encoders. Taken together, our results suggest that the combination of STDP with latency coding may be a key to understanding the way that the primate visual system learns, its remarkable processing speed and its low energy consumption. These mechanisms are also interesting for artificial vision systems, particularly for hardware solutions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Atoms of recognition in human and computer vision.

PubMed

Ullman, Shimon; Assif, Liav; Fetaya, Ethan; Harari, Daniel

2016-03-08

Discovering the visual features and representations used by the brain to recognize objects is a central problem in the study of vision. Recently, neural network models of visual object recognition, including biological and deep network models, have shown remarkable progress and have begun to rival human performance in some challenging tasks. These models are trained on image examples and learn to extract features and representations and to use them for categorization. It remains unclear, however, whether the representations and learning processes discovered by current models are similar to those used by the human visual system. Here we show, by introducing and using minimal recognizable images, that the human visual system uses features and processes that are not used by current models and that are critical for recognition. We found by psychophysical studies that at the level of minimal recognizable images a minute change in the image can have a drastic effect on recognition, thus identifying features that are critical for the task. Simulations then showed that current models cannot explain this sensitivity to precise feature configurations and, more generally, do not learn to recognize minimal images at a human level. The role of the features shown here is revealed uniquely at the minimal level, where the contribution of each feature is essential. A full understanding of the learning and use of such features will extend our understanding of visual recognition and its cortical mechanisms and will enhance the capacity of computational models to learn from visual experience and to deal with recognition and detailed image interpretation.

Human Occipital and Parietal GABA Selectively Influence Visual Perception of Orientation and Size.

PubMed

Song, Chen; Sandberg, Kristian; Andersen, Lau Møller; Blicher, Jakob Udby; Rees, Geraint

2017-09-13

GABA is the primary inhibitory neurotransmitter in human brain. The level of GABA varies substantially across individuals, and this variability is associated with interindividual differences in visual perception. However, it remains unclear whether the association between GABA level and visual perception reflects a general influence of visual inhibition or whether the GABA levels of different cortical regions selectively influence perception of different visual features. To address this, we studied how the GABA levels of parietal and occipital cortices related to interindividual differences in size, orientation, and brightness perception. We used visual contextual illusion as a perceptual assay since the illusion dissociates perceptual content from stimulus content and the magnitude of the illusion reflects the effect of visual inhibition. Across individuals, we observed selective correlations between the level of GABA and the magnitude of contextual illusion. Specifically, parietal GABA level correlated with size illusion magnitude but not with orientation or brightness illusion magnitude; in contrast, occipital GABA level correlated with orientation illusion magnitude but not with size or brightness illusion magnitude. Our findings reveal a region- and feature-dependent influence of GABA level on human visual perception. Parietal and occipital cortices contain, respectively, topographic maps of size and orientation preference in which neural responses to stimulus sizes and stimulus orientations are modulated by intraregional lateral connections. We propose that these lateral connections may underlie the selective influence of GABA on visual perception. SIGNIFICANCE STATEMENT GABA, the primary inhibitory neurotransmitter in human visual system, varies substantially across individuals. This interindividual variability in GABA level is linked to interindividual differences in many aspects of visual perception. However, the widespread influence of GABA raises the question of whether interindividual variability in GABA reflects an overall variability in visual inhibition and has a general influence on visual perception or whether the GABA levels of different cortical regions have selective influence on perception of different visual features. Here we report a region- and feature-dependent influence of GABA level on human visual perception. Our findings suggest that GABA level of a cortical region selectively influences perception of visual features that are topographically mapped in this region through intraregional lateral connections. Copyright © 2017 Song, Sandberg et al.

Object Recognition in Mental Representations: Directions for Exploring Diagnostic Features through Visual Mental Imagery.

PubMed

Roldan, Stephanie M

2017-01-01

One of the fundamental goals of object recognition research is to understand how a cognitive representation produced from the output of filtered and transformed sensory information facilitates efficient viewer behavior. Given that mental imagery strongly resembles perceptual processes in both cortical regions and subjective visual qualities, it is reasonable to question whether mental imagery facilitates cognition in a manner similar to that of perceptual viewing: via the detection and recognition of distinguishing features. Categorizing the feature content of mental imagery holds potential as a reverse pathway by which to identify the components of a visual stimulus which are most critical for the creation and retrieval of a visual representation. This review will examine the likelihood that the information represented in visual mental imagery reflects distinctive object features thought to facilitate efficient object categorization and recognition during perceptual viewing. If it is the case that these representational features resemble their sensory counterparts in both spatial and semantic qualities, they may well be accessible through mental imagery as evaluated through current investigative techniques. In this review, methods applied to mental imagery research and their findings are reviewed and evaluated for their efficiency in accessing internal representations, and implications for identifying diagnostic features are discussed. An argument is made for the benefits of combining mental imagery assessment methods with diagnostic feature research to advance the understanding of visual perceptive processes, with suggestions for avenues of future investigation.

Object Recognition in Mental Representations: Directions for Exploring Diagnostic Features through Visual Mental Imagery

PubMed Central

Roldan, Stephanie M.

2017-01-01

One of the fundamental goals of object recognition research is to understand how a cognitive representation produced from the output of filtered and transformed sensory information facilitates efficient viewer behavior. Given that mental imagery strongly resembles perceptual processes in both cortical regions and subjective visual qualities, it is reasonable to question whether mental imagery facilitates cognition in a manner similar to that of perceptual viewing: via the detection and recognition of distinguishing features. Categorizing the feature content of mental imagery holds potential as a reverse pathway by which to identify the components of a visual stimulus which are most critical for the creation and retrieval of a visual representation. This review will examine the likelihood that the information represented in visual mental imagery reflects distinctive object features thought to facilitate efficient object categorization and recognition during perceptual viewing. If it is the case that these representational features resemble their sensory counterparts in both spatial and semantic qualities, they may well be accessible through mental imagery as evaluated through current investigative techniques. In this review, methods applied to mental imagery research and their findings are reviewed and evaluated for their efficiency in accessing internal representations, and implications for identifying diagnostic features are discussed. An argument is made for the benefits of combining mental imagery assessment methods with diagnostic feature research to advance the understanding of visual perceptive processes, with suggestions for avenues of future investigation. PMID:28588538

Semi-automatic mapping of cultural heritage from airborne laser scanning using deep learning

NASA Astrophysics Data System (ADS)

Due Trier, Øivind; Salberg, Arnt-Børre; Holger Pilø, Lars; Tonning, Christer; Marius Johansen, Hans; Aarsten, Dagrun

2016-04-01

This paper proposes to use deep learning to improve semi-automatic mapping of cultural heritage from airborne laser scanning (ALS) data. Automatic detection methods, based on traditional pattern recognition, have been applied in a number of cultural heritage mapping projects in Norway for the past five years. Automatic detection of pits and heaps have been combined with visual interpretation of the ALS data for the mapping of deer hunting systems, iron production sites, grave mounds and charcoal kilns. However, the performance of the automatic detection methods varies substantially between ALS datasets. For the mapping of deer hunting systems on flat gravel and sand sediment deposits, the automatic detection results were almost perfect. However, some false detections appeared in the terrain outside of the sediment deposits. These could be explained by other pit-like landscape features, like parts of river courses, spaces between boulders, and modern terrain modifications. However, these were easy to spot during visual interpretation, and the number of missed individual pitfall traps was still low. For the mapping of grave mounds, the automatic method produced a large number of false detections, reducing the usefulness of the semi-automatic approach. The mound structure is a very common natural terrain feature, and the grave mounds are less distinct in shape than the pitfall traps. Still, applying automatic mound detection on an entire municipality did lead to a new discovery of an Iron Age grave field with more than 15 individual mounds. Automatic mound detection also proved to be useful for a detailed re-mapping of Norway's largest Iron Age grave yard, which contains almost 1000 individual graves. Combined pit and mound detection has been applied to the mapping of more than 1000 charcoal kilns that were used by an iron work 350-200 years ago. The majority of charcoal kilns were indirectly detected as either pits on the circumference, a central mound, or both. However, kilns with a flat interior and a shallow ditch along the circumference were often missed by the automatic detection method. The successfulness of automatic detection seems to depend on two factors: (1) the density of ALS ground hits on the cultural heritage structures being sought, and (2) to what extent these structures stand out from natural terrain structures. The first factor may, to some extent, be improved by using a higher number of ALS pulses per square meter. The second factor is difficult to change, and also highlights another challenge: how to make a general automatic method that is applicable in all types of terrain within a country. The mixed experience with traditional pattern recognition for semi-automatic mapping of cultural heritage led us to consider deep learning as an alternative approach. The main principle is that a general feature detector has been trained on a large image database. The feature detector is then tailored to a specific task by using a modest number of images of true and false examples of the features being sought. Results of using deep learning are compared with previous results using traditional pattern recognition.

A novel visual saliency analysis model based on dynamic multiple feature combination strategy

NASA Astrophysics Data System (ADS)

Lv, Jing; Ye, Qi; Lv, Wen; Zhang, Libao

2017-06-01

The human visual system can quickly focus on a small number of salient objects. This process was known as visual saliency analysis and these salient objects are called focus of attention (FOA). The visual saliency analysis mechanism can be used to extract the salient regions and analyze saliency of object in an image, which is time-saving and can avoid unnecessary costs of computing resources. In this paper, a novel visual saliency analysis model based on dynamic multiple feature combination strategy is introduced. In the proposed model, we first generate multi-scale feature maps of intensity, color and orientation features using Gaussian pyramids and the center-surround difference. Then, we evaluate the contribution of all feature maps to the saliency map according to the area of salient regions and their average intensity, and attach different weights to different features according to their importance. Finally, we choose the largest salient region generated by the region growing method to perform the evaluation. Experimental results show that the proposed model cannot only achieve higher accuracy in saliency map computation compared with other traditional saliency analysis models, but also extract salient regions with arbitrary shapes, which is of great value for the image analysis and understanding.

Task-relevant perceptual features can define categories in visual memory too.

PubMed

Antonelli, Karla B; Williams, Carrick C

2017-11-01

Although Konkle, Brady, Alvarez, and Oliva (2010, Journal of Experimental Psychology: General, 139(3), 558) claim that visual long-term memory (VLTM) is organized on underlying conceptual, not perceptual, information, visual memory results from visual search tasks are not well explained by this theory. We hypothesized that when viewing an object, any task-relevant visual information is critical to the organizational structure of VLTM. In two experiments, we examined the organization of VLTM by measuring the amount of retroactive interference created by objects possessing different combinations of task-relevant features. Based on task instructions, only the conceptual category was task relevant or both the conceptual category and a perceptual object feature were task relevant. Findings indicated that when made task relevant, perceptual object feature information, along with conceptual category information, could affect memory organization for objects in VLTM. However, when perceptual object feature information was task irrelevant, it did not contribute to memory organization; instead, memory defaulted to being organized around conceptual category information. These findings support the theory that a task-defined organizational structure is created in VLTM based on the relevance of particular object features and information.

Collinearity Impairs Local Element Visual Search

ERIC Educational Resources Information Center

Jingling, Li; Tseng, Chia-Huei

2013-01-01

In visual searches, stimuli following the law of good continuity attract attention to the global structure and receive attentional priority. Also, targets that have unique features are of high feature contrast and capture attention in visual search. We report on a salient global structure combined with a high orientation contrast to the…

Interactive Visualization of Assessment Data: The Software Package Mondrian

ERIC Educational Resources Information Center

Unlu, Ali; Sargin, Anatol

2009-01-01

Mondrian is state-of-the-art statistical data visualization software featuring modern interactive visualization techniques for a wide range of data types. This article reviews the capabilities, functionality, and interactive properties of this software package. Key features of Mondrian are illustrated with data from the Programme for International…

Disturbance of visual search by stimulating to posterior parietal cortex in the brain using transcranial magnetic stimulation

NASA Astrophysics Data System (ADS)

Iramina, Keiji; Ge, Sheng; Hyodo, Akira; Hayami, Takehito; Ueno, Shoogo

2009-04-01

In this study, we applied a transcranial magnetic stimulation (TMS) to investigate the temporal aspect for the functional processing of visual attention. Although it has been known that right posterior parietal cortex (PPC) in the brain has a role in certain visual search tasks, there is little knowledge about the temporal aspect of this area. Three visual search tasks that have different difficulties of task execution individually were carried out. These three visual search tasks are the "easy feature task," the "hard feature task," and the "conjunction task." To investigate the temporal aspect of the PPC involved in the visual search, we applied various stimulus onset asynchronies (SOAs) and measured the reaction time of the visual search. The magnetic stimulation was applied on the right PPC or the left PPC by the figure-eight coil. The results show that the reaction times of the hard feature task are longer than those of the easy feature task. When SOA=150 ms, compared with no-TMS condition, there was a significant increase in target-present reaction time when TMS pulses were applied. We considered that the right PPC was involved in the visual search at about SOA=150 ms after visual stimulus presentation. The magnetic stimulation to the right PPC disturbed the processing of the visual search. However, the magnetic stimulation to the left PPC gives no effect on the processing of the visual search.

A signal detection model predicts the effects of set size on visual search accuracy for feature, conjunction, triple conjunction, and disjunction displays

NASA Technical Reports Server (NTRS)

Eckstein, M. P.; Thomas, J. P.; Palmer, J.; Shimozaki, S. S.

2000-01-01

Recently, quantitative models based on signal detection theory have been successfully applied to the prediction of human accuracy in visual search for a target that differs from distractors along a single attribute (feature search). The present paper extends these models for visual search accuracy to multidimensional search displays in which the target differs from the distractors along more than one feature dimension (conjunction, disjunction, and triple conjunction displays). The model assumes that each element in the display elicits a noisy representation for each of the relevant feature dimensions. The observer combines the representations across feature dimensions to obtain a single decision variable, and the stimulus with the maximum value determines the response. The model accurately predicts human experimental data on visual search accuracy in conjunctions and disjunctions of contrast and orientation. The model accounts for performance degradation without resorting to a limited-capacity spatially localized and temporally serial mechanism by which to bind information across feature dimensions.

Decontaminate feature for tracking: adaptive tracking via evolutionary feature subset

NASA Astrophysics Data System (ADS)

Liu, Qiaoyuan; Wang, Yuru; Yin, Minghao; Ren, Jinchang; Li, Ruizhi

2017-11-01

Although various visual tracking algorithms have been proposed in the last 2-3 decades, it remains a challenging problem for effective tracking with fast motion, deformation, occlusion, etc. Under complex tracking conditions, most tracking models are not discriminative and adaptive enough. When the combined feature vectors are inputted to the visual models, this may lead to redundancy causing low efficiency and ambiguity causing poor performance. An effective tracking algorithm is proposed to decontaminate features for each video sequence adaptively, where the visual modeling is treated as an optimization problem from the perspective of evolution. Every feature vector is compared to a biological individual and then decontaminated via classical evolutionary algorithms. With the optimized subsets of features, the "curse of dimensionality" has been avoided while the accuracy of the visual model has been improved. The proposed algorithm has been tested on several publicly available datasets with various tracking challenges and benchmarked with a number of state-of-the-art approaches. The comprehensive experiments have demonstrated the efficacy of the proposed methodology.

Large-Format AlGaN PIN Photodiode Arrays for UV Images

NASA Technical Reports Server (NTRS)

Aslam, Shahid; Franz, David

2010-01-01

A large-format hybridized AlGaN photodiode array with an adjustable bandwidth features stray-light control, ultralow dark-current noise to reduce cooling requirements, and much higher radiation tolerance than previous technologies. This technology reduces the size, mass, power, and cost of future ultraviolet (UV) detection instruments by using lightweight, low-voltage AlGaN detectors in a hybrid detector/multiplexer configuration. The solar-blind feature eliminates the need for additional visible light rejection and reduces the sensitivity of the system to stray light that can contaminate observations.

Perception and Processing of Faces in the Human Brain Is Tuned to Typical Feature Locations

PubMed Central

Schwarzkopf, D. Samuel; Alvarez, Ivan; Lawson, Rebecca P.; Henriksson, Linda; Kriegeskorte, Nikolaus; Rees, Geraint

2016-01-01

Faces are salient social stimuli whose features attract a stereotypical pattern of fixations. The implications of this gaze behavior for perception and brain activity are largely unknown. Here, we characterize and quantify a retinotopic bias implied by typical gaze behavior toward faces, which leads to eyes and mouth appearing most often in the upper and lower visual field, respectively. We found that the adult human visual system is tuned to these contingencies. In two recognition experiments, recognition performance for isolated face parts was better when they were presented at typical, rather than reversed, visual field locations. The recognition cost of reversed locations was equal to ∼60% of that for whole face inversion in the same sample. Similarly, an fMRI experiment showed that patterns of activity evoked by eye and mouth stimuli in the right inferior occipital gyrus could be separated with significantly higher accuracy when these features were presented at typical, rather than reversed, visual field locations. Our findings demonstrate that human face perception is determined not only by the local position of features within a face context, but by whether features appear at the typical retinotopic location given normal gaze behavior. Such location sensitivity may reflect fine-tuning of category-specific visual processing to retinal input statistics. Our findings further suggest that retinotopic heterogeneity might play a role for face inversion effects and for the understanding of conditions affecting gaze behavior toward faces, such as autism spectrum disorders and congenital prosopagnosia. SIGNIFICANCE STATEMENT Faces attract our attention and trigger stereotypical patterns of visual fixations, concentrating on inner features, like eyes and mouth. Here we show that the visual system represents face features better when they are shown at retinal positions where they typically fall during natural vision. When facial features were shown at typical (rather than reversed) visual field locations, they were discriminated better by humans and could be decoded with higher accuracy from brain activity patterns in the right occipital face area. This suggests that brain representations of face features do not cover the visual field uniformly. It may help us understand the well-known face-inversion effect and conditions affecting gaze behavior toward faces, such as prosopagnosia and autism spectrum disorders. PMID:27605606

Dynamic Integration of Task-Relevant Visual Features in Posterior Parietal Cortex

PubMed Central

Freedman, David J.

2014-01-01

Summary The primate visual system consists of multiple hierarchically organized cortical areas, each specialized for processing distinct aspects of the visual scene. For example, color and form are encoded in ventral pathway areas such as V4 and inferior temporal cortex, while motion is preferentially processed in dorsal pathway areas such as the middle temporal area. Such representations often need to be integrated perceptually to solve tasks which depend on multiple features. We tested the hypothesis that the lateral intraparietal area (LIP) integrates disparate task-relevant visual features by recording from LIP neurons in monkeys trained to identify target stimuli composed of conjunctions of color and motion features. We show that LIP neurons exhibit integrative representations of both color and motion features when they are task relevant, and task-dependent shifts of both direction and color tuning. This suggests that LIP plays a role in flexibly integrating task-relevant sensory signals. PMID:25199703

Combined Feature Based and Shape Based Visual Tracker for Robot Navigation

NASA Technical Reports Server (NTRS)

Deans, J.; Kunz, C.; Sargent, R.; Park, E.; Pedersen, L.

2005-01-01

We have developed a combined feature based and shape based visual tracking system designed to enable a planetary rover to visually track and servo to specific points chosen by a user with centimeter precision. The feature based tracker uses invariant feature detection and matching across a stereo pair, as well as matching pairs before and after robot movement in order to compute an incremental 6-DOF motion at each tracker update. This tracking method is subject to drift over time, which can be compensated by the shape based method. The shape based tracking method consists of 3D model registration, which recovers 6-DOF motion given sufficient shape and proper initialization. By integrating complementary algorithms, the combined tracker leverages the efficiency and robustness of feature based methods with the precision and accuracy of model registration. In this paper, we present the algorithms and their integration into a combined visual tracking system.

Visual Working Memory Is Independent of the Cortical Spacing Between Memoranda.

PubMed

Harrison, William J; Bays, Paul M

2018-03-21

The sensory recruitment hypothesis states that visual short-term memory is maintained in the same visual cortical areas that initially encode a stimulus' features. Although it is well established that the distance between features in visual cortex determines their visibility, a limitation known as crowding, it is unknown whether short-term memory is similarly constrained by the cortical spacing of memory items. Here, we investigated whether the cortical spacing between sequentially presented memoranda affects the fidelity of memory in humans (of both sexes). In a first experiment, we varied cortical spacing by taking advantage of the log-scaling of visual cortex with eccentricity, presenting memoranda in peripheral vision sequentially along either the radial or tangential visual axis with respect to the fovea. In a second experiment, we presented memoranda sequentially either within or beyond the critical spacing of visual crowding, a distance within which visual features cannot be perceptually distinguished due to their nearby cortical representations. In both experiments and across multiple measures, we found strong evidence that the ability to maintain visual features in memory is unaffected by cortical spacing. These results indicate that the neural architecture underpinning working memory has properties inconsistent with the known behavior of sensory neurons in visual cortex. Instead, the dissociation between perceptual and memory representations supports a role of higher cortical areas such as posterior parietal or prefrontal regions or may involve an as yet unspecified mechanism in visual cortex in which stimulus features are bound to their temporal order. SIGNIFICANCE STATEMENT Although much is known about the resolution with which we can remember visual objects, the cortical representation of items held in short-term memory remains contentious. A popular hypothesis suggests that memory of visual features is maintained via the recruitment of the same neural architecture in sensory cortex that encodes stimuli. We investigated this claim by manipulating the spacing in visual cortex between sequentially presented memoranda such that some items shared cortical representations more than others while preventing perceptual interference between stimuli. We found clear evidence that short-term memory is independent of the intracortical spacing of memoranda, revealing a dissociation between perceptual and memory representations. Our data indicate that working memory relies on different neural mechanisms from sensory perception. Copyright © 2018 Harrison and Bays.

New light-amplifier-based detector designs for high spatial resolution and high sensitivity CBCT mammography and fluoroscopy

PubMed Central

Rudin, Stephen; Kuhls, Andrew T.; Yadava, Girijesh K.; Josan, Gaurav C.; Wu, Ye; Chityala, Ravishankar N.; Rangwala, Hussain S.; Ciprian Ionita, N.; Hoffmann, Kenneth R.; Bednarek, Daniel R.

2011-01-01

New cone-beam computed tomographic (CBCT) mammography system designs are presented where the detectors provide high spatial resolution, high sensitivity, low noise, wide dynamic range, negligible lag and high frame rates similar to features required for high performance fluoroscopy detectors. The x-ray detectors consist of a phosphor coupled by a fiber-optic taper to either a high gain image light amplifier (LA) then CCD camera or to an electron multiplying CCD. When a square-array of such detectors is used, a field-of-view (FOV) to 20 × 20 cm can be obtained where the images have pixel-resolution of 100 µm or better. To achieve practical CBCT mammography scan-times, 30 fps may be acquired with quantum limited (noise free) performance below 0.2 µR detector exposure per frame. Because of the flexible voltage controlled gain of the LA’s and EMCCDs, large detector dynamic range is also achievable. Features of such detector systems with arrays of either generation 2 (Gen 2) or 3 (Gen 3) LAs optically coupled to CCD cameras or arrays of EMCCDs coupled directly are compared. Quantum accounting analysis is done for a variety of such designs where either the lowest number of information carriers off the LA photo-cathode or electrons released in the EMCCDs per x-ray absorbed in the phosphor are large enough to imply no quantum sink for the design. These new LA- or EMCCD-based systems could lead to vastly improved CBCT mammography, ROI-CT, or fluoroscopy performance compared to systems using flat panels. PMID:21297904

New light-amplifier-based detector designs for high spatial resolution and high sensitivity CBCT mammography and fluoroscopy

NASA Astrophysics Data System (ADS)

Rudin, Stephen; Kuhls, Andrew T.; Yadava, Girijesh K.; Josan, Gaurav C.; Wu, Ye; Chityala, Ravishankar N.; Rangwala, Hussain S.; Ionita, N. Ciprian; Hoffmann, Kenneth R.; Bednarek, Daniel R.

2006-03-01

New cone-beam computed tomographic (CBCT) mammography system designs are presented where the detectors provide high spatial resolution, high sensitivity, low noise, wide dynamic range, negligible lag and high frame rates similar to features required for high performance fluoroscopy detectors. The x-ray detectors consist of a phosphor coupled by a fiber-optic taper to either a high gain image light amplifier (LA) then CCD camera or to an electron multiplying CCD. When a square-array of such detectors is used, a field-of-view (FOV) to 20 x 20 cm can be obtained where the images have pixel-resolution of 100 μm or better. To achieve practical CBCT mammography scan-times, 30 fps may be acquired with quantum limited (noise free) performance below 0.2 μR detector exposure per frame. Because of the flexible voltage controlled gain of the LA's and EMCCDs, large detector dynamic range is also achievable. Features of such detector systems with arrays of either generation 2 (Gen 2) or 3 (Gen 3) LAs optically coupled to CCD cameras or arrays of EMCCDs coupled directly are compared. Quantum accounting analysis is done for a variety of such designs where either the lowest number of information carriers off the LA photo-cathode or electrons released in the EMCCDs per x-ray absorbed in the phosphor are large enough to imply no quantum sink for the design. These new LA- or EMCCD-based systems could lead to vastly improved CBCT mammography, ROI-CT, or fluoroscopy performance compared to systems using flat panels.

Characterization and development of an event-driven hybrid CMOS x-ray detector

NASA Astrophysics Data System (ADS)

Griffith, Christopher

2015-06-01

Hybrid CMOS detectors (HCD) have provided great benefit to the infrared and optical fields of astronomy, and they are poised to do the same for X-ray astronomy. Infrared HCDs have already flown on the Hubble Space Telescope and the Wide-Field Infrared Survey Explorer (WISE) mission and are slated to fly on the James Webb Space Telescope (JWST). Hybrid CMOS X-ray detectors offer low susceptibility to radiation damage, low power consumption, and fast readout time to avoid pile-up. The fast readout time is necessary for future high throughput X-ray missions. The Speedster-EXD X-ray HCD presented in this dissertation offers new in-pixel features and reduces known noise sources seen on previous generation HCDs. The Speedster-EXD detector makes a great step forward in the development of these detectors for future space missions. This dissertation begins with an overview of future X-ray space mission concepts and their detector requirements. The background on the physics of semiconductor devices and an explanation of the detection of X-rays with these devices will be discussed followed by a discussion on CCDs and CMOS detectors. Next, hybrid CMOS X-ray detectors will be explained including their advantages and disadvantages. The Speedster-EXD detector and its new features will be outlined including its ability to only read out pixels which contain X-ray events. Test stand design and construction for the Speedster-EXD detector is outlined and the characterization of each parameter on two Speedster-EXD detectors is detailed including read noise, dark current, interpixel capacitance crosstalk (IPC), and energy resolution. Gain variation is also characterized, and a Monte Carlo simulation of its impact on energy resolution is described. This analysis shows that its effect can be successfully nullified with proper calibration, which would be important for a flight mission. Appendix B contains a study of the extreme tidal disruption event, Swift J1644+57, to search for periodicities in its X-ray light curve. iii.

Detector Design Considerations in High-Dimensional Artificial Immune Systems

DTIC Science & Technology

2012-03-22

a method known as randomized RNS [15]. In this approach, Monte Carlo integration is used to determine the size of self and non-self within the given...feature space, then a number of randomly placed detectors are chosen according to Monte Carlo integration calculations. Simulated annealing is then...detector is only counted once). This value is termed ‘actual content’ because it does not including overlapping content, but only that content that is

Visual feature-tolerance in the reading network.

PubMed

Rauschecker, Andreas M; Bowen, Reno F; Perry, Lee M; Kevan, Alison M; Dougherty, Robert F; Wandell, Brian A

2011-09-08

A century of neurology and neuroscience shows that seeing words depends on ventral occipital-temporal (VOT) circuitry. Typically, reading is learned using high-contrast line-contour words. We explored whether a specific VOT region, the visual word form area (VWFA), learns to see only these words or recognizes words independent of the specific shape-defining visual features. Word forms were created using atypical features (motion-dots, luminance-dots) whose statistical properties control word-visibility. We measured fMRI responses as word form visibility varied, and we used TMS to interfere with neural processing in specific cortical circuits, while subjects performed a lexical decision task. For all features, VWFA responses increased with word-visibility and correlated with performance. TMS applied to motion-specialized area hMT+ disrupted reading performance for motion-dots, but not line-contours or luminance-dots. A quantitative model describes feature-convergence in the VWFA and relates VWFA responses to behavioral performance. These findings suggest how visual feature-tolerance in the reading network arises through signal convergence from feature-specialized cortical areas. Copyright © 2011 Elsevier Inc. All rights reserved.

Life Finder Detectors: An Overview of Detector Technologies for Detecting Life on Other Worlds

NASA Astrophysics Data System (ADS)

Rauscher, Bernard J.; Domagal-Goldman, Shawn; Greenhouse, Matthew A.; Hsieh, Wen-Ting; McElwain, Michael W.; Moseley, Samuel H.; Noroozian, Omid; Norton, Tim; Kutyrev, Alexander; Rinehart, Stephen; stock, Joseph

2015-01-01

Future large space telescopes will seek evidence for life on other worlds by searching for spectroscopic biosignatures. Atmospheric biosignature gases include oxygen, ozone, water vapor, and methane. Non-biological gases, including carbon monoxide and carbon dioxide, are important for discriminating false positives. All of these gases imprint spectroscopic features in the UV through mid-IR that are potentially detectable using future space based coronagraphs or star shades for starlight suppression.Direct spectroscopic biosignature detection requires sensors capable of robustly measuring photon arrival rates on the order of 10 per resolution element per hour. Photon counting is required for some wavefront sensing and control approaches to achieve the requisite high contrast ratios. We review life finder detector technologies that either exist today, or are under development, that have the potential to meet these challenging requirements. We specifically highlight areas where more work or development is needed.Life finder detectors will be invaluable for a wide variety of other major science programs. Because of its cross cutting nature; UV, optical, and infrared (UVOIR) detector development features prominently in the 2010 National Research Council Decadal Survey, 'New Worlds, New Horizons in Astronomy and Astrophysics', and the NASA Cosmic Origins Program Technology Roadmap.

Recent results in visual servoing

NASA Astrophysics Data System (ADS)

Chaumette, François

2008-06-01

Visual servoing techniques consist in using the data provided by a vision sensor in order to control the motions of a dynamic system. Such systems are usually robot arms, mobile robots, aerial robots,… but can also be virtual robots for applications in computer animation, or even a virtual camera for applications in computer vision and augmented reality. A large variety of positioning tasks, or mobile target tracking, can be implemented by controlling from one to all the degrees of freedom of the system. Whatever the sensor configuration, which can vary from one on-board camera on the robot end-effector to several free-standing cameras, a set of visual features has to be selected at best from the image measurements available, allowing to control the degrees of freedom desired. A control law has also to be designed so that these visual features reach a desired value, defining a correct realization of the task. With a vision sensor providing 2D measurements, potential visual features are numerous, since as well 2D data (coordinates of feature points in the image, moments, …) as 3D data provided by a localization algorithm exploiting the extracted 2D measurements can be considered. It is also possible to combine 2D and 3D visual features to take the advantages of each approach while avoiding their respective drawbacks. From the selected visual features, the behavior of the system will have particular properties as for stability, robustness with respect to noise or to calibration errors, robot 3D trajectory, etc. The talk will present the main basic aspects of visual servoing, as well as technical advances obtained recently in the field inside the Lagadic group at INRIA/INRISA Rennes. Several application results will be also described.

Automated scanning of plastic nuclear track detectors using the Minnesota star scanner

NASA Technical Reports Server (NTRS)

Fink, P. J.; Waddington, C. J.

1986-01-01

The problems found in an attempt to adapt an automated scanner of astronomical plates, the Minnesota Automated Dual Plate Scanner (APS), to locating and measuring the etch pits produced by ionizing particles in plastic nuclear track detectors (CR-39) are described. A visual study of these pits was made to determine the errors introduced in determining positions and shapes. Measurements made under a low power microscope were compared with those from the APS.

ST Spot Detector: a web-based application for automatic spot and tissue detection for spatial Transcriptomics image datasets.

PubMed

Wong, Kim; Navarro, José Fernández; Bergenstråhle, Ludvig; Ståhl, Patrik L; Lundeberg, Joakim

2018-06-01

Spatial Transcriptomics (ST) is a method which combines high resolution tissue imaging with high troughput transcriptome sequencing data. This data must be aligned with the images for correct visualization, a process that involves several manual steps. Here we present ST Spot Detector, a web tool that automates and facilitates this alignment through a user friendly interface. jose.fernandez.navarro@scilifelab.se. Supplementary data are available at Bioinformatics online.

Associative learning in baboons (Papio papio) and humans (Homo sapiens): species differences in learned attention to visual features.

PubMed

Fagot, J; Kruschke, J K; Dépy, D; Vauclair, J

1998-10-01

We examined attention shifting in baboons and humans during the learning of visual categories. Within a conditional matching-to-sample task, participants of the two species sequentially learned two two-feature categories which shared a common feature. Results showed that humans encoded both features of the initially learned category, but predominantly only the distinctive feature of the subsequently learned category. Although baboons initially encoded both features of the first category, they ultimately retained only the distinctive features of each category. Empirical data from the two species were analyzed with the 1996 ADIT connectionist model of Kruschke. ADIT fits the baboon data when the attentional shift rate is zero, and the human data when the attentional shift rate is not zero. These empirical and modeling results suggest species differences in learned attention to visual features.

Local motion adaptation enhances the representation of spatial structure at EMD arrays

PubMed Central

Lindemann, Jens P.; Egelhaaf, Martin

2017-01-01

Neuronal representation and extraction of spatial information are essential for behavioral control. For flying insects, a plausible way to gain spatial information is to exploit distance-dependent optic flow that is generated during translational self-motion. Optic flow is computed by arrays of local motion detectors retinotopically arranged in the second neuropile layer of the insect visual system. These motion detectors have adaptive response characteristics, i.e. their responses to motion with a constant or only slowly changing velocity decrease, while their sensitivity to rapid velocity changes is maintained or even increases. We analyzed by a modeling approach how motion adaptation affects signal representation at the output of arrays of motion detectors during simulated flight in artificial and natural 3D environments. We focused on translational flight, because spatial information is only contained in the optic flow induced by translational locomotion. Indeed, flies, bees and other insects segregate their flight into relatively long intersaccadic translational flight sections interspersed with brief and rapid saccadic turns, presumably to maximize periods of translation (80% of the flight). With a novel adaptive model of the insect visual motion pathway we could show that the motion detector responses to background structures of cluttered environments are largely attenuated as a consequence of motion adaptation, while responses to foreground objects stay constant or even increase. This conclusion even holds under the dynamic flight conditions of insects. PMID:29281631

Asymmetries in visual search for conjunctive targets.

PubMed

Cohen, A

1993-08-01

Asymmetry is demonstrated between conjunctive targets in visual search with no detectable asymmetries between the individual features that compose these targets. Experiment 1 demonstrated this phenomenon for targets composed of color and shape. Experiment 2 and 4 demonstrate this asymmetry for targets composed of size and orientation and for targets composed of contrast level and orientation, respectively. Experiment 3 demonstrates that search rate of individual features cannot predict search rate for conjunctive targets. These results demonstrate the need for 2 levels of representations: one of features and one of conjunction of features. A model related to the modified feature integration theory is proposed to account for these results. The proposed model and other models of visual search are discussed.

Red to Green or Fast to Slow? Infants' Visual Working Memory for "Just Salient Differences"

ERIC Educational Resources Information Center

Kaldy, Zsuzsa; Blaser, Erik

2013-01-01

In this study, 6-month-old infants' visual working memory for a static feature (color) and a dynamic feature (rotational motion) was compared. Comparing infants' use of different features can only be done properly if experimental manipulations to those features are equally salient (Kaldy & Blaser, 2009; Kaldy, Blaser, & Leslie,…

Implicit integration in a case of integrative visual agnosia.

PubMed

Aviezer, Hillel; Landau, Ayelet N; Robertson, Lynn C; Peterson, Mary A; Soroker, Nachum; Sacher, Yaron; Bonneh, Yoram; Bentin, Shlomo

2007-05-15

We present a case (SE) with integrative visual agnosia following ischemic stroke affecting the right dorsal and the left ventral pathways of the visual system. Despite his inability to identify global hierarchical letters [Navon, D. (1977). Forest before trees: The precedence of global features in visual perception. Cognitive Psychology, 9, 353-383], and his dense object agnosia, SE showed normal global-to-local interference when responding to local letters in Navon hierarchical stimuli and significant picture-word identity priming in a semantic decision task for words. Since priming was absent if these features were scrambled, it stands to reason that these effects were not due to priming by distinctive features. The contrast between priming effects induced by coherent and scrambled stimuli is consistent with implicit but not explicit integration of features into a unified whole. We went on to show that possible/impossible object decisions were facilitated by words in a word-picture priming task, suggesting that prompts could activate perceptually integrated images in a backward fashion. We conclude that the absence of SE's ability to identify visual objects except through tedious serial construction reflects a deficit in accessing an integrated visual representation through bottom-up visual processing alone. However, top-down generated images can help activate these visual representations through semantic links.

A multi-level anomaly detection algorithm for time-varying graph data with interactive visualization

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

Bridges, Robert A.; Collins, John P.; Ferragut, Erik M.

This work presents a novel modeling and analysis framework for graph sequences which addresses the challenge of detecting and contextualizing anomalies in labelled, streaming graph data. We introduce a generalization of the BTER model of Seshadhri et al. by adding flexibility to community structure, and use this model to perform multi-scale graph anomaly detection. Specifically, probability models describing coarse subgraphs are built by aggregating node probabilities, and these related hierarchical models simultaneously detect deviations from expectation. This technique provides insight into a graph's structure and internal context that may shed light on a detected event. Additionally, this multi-scale analysis facilitatesmore » intuitive visualizations by allowing users to narrow focus from an anomalous graph to particular subgraphs or nodes causing the anomaly. For evaluation, two hierarchical anomaly detectors are tested against a baseline Gaussian method on a series of sampled graphs. We demonstrate that our graph statistics-based approach outperforms both a distribution-based detector and the baseline in a labeled setting with community structure, and it accurately detects anomalies in synthetic and real-world datasets at the node, subgraph, and graph levels. Furthermore, to illustrate the accessibility of information made possible via this technique, the anomaly detector and an associated interactive visualization tool are tested on NCAA football data, where teams and conferences that moved within the league are identified with perfect recall, and precision greater than 0.786.« less

Development of a small prototype for a proof-of-concept of OpenPET imaging

NASA Astrophysics Data System (ADS)

Yamaya, Taiga; Yoshida, Eiji; Inaniwa, Taku; Sato, Shinji; Nakajima, Yasunori; Wakizaka, Hidekatsu; Kokuryo, Daisuke; Tsuji, Atsushi; Mitsuhashi, Takayuki; Kawai, Hideyuki; Tashima, Hideaki; Nishikido, Fumihiko; Inadama, Naoko; Murayama, Hideo; Haneishi, Hideaki; Suga, Mikio; Kinouchi, Shoko

2011-02-01

The OpenPET geometry is our new idea to visualize a physically opened space between two detector rings. In this paper, we developed the first small prototype to show a proof-of-concept of OpenPET imaging. Two detector rings of 110 mm diameter and 42 mm axial length were placed with a gap of 42 mm. The basic imaging performance was confirmed through phantom studies; the open imaging was realized at the cost of slight loss of axial resolution and 24% loss of sensitivity. For a proof-of-concept of PET image-guided radiation therapy, we carried out the in-beam tests with 11C radioactive beam irradiation in the heavy ion medical accelerator in Chiba to visualize in situ distribution of primary particles stopped in a phantom. We showed that PET images corresponding to dose distribution were obtained. For an initial proof-of-concept of real-time multimodal imaging, we measured a tumor-inoculated mouse with 18F-FDG, and an optical image of the mouse body surface was taken during the PET measurement by inserting a digital camera in the ring gap. We confirmed that the tumor in the gap was clearly visualized. The result also showed the extension effect of an axial field-of-view (FOV); a large axial FOV of 126 mm was obtained with the detectors that originally covered only an 84 mm axial FOV. In conclusion, our initial imaging studies showed promising performance of the OpenPET.

A multi-level anomaly detection algorithm for time-varying graph data with interactive visualization

DOE PAGES

Bridges, Robert A.; Collins, John P.; Ferragut, Erik M.; ...

2016-01-01

This work presents a novel modeling and analysis framework for graph sequences which addresses the challenge of detecting and contextualizing anomalies in labelled, streaming graph data. We introduce a generalization of the BTER model of Seshadhri et al. by adding flexibility to community structure, and use this model to perform multi-scale graph anomaly detection. Specifically, probability models describing coarse subgraphs are built by aggregating node probabilities, and these related hierarchical models simultaneously detect deviations from expectation. This technique provides insight into a graph's structure and internal context that may shed light on a detected event. Additionally, this multi-scale analysis facilitatesmore » intuitive visualizations by allowing users to narrow focus from an anomalous graph to particular subgraphs or nodes causing the anomaly. For evaluation, two hierarchical anomaly detectors are tested against a baseline Gaussian method on a series of sampled graphs. We demonstrate that our graph statistics-based approach outperforms both a distribution-based detector and the baseline in a labeled setting with community structure, and it accurately detects anomalies in synthetic and real-world datasets at the node, subgraph, and graph levels. Furthermore, to illustrate the accessibility of information made possible via this technique, the anomaly detector and an associated interactive visualization tool are tested on NCAA football data, where teams and conferences that moved within the league are identified with perfect recall, and precision greater than 0.786.« less

Topic Transition in Educational Videos Using Visually Salient Words

ERIC Educational Resources Information Center

Gandhi, Ankit; Biswas, Arijit; Deshmukh, Om

2015-01-01

In this paper, we propose a visual saliency algorithm for automatically finding the topic transition points in an educational video. First, we propose a method for assigning a saliency score to each word extracted from an educational video. We design several mid-level features that are indicative of visual saliency. The optimal feature combination…

Visual word ambiguity.

PubMed

van Gemert, Jan C; Veenman, Cor J; Smeulders, Arnold W M; Geusebroek, Jan-Mark

2010-07-01

This paper studies automatic image classification by modeling soft assignment in the popular codebook model. The codebook model describes an image as a bag of discrete visual words selected from a vocabulary, where the frequency distributions of visual words in an image allow classification. One inherent component of the codebook model is the assignment of discrete visual words to continuous image features. Despite the clear mismatch of this hard assignment with the nature of continuous features, the approach has been successfully applied for some years. In this paper, we investigate four types of soft assignment of visual words to image features. We demonstrate that explicitly modeling visual word assignment ambiguity improves classification performance compared to the hard assignment of the traditional codebook model. The traditional codebook model is compared against our method for five well-known data sets: 15 natural scenes, Caltech-101, Caltech-256, and Pascal VOC 2007/2008. We demonstrate that large codebook vocabulary sizes completely deteriorate the performance of the traditional model, whereas the proposed model performs consistently. Moreover, we show that our method profits in high-dimensional feature spaces and reaps higher benefits when increasing the number of image categories.

Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features.

PubMed

Li, Linyi; Xu, Tingbao; Chen, Yun

2017-01-01

In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF) was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images.

Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features

PubMed Central

Xu, Tingbao; Chen, Yun

2017-01-01

In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF) was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images. PMID:28761440

Threat as a feature in visual semantic object memory.

PubMed

Calley, Clifford S; Motes, Michael A; Chiang, H-Sheng; Buhl, Virginia; Spence, Jeffrey S; Abdi, Hervé; Anand, Raksha; Maguire, Mandy; Estevez, Leonardo; Briggs, Richard; Freeman, Thomas; Kraut, Michael A; Hart, John

2013-08-01

Threatening stimuli have been found to modulate visual processes related to perception and attention. The present functional magnetic resonance imaging (fMRI) study investigated whether threat modulates visual object recognition of man-made and naturally occurring categories of stimuli. Compared with nonthreatening pictures, threatening pictures of real items elicited larger fMRI BOLD signal changes in medial visual cortices extending inferiorly into the temporo-occipital (TO) "what" pathways. This region elicited greater signal changes for threatening items compared to nonthreatening from both the natural-occurring and man-made stimulus supraordinate categories, demonstrating a featural component to these visual processing areas. Two additional loci of signal changes within more lateral inferior TO areas (bilateral BA18 and 19 as well as the right ventral temporal lobe) were detected for a category-feature interaction, with stronger responses to man-made (category) threatening (feature) stimuli than to natural threats. The findings are discussed in terms of visual recognition of processing efficiently or rapidly groups of items that confer an advantage for survival. Copyright © 2012 Wiley Periodicals, Inc.

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

Berres, Anne Sabine

This slide presentation describes basic topological concepts, including topological spaces, homeomorphisms, homotopy, betti numbers. Scalar field topology explores finding topological features and scalar field visualization, and vector field topology explores finding topological features and vector field visualization.

Energy dependent features of X-ray signals in a GridPix detector

NASA Astrophysics Data System (ADS)

Krieger, C.; Kaminski, J.; Vafeiadis, T.; Desch, K.

2018-06-01

We report on the calibration of an argon/isobutane (97.7%/2.3%)-filled GridPix detector with soft X-rays (277 eV to 8 keV) using the variable energy X-ray source of the CAST Detector Lab at CERN. We study the linearity and energy resolution of the detector using both the number of pixels hit and the total measured charge as energy measures. For the latter, the energy resolution σE / E is better than 10% (20%) for energies above 2 keV (0.5 keV). Several characteristics of the recorded events are studied.

Multi-spectral black meta-infrared detectors (Conference Presentation)

NASA Astrophysics Data System (ADS)

Krishna, Sanjay

2016-09-01

There is an increased emphasis on obtaining imaging systems with on-demand spectro-polarimetric information at the pixel level. Meta-infrared detectors in which infrared detectors are combined with metamaterials are a promising way to realize this. The infrared region is appealing due to the low metallic loss, large penetration depth of the localized field and the larger feature sizes compared to the visible region. I will discuss approaches to realize multispectral detectors including our recent work on double metal meta-material design combined with Type II superlattices that have demonstrated enhanced quantum efficiency (collaboration with Padilla group at Duke University).

Exploration of complex visual feature spaces for object perception

PubMed Central

Leeds, Daniel D.; Pyles, John A.; Tarr, Michael J.

2014-01-01

The mid- and high-level visual properties supporting object perception in the ventral visual pathway are poorly understood. In the absence of well-specified theory, many groups have adopted a data-driven approach in which they progressively interrogate neural units to establish each unit's selectivity. Such methods are challenging in that they require search through a wide space of feature models and stimuli using a limited number of samples. To more rapidly identify higher-level features underlying human cortical object perception, we implemented a novel functional magnetic resonance imaging method in which visual stimuli are selected in real-time based on BOLD responses to recently shown stimuli. This work was inspired by earlier primate physiology work, in which neural selectivity for mid-level features in IT was characterized using a simple parametric approach (Hung et al., 2012). To extend such work to human neuroimaging, we used natural and synthetic object stimuli embedded in feature spaces constructed on the basis of the complex visual properties of the objects themselves. During fMRI scanning, we employed a real-time search method to control continuous stimulus selection within each image space. This search was designed to maximize neural responses across a pre-determined 1 cm3 brain region within ventral cortex. To assess the value of this method for understanding object encoding, we examined both the behavior of the method itself and the complex visual properties the method identified as reliably activating selected brain regions. We observed: (1) Regions selective for both holistic and component object features and for a variety of surface properties; (2) Object stimulus pairs near one another in feature space that produce responses at the opposite extremes of the measured activity range. Together, these results suggest that real-time fMRI methods may yield more widely informative measures of selectivity within the broad classes of visual features associated with cortical object representation. PMID:25309408

Properties of V1 Neurons Tuned to Conjunctions of Visual Features: Application of the V1 Saliency Hypothesis to Visual Search behavior

PubMed Central

Zhaoping, Li; Zhe, Li

2012-01-01

From a computational theory of V1, we formulate an optimization problem to investigate neural properties in the primary visual cortex (V1) from human reaction times (RTs) in visual search. The theory is the V1 saliency hypothesis that the bottom-up saliency of any visual location is represented by the highest V1 response to it relative to the background responses. The neural properties probed are those associated with the less known V1 neurons tuned simultaneously or conjunctively in two feature dimensions. The visual search is to find a target bar unique in color (C), orientation (O), motion direction (M), or redundantly in combinations of these features (e.g., CO, MO, or CM) among uniform background bars. A feature singleton target is salient because its evoked V1 response largely escapes the iso-feature suppression on responses to the background bars. The responses of the conjunctively tuned cells are manifested in the shortening of the RT for a redundant feature target (e.g., a CO target) from that predicted by a race between the RTs for the two corresponding single feature targets (e.g., C and O targets). Our investigation enables the following testable predictions. Contextual suppression on the response of a CO-tuned or MO-tuned conjunctive cell is weaker when the contextual inputs differ from the direct inputs in both feature dimensions, rather than just one. Additionally, CO-tuned cells and MO-tuned cells are often more active than the single feature tuned cells in response to the redundant feature targets, and this occurs more frequently for the MO-tuned cells such that the MO-tuned cells are no less likely than either the M-tuned or O-tuned neurons to be the most responsive neuron to dictate saliency for an MO target. PMID:22719829

Properties of V1 neurons tuned to conjunctions of visual features: application of the V1 saliency hypothesis to visual search behavior.

PubMed

Zhaoping, Li; Zhe, Li

2012-01-01

From a computational theory of V1, we formulate an optimization problem to investigate neural properties in the primary visual cortex (V1) from human reaction times (RTs) in visual search. The theory is the V1 saliency hypothesis that the bottom-up saliency of any visual location is represented by the highest V1 response to it relative to the background responses. The neural properties probed are those associated with the less known V1 neurons tuned simultaneously or conjunctively in two feature dimensions. The visual search is to find a target bar unique in color (C), orientation (O), motion direction (M), or redundantly in combinations of these features (e.g., CO, MO, or CM) among uniform background bars. A feature singleton target is salient because its evoked V1 response largely escapes the iso-feature suppression on responses to the background bars. The responses of the conjunctively tuned cells are manifested in the shortening of the RT for a redundant feature target (e.g., a CO target) from that predicted by a race between the RTs for the two corresponding single feature targets (e.g., C and O targets). Our investigation enables the following testable predictions. Contextual suppression on the response of a CO-tuned or MO-tuned conjunctive cell is weaker when the contextual inputs differ from the direct inputs in both feature dimensions, rather than just one. Additionally, CO-tuned cells and MO-tuned cells are often more active than the single feature tuned cells in response to the redundant feature targets, and this occurs more frequently for the MO-tuned cells such that the MO-tuned cells are no less likely than either the M-tuned or O-tuned neurons to be the most responsive neuron to dictate saliency for an MO target.

The PHOBOS detector at RHIC

NASA Astrophysics Data System (ADS)

Back, B. B.; Baker, M. D.; Barton, D. S.; Basilev, S.; Baum, R.; Betts, R. R.; Białas, A.; Bindel, R.; Bogucki, W.; Budzanowski, A.; Busza, W.; Carroll, A.; Ceglia, M.; Chang, Y.-H.; Chen, A. E.; Coghen, T.; Connor, C.; Czyż, W.; Dabrowski, B.; Decowski, M. P.; Despet, M.; Fita, P.; Fitch, J.; Friedl, M.; Gałuszka, K.; Ganz, R.; Garcia, E.; George, N.; Godlewski, J.; Gomes, C.; Griesmayer, E.; Gulbrandsen, K.; Gushue, S.; Halik, J.; Halliwell, C.; Haridas, P.; Hayes, A.; Heintzelman, G. A.; Henderson, C.; Hollis, R.; Hołyński, R.; Hofman, D.; Holzman, B.; Johnson, E.; Kane, J.; Katzy, J.; Kita, W.; Kotuła, J.; Kraner, H.; Kucewicz, W.; Kulinich, P.; Law, C.; Lemler, M.; Ligocki, J.; Lin, W. T.; Manly, S.; McLeod, D.; Michałowski, J.; Mignerey, A.; Mülmenstädt, J.; Neal, M.; Nouicer, R.; Olszewski, A.; Pak, R.; Park, I. C.; Patel, M.; Pernegger, H.; Plesko, M.; Reed, C.; Remsberg, L. P.; Reuter, M.; Roland, C.; Roland, G.; Ross, D.; Rosenberg, L.; Ryan, J.; Sanzgiri, A.; Sarin, P.; Sawicki, P.; Scaduto, J.; Shea, J.; Sinacore, J.; Skulski, W.; Steadman, S. G.; Stephans, G. S. F.; Steinberg, P.; Straczek, A.; Stodulski, M.; Strek, M.; Stopa, Z.; Sukhanov, A.; Surowiecka, K.; Tang, J.-L.; Teng, R.; Trzupek, A.; Vale, C.; van Nieuwenhuizen, G. J.; Verdier, R.; Wadsworth, B.; Wolfs, F. L. H.; Wosiek, B.; Woźniak, K.; Wuosmaa, A. H.; Wysłouch, B.; Zalewski, K.; Żychowski, P.; Phobos Collaboration

2003-03-01

This manuscript contains a detailed description of the PHOBOS experiment as it is configured for the Year 2001 running period. It is capable of detecting charged particles over the full solid angle using a multiplicity detector and measuring identified charged particles near mid-rapidity in two spectrometer arms with opposite magnetic fields. Both of these components utilize silicon pad detectors for charged particle detection. The minimization of material between the collision vertex and the first layers of silicon detectors allows for the detection of charged particles with very low transverse momenta, which is a unique feature of the PHOBOS experiment. Additional detectors include a time-of-flight wall which extends the particle identification range for one spectrometer arm, as well as sets of scintillator paddle and Cherenkov detector arrays for event triggering and centrality selection.

Visualization of Oxidative Stress Induced by Experimental Periodontitis in Keap1-Dependent Oxidative Stress Detector-Luciferase Mice.

PubMed

Kataoka, Kota; Ekuni, Daisuke; Tomofuji, Takaaki; Irie, Koichiro; Kunitomo, Muneyoshi; Uchida, Yoko; Fukuhara, Daiki; Morita, Manabu

2016-11-16

The aim of this study was to investigate whether a Keap1-dependent oxidative stress detector-luciferase (OKD-LUC) mouse model would be useful for the visualization of oxidative stress induced by experimental periodontitis. A ligature was placed around the mandibular first molars for seven days to induce periodontitis. Luciferase activity was measured with an intraperitoneal injection of d-luciferin on days 0, 1, and 7. The luciferase activity in the periodontitis group was significantly greater than that in the control group at seven days. The expressions of heme oxygenase-1 (HO-1) and malondialdehyde in periodontal tissue were significantly higher in the periodontitis group than in the control group. Immunofluorescent analysis confirmed that the nuclear translocation of nuclear factor erythroid 2-related factor 2 (Nrf2) occurred more frequently in the periodontitis group than in the control group. This study found that under oxidative stress induced by experimental periodontitis, the Nrf2/antioxidant defense pathway was activated and could be visualized from the luciferase activity in the OKD-LUC model. Thus, the OKD-LUC mouse model may be useful for exploring the mechanism underlying the relationship between the Nrf2/antioxidant defense pathway and periodontitis by enabling the visualization of oxidative stress over time.

Sensory processing and world modeling for an active ranging device

NASA Technical Reports Server (NTRS)

Hong, Tsai-Hong; Wu, Angela Y.

1991-01-01

In this project, we studied world modeling and sensory processing for laser range data. World Model data representation and operation were defined. Sensory processing algorithms for point processing and linear feature detection were designed and implemented. The interface between world modeling and sensory processing in the Servo and Primitive levels was investigated and implemented. In the primitive level, linear features detectors for edges were also implemented, analyzed and compared. The existing world model representations is surveyed. Also presented is the design and implementation of the Y-frame model, a hierarchical world model. The interfaces between the world model module and the sensory processing module are discussed as well as the linear feature detectors that were designed and implemented.

New apparatus of single particle trap system for aerosol visualization

NASA Astrophysics Data System (ADS)

Higashi, Hidenori; Fujioka, Tomomi; Endo, Tetsuo; Kitayama, Chiho; Seto, Takafumi; Otani, Yoshio

2014-08-01

Control of transport and deposition of charged aerosol particles is important in various manufacturing processes. Aerosol visualization is an effective method to directly observe light scattering signal from laser-irradiated single aerosol particle trapped in a visualization cell. New single particle trap system triggered by light scattering pulse signal was developed in this study. The performance of the device was evaluated experimentally. Experimental setup consisted of an aerosol generator, a differential mobility analyzer (DMA), an optical particle counter (OPC) and the single particle trap system. Polystylene latex standard (PSL) particles (0.5, 1.0 and 2.0 μm) were generated and classified according to the charge by the DMA. Singly charged 0.5 and 1.0 μm particles and doubly charged 2.0 μm particles were used as test particles. The single particle trap system was composed of a light scattering signal detector and a visualization cell. When the particle passed through the detector, trigger signal with a given delay time sent to the solenoid valves upstream and downstream of the visualization cell for trapping the particle in the visualization cell. The motion of particle in the visualization cell was monitored by CCD camera and the gravitational settling velocity and the electrostatic migration velocity were measured from the video image. The aerodynamic diameter obtained from the settling velocity was in good agreement with Stokes diameter calculated from the electrostatic migration velocity for individual particles. It was also found that the aerodynamic diameter obtained from the settling velocity was a one-to-one function of the scattered light intensity of individual particles. The applicability of this system will be discussed.

Specific excitatory connectivity for feature integration in mouse primary visual cortex

PubMed Central

Molina-Luna, Patricia; Roth, Morgane M.

2017-01-01

Local excitatory connections in mouse primary visual cortex (V1) are stronger and more prevalent between neurons that share similar functional response features. However, the details of how functional rules for local connectivity shape neuronal responses in V1 remain unknown. We hypothesised that complex responses to visual stimuli may arise as a consequence of rules for selective excitatory connectivity within the local network in the superficial layers of mouse V1. In mouse V1 many neurons respond to overlapping grating stimuli (plaid stimuli) with highly selective and facilitatory responses, which are not simply predicted by responses to single gratings presented alone. This complexity is surprising, since excitatory neurons in V1 are considered to be mainly tuned to single preferred orientations. Here we examined the consequences for visual processing of two alternative connectivity schemes: in the first case, local connections are aligned with visual properties inherited from feedforward input (a ‘like-to-like’ scheme specifically connecting neurons that share similar preferred orientations); in the second case, local connections group neurons into excitatory subnetworks that combine and amplify multiple feedforward visual properties (a ‘feature binding’ scheme). By comparing predictions from large scale computational models with in vivo recordings of visual representations in mouse V1, we found that responses to plaid stimuli were best explained by assuming feature binding connectivity. Unlike under the like-to-like scheme, selective amplification within feature-binding excitatory subnetworks replicated experimentally observed facilitatory responses to plaid stimuli; explained selective plaid responses not predicted by grating selectivity; and was consistent with broad anatomical selectivity observed in mouse V1. Our results show that visual feature binding can occur through local recurrent mechanisms without requiring feedforward convergence, and that such a mechanism is consistent with visual responses and cortical anatomy in mouse V1. PMID:29240769

Study of Viability and Challenges of using SiPMs as an Alternative to PMT’s in Scintillation Detectors for Nuclear Safeguards

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

Iliev, Metodi

The goals of this project are to identify fundamental and practical problems and features with SiPMs as they relate to IAEA detector needs, Identify published results and implementations of scintillation detectors tat use SiPMs that are of interest to IAEA, asses how effectively the fundamental problems were addresses, and perform simulations and experiments as needed to reproduce crucial results and make recommendations.

The hyperion particle-γ detector array

DOE PAGES

Hughes, R. O.; Burke, J. T.; Casperson, R. J.; ...

2017-03-08

Hyperion is a new high-efficiency charged-particle γ-ray detector array which consists of a segmented silicon telescope for charged-particle detection and up to fourteen high-purity germanium clover detectors for the detection of coincident γ rays. The array will be used in nuclear physics measurements and Stockpile Stewardship studies and replaces the STARLiTeR array. In conclusion, this article discusses the features of the array and presents data collected with the array in the commissioning experiment.

Improving the accuracy in detection of clustered microcalcifications with a context-sensitive classification model.

PubMed

Wang, Juan; Nishikawa, Robert M; Yang, Yongyi

2016-01-01

In computer-aided detection of microcalcifications (MCs), the detection accuracy is often compromised by frequent occurrence of false positives (FPs), which can be attributed to a number of factors, including imaging noise, inhomogeneity in tissue background, linear structures, and artifacts in mammograms. In this study, the authors investigated a unified classification approach for combating the adverse effects of these heterogeneous factors for accurate MC detection. To accommodate FPs caused by different factors in a mammogram image, the authors developed a classification model to which the input features were adapted according to the image context at a detection location. For this purpose, the input features were defined in two groups, of which one group was derived from the image intensity pattern in a local neighborhood of a detection location, and the other group was used to characterize how a MC is different from its structural background. Owing to the distinctive effect of linear structures in the detector response, the authors introduced a dummy variable into the unified classifier model, which allowed the input features to be adapted according to the image context at a detection location (i.e., presence or absence of linear structures). To suppress the effect of inhomogeneity in tissue background, the input features were extracted from different domains aimed for enhancing MCs in a mammogram image. To demonstrate the flexibility of the proposed approach, the authors implemented the unified classifier model by two widely used machine learning algorithms, namely, a support vector machine (SVM) classifier and an Adaboost classifier. In the experiment, the proposed approach was tested for two representative MC detectors in the literature [difference-of-Gaussians (DoG) detector and SVM detector]. The detection performance was assessed using free-response receiver operating characteristic (FROC) analysis on a set of 141 screen-film mammogram (SFM) images (66 cases) and a set of 188 full-field digital mammogram (FFDM) images (95 cases). The FROC analysis results show that the proposed unified classification approach can significantly improve the detection accuracy of two MC detectors on both SFM and FFDM images. Despite the difference in performance between the two detectors, the unified classifiers can reduce their FP rate to a similar level in the output of the two detectors. In particular, with true-positive rate at 85%, the FP rate on SFM images for the DoG detector was reduced from 1.16 to 0.33 clusters/image (unified SVM) and 0.36 clusters/image (unified Adaboost), respectively; similarly, for the SVM detector, the FP rate was reduced from 0.45 clusters/image to 0.30 clusters/image (unified SVM) and 0.25 clusters/image (unified Adaboost), respectively. Similar FP reduction results were also achieved on FFDM images for the two MC detectors. The proposed unified classification approach can be effective for discriminating MCs from FPs caused by different factors (such as MC-like noise patterns and linear structures) in MC detection. The framework is general and can be applicable for further improving the detection accuracy of existing MC detectors.

Modulation of neuronal responses during covert search for visual feature conjunctions

PubMed Central

Buracas, Giedrius T.; Albright, Thomas D.

2009-01-01

While searching for an object in a visual scene, an observer's attentional focus and eye movements are often guided by information about object features and spatial locations. Both spatial and feature-specific attention are known to modulate neuronal responses in visual cortex, but little is known of the dynamics and interplay of these mechanisms as visual search progresses. To address this issue, we recorded from directionally selective cells in visual area MT of monkeys trained to covertly search for targets defined by a unique conjunction of color and motion features and to signal target detection with an eye movement to the putative target. Two patterns of response modulation were observed. One pattern consisted of enhanced responses to targets presented in the receptive field (RF). These modulations occurred at the end-stage of search and were more potent during correct target identification than during erroneous saccades to a distractor in RF, thus suggesting that this modulation is not a mere presaccadic enhancement. A second pattern of modulation was observed when RF stimuli were nontargets that shared a feature with the target. The latter effect was observed during early stages of search and is consistent with a global feature-specific mechanism. This effect often terminated before target identification, thus suggesting that it interacts with spatial attention. This modulation was exhibited not only for motion but also for color cue, although MT neurons are known to be insensitive to color. Such cue-invariant attentional effects may contribute to a feature binding mechanism acting across visual dimensions. PMID:19805385

Modulation of neuronal responses during covert search for visual feature conjunctions.

PubMed

Buracas, Giedrius T; Albright, Thomas D

2009-09-29

While searching for an object in a visual scene, an observer's attentional focus and eye movements are often guided by information about object features and spatial locations. Both spatial and feature-specific attention are known to modulate neuronal responses in visual cortex, but little is known of the dynamics and interplay of these mechanisms as visual search progresses. To address this issue, we recorded from directionally selective cells in visual area MT of monkeys trained to covertly search for targets defined by a unique conjunction of color and motion features and to signal target detection with an eye movement to the putative target. Two patterns of response modulation were observed. One pattern consisted of enhanced responses to targets presented in the receptive field (RF). These modulations occurred at the end-stage of search and were more potent during correct target identification than during erroneous saccades to a distractor in RF, thus suggesting that this modulation is not a mere presaccadic enhancement. A second pattern of modulation was observed when RF stimuli were nontargets that shared a feature with the target. The latter effect was observed during early stages of search and is consistent with a global feature-specific mechanism. This effect often terminated before target identification, thus suggesting that it interacts with spatial attention. This modulation was exhibited not only for motion but also for color cue, although MT neurons are known to be insensitive to color. Such cue-invariant attentional effects may contribute to a feature binding mechanism acting across visual dimensions.

Using Saliency-Weighted Disparity Statistics for Objective Visual Comfort Assessment of Stereoscopic Images

NASA Astrophysics Data System (ADS)

Zhang, Wenlan; Luo, Ting; Jiang, Gangyi; Jiang, Qiuping; Ying, Hongwei; Lu, Jing

2016-06-01

Visual comfort assessment (VCA) for stereoscopic images is a particularly significant yet challenging task in 3D quality of experience research field. Although the subjective assessment given by human observers is known as the most reliable way to evaluate the experienced visual discomfort, it is time-consuming and non-systematic. Therefore, it is of great importance to develop objective VCA approaches that can faithfully predict the degree of visual discomfort as human beings do. In this paper, a novel two-stage objective VCA framework is proposed. The main contribution of this study is that the important visual attention mechanism of human visual system is incorporated for visual comfort-aware feature extraction. Specifically, in the first stage, we first construct an adaptive 3D visual saliency detection model to derive saliency map of a stereoscopic image, and then a set of saliency-weighted disparity statistics are computed and combined to form a single feature vector to represent a stereoscopic image in terms of visual comfort. In the second stage, a high dimensional feature vector is fused into a single visual comfort score by performing random forest algorithm. Experimental results on two benchmark databases confirm the superior performance of the proposed approach.

Coupled binary embedding for large-scale image retrieval.

PubMed

Zheng, Liang; Wang, Shengjin; Tian, Qi

2014-08-01

Visual matching is a crucial step in image retrieval based on the bag-of-words (BoW) model. In the baseline method, two keypoints are considered as a matching pair if their SIFT descriptors are quantized to the same visual word. However, the SIFT visual word has two limitations. First, it loses most of its discriminative power during quantization. Second, SIFT only describes the local texture feature. Both drawbacks impair the discriminative power of the BoW model and lead to false positive matches. To tackle this problem, this paper proposes to embed multiple binary features at indexing level. To model correlation between features, a multi-IDF scheme is introduced, through which different binary features are coupled into the inverted file. We show that matching verification methods based on binary features, such as Hamming embedding, can be effectively incorporated in our framework. As an extension, we explore the fusion of binary color feature into image retrieval. The joint integration of the SIFT visual word and binary features greatly enhances the precision of visual matching, reducing the impact of false positive matches. Our method is evaluated through extensive experiments on four benchmark datasets (Ukbench, Holidays, DupImage, and MIR Flickr 1M). We show that our method significantly improves the baseline approach. In addition, large-scale experiments indicate that the proposed method requires acceptable memory usage and query time compared with other approaches. Further, when global color feature is integrated, our method yields competitive performance with the state-of-the-arts.

Biometric recognition via texture features of eye movement trajectories in a visual searching task.

PubMed

Li, Chunyong; Xue, Jiguo; Quan, Cheng; Yue, Jingwei; Zhang, Chenggang

2018-01-01

Biometric recognition technology based on eye-movement dynamics has been in development for more than ten years. Different visual tasks, feature extraction and feature recognition methods are proposed to improve the performance of eye movement biometric system. However, the correct identification and verification rates, especially in long-term experiments, as well as the effects of visual tasks and eye trackers' temporal and spatial resolution are still the foremost considerations in eye movement biometrics. With a focus on these issues, we proposed a new visual searching task for eye movement data collection and a new class of eye movement features for biometric recognition. In order to demonstrate the improvement of this visual searching task being used in eye movement biometrics, three other eye movement feature extraction methods were also tested on our eye movement datasets. Compared with the original results, all three methods yielded better results as expected. In addition, the biometric performance of these four feature extraction methods was also compared using the equal error rate (EER) and Rank-1 identification rate (Rank-1 IR), and the texture features introduced in this paper were ultimately shown to offer some advantages with regard to long-term stability and robustness over time and spatial precision. Finally, the results of different combinations of these methods with a score-level fusion method indicated that multi-biometric methods perform better in most cases.

Biometric recognition via texture features of eye movement trajectories in a visual searching task

PubMed Central

Li, Chunyong; Xue, Jiguo; Quan, Cheng; Yue, Jingwei

2018-01-01

Biometric recognition technology based on eye-movement dynamics has been in development for more than ten years. Different visual tasks, feature extraction and feature recognition methods are proposed to improve the performance of eye movement biometric system. However, the correct identification and verification rates, especially in long-term experiments, as well as the effects of visual tasks and eye trackers’ temporal and spatial resolution are still the foremost considerations in eye movement biometrics. With a focus on these issues, we proposed a new visual searching task for eye movement data collection and a new class of eye movement features for biometric recognition. In order to demonstrate the improvement of this visual searching task being used in eye movement biometrics, three other eye movement feature extraction methods were also tested on our eye movement datasets. Compared with the original results, all three methods yielded better results as expected. In addition, the biometric performance of these four feature extraction methods was also compared using the equal error rate (EER) and Rank-1 identification rate (Rank-1 IR), and the texture features introduced in this paper were ultimately shown to offer some advantages with regard to long-term stability and robustness over time and spatial precision. Finally, the results of different combinations of these methods with a score-level fusion method indicated that multi-biometric methods perform better in most cases. PMID:29617383

pV3-Gold Visualization Environment for Computer Simulations

NASA Technical Reports Server (NTRS)

Babrauckas, Theresa L.

1997-01-01

A new visualization environment, pV3-Gold, can be used during and after a computer simulation to extract and visualize the physical features in the results. This environment, which is an extension of the pV3 visualization environment developed at the Massachusetts Institute of Technology with guidance and support by researchers at the NASA Lewis Research Center, features many tools that allow users to display data in various ways.

Feature-fused SSD: fast detection for small objects

NASA Astrophysics Data System (ADS)

Cao, Guimei; Xie, Xuemei; Yang, Wenzhe; Liao, Quan; Shi, Guangming; Wu, Jinjian

2018-04-01

Small objects detection is a challenging task in computer vision due to its limited resolution and information. In order to solve this problem, the majority of existing methods sacrifice speed for improvement in accuracy. In this paper, we aim to detect small objects at a fast speed, using the best object detector Single Shot Multibox Detector (SSD) with respect to accuracy-vs-speed trade-off as base architecture. We propose a multi-level feature fusion method for introducing contextual information in SSD, in order to improve the accuracy for small objects. In detailed fusion operation, we design two feature fusion modules, concatenation module and element-sum module, different in the way of adding contextual information. Experimental results show that these two fusion modules obtain higher mAP on PASCAL VOC2007 than baseline SSD by 1.6 and 1.7 points respectively, especially with 2-3 points improvement on some small objects categories. The testing speed of them is 43 and 40 FPS respectively, superior to the state of the art Deconvolutional single shot detector (DSSD) by 29.4 and 26.4 FPS.

Using convolutional neural networks to estimate time-of-flight from PET detector waveforms

NASA Astrophysics Data System (ADS)

Berg, Eric; Cherry, Simon R.

2018-01-01

Although there have been impressive strides in detector development for time-of-flight positron emission tomography, most detectors still make use of simple signal processing methods to extract the time-of-flight information from the detector signals. In most cases, the timing pick-off for each waveform is computed using leading edge discrimination or constant fraction discrimination, as these were historically easily implemented with analog pulse processing electronics. However, now with the availability of fast waveform digitizers, there is opportunity to make use of more of the timing information contained in the coincident detector waveforms with advanced signal processing techniques. Here we describe the application of deep convolutional neural networks (CNNs), a type of machine learning, to estimate time-of-flight directly from the pair of digitized detector waveforms for a coincident event. One of the key features of this approach is the simplicity in obtaining ground-truth-labeled data needed to train the CNN: the true time-of-flight is determined from the difference in path length between the positron emission and each of the coincident detectors, which can be easily controlled experimentally. The experimental setup used here made use of two photomultiplier tube-based scintillation detectors, and a point source, stepped in 5 mm increments over a 15 cm range between the two detectors. The detector waveforms were digitized at 10 GS s-1 using a bench-top oscilloscope. The results shown here demonstrate that CNN-based time-of-flight estimation improves timing resolution by 20% compared to leading edge discrimination (231 ps versus 185 ps), and 23% compared to constant fraction discrimination (242 ps versus 185 ps). By comparing several different CNN architectures, we also showed that CNN depth (number of convolutional and fully connected layers) had the largest impact on timing resolution, while the exact network parameters, such as convolutional filter size and number of feature maps, had only a minor influence.

Automatic topics segmentation for TV news video

NASA Astrophysics Data System (ADS)

Hmayda, Mounira; Ejbali, Ridha; Zaied, Mourad

2017-03-01

Automatic identification of television programs in the TV stream is an important task for operating archives. This article proposes a new spatio-temporal approach to identify the programs in TV stream into two main steps: First, a reference catalogue for video features visual jingles built. We operate the features that characterize the instances of the same program type to identify the different types of programs in the flow of television. The role of video features is to represent the visual invariants for each visual jingle using appropriate automatic descriptors for each television program. On the other hand, programs in television streams are identified by examining the similarity of the video signal for visual grammars in the catalogue. The main idea of the identification process is to compare the visual similarity of the video signal features in the flow of television to the catalogue. After presenting the proposed approach, the paper overviews encouraging experimental results on several streams extracted from different channels and compounds of several programs.

Crowding by a single bar: probing pattern recognition mechanisms in the visual periphery.

PubMed

Põder, Endel

2014-11-06

Whereas visual crowding does not greatly affect the detection of the presence of simple visual features, it heavily inhibits combining them into recognizable objects. Still, crowding effects have rarely been directly related to general pattern recognition mechanisms. In this study, pattern recognition mechanisms in visual periphery were probed using a single crowding feature. Observers had to identify the orientation of a rotated T presented briefly in a peripheral location. Adjacent to the target, a single bar was presented. The bar was either horizontal or vertical and located in a random direction from the target. It appears that such a crowding bar has very strong and regular effects on the identification of the target orientation. The observer's responses are determined by approximate relative positions of basic visual features; exact image-based similarity to the target is not important. A version of the "standard model" of object recognition with second-order features explains the main regularities of the data. © 2014 ARVO.

Updates on Software development for a RICH detector

NASA Astrophysics Data System (ADS)

Voloshin, Andrew; Benmokhtar, Fatiha; Lendacky, Andrew; Goodwill, Justin

2017-01-01

The CLAS12 detector at Thomas Jefferson National Accelerator Facility (TJNAF) is undergoing an upgrade. One of the improvements is the addition of a Ring Imaging Cherenkov (RICH) detector to improve particle identification in the 3-8 GeV/c momentum range. Approximately 400 multi anode photomultiplier tubes (MAPMTs) are going to be used to detect Cherenkov Radiation in the single photoelectron spectra (SPS). Software development for slow control as well as online monitoring is under development. I will be presenting my work on the development of a java based programs for a monitor and explain its interaction with a Mysql database where the MAPMTs information is stored as well as the techniques used to visualize Cherenkov rings.

Conjunctive Coding of Complex Object Features

PubMed Central

Erez, Jonathan; Cusack, Rhodri; Kendall, William; Barense, Morgan D.

2016-01-01

Critical to perceiving an object is the ability to bind its constituent features into a cohesive representation, yet the manner by which the visual system integrates object features to yield a unified percept remains unknown. Here, we present a novel application of multivoxel pattern analysis of neuroimaging data that allows a direct investigation of whether neural representations integrate object features into a whole that is different from the sum of its parts. We found that patterns of activity throughout the ventral visual stream (VVS), extending anteriorly into the perirhinal cortex (PRC), discriminated between the same features combined into different objects. Despite this sensitivity to the unique conjunctions of features comprising objects, activity in regions of the VVS, again extending into the PRC, was invariant to the viewpoints from which the conjunctions were presented. These results suggest that the manner in which our visual system processes complex objects depends on the explicit coding of the conjunctions of features comprising them. PMID:25921583

Basic Performance Test of a Prototype PET Scanner Using CdTe Semiconductor Detectors

NASA Astrophysics Data System (ADS)

Ueno, Y.; Morimoto, Y.; Tsuchiya, K.; Yanagita, N.; Kojima, S.; Ishitsu, T.; Kitaguchi, H.; Kubo, N.; Zhao, S.; Tamaki, N.; Amemiya, K.

2009-02-01

A prototype positron emission tomography (PET) scanner using CdTe semiconductor detectors was developed, and its initial evaluation was conducted. The scanner was configured to form a single detector ring with six separated detector units, each having 96 detectors arranged in three detector layers. The field of view (FOV) size was 82 mm in diameter. Basic physical performance indicators of the scanner were measured through phantom studies and confirmed by rat imaging. The system-averaged energy resolution and timing resolution were 5.4% and 6.0 ns (each in FWHM) respectively. Spatial resolution measured at FOV center was 2.6 mm FWHM. Scatter fraction was measured and calculated in a National Electrical Manufacturers Association (NEMA)-fashioned manner using a 3-mm diameter hot capillary in a water-filled 80-mm diameter acrylic cylinder. The calculated result was 3.6%. Effect of depth of interaction (DOI) measurement was demonstrated by comparing hot-rod phantom images reconstructed with and without DOI information. Finally, images of a rat myocardium and an implanted tumor were visually assessed, and the imaging performance was confirmed.

Tracking real-time neural activation of conceptual knowledge using single-trial event-related potentials.

PubMed

Amsel, Ben D

2011-04-01

Empirically derived semantic feature norms categorized into different types of knowledge (e.g., visual, functional, auditory) can be summed to create number-of-feature counts per knowledge type. Initial evidence suggests several such knowledge types may be recruited during language comprehension. The present study provides a more detailed understanding of the timecourse and intensity of influence of several such knowledge types on real-time neural activity. A linear mixed-effects model was applied to single trial event-related potentials for 207 visually presented concrete words measured on total number of features (semantic richness), imageability, and number of visual motion, color, visual form, smell, taste, sound, and function features. Significant influences of multiple feature types occurred before 200ms, suggesting parallel neural computation of word form and conceptual knowledge during language comprehension. Function and visual motion features most prominently influenced neural activity, underscoring the importance of action-related knowledge in computing word meaning. The dynamic time courses and topographies of these effects are most consistent with a flexible conceptual system wherein temporally dynamic recruitment of representations in modal and supramodal cortex are a crucial element of the constellation of processes constituting word meaning computation in the brain. Copyright © 2011 Elsevier Ltd. All rights reserved.

Bag of Visual Words Model with Deep Spatial Features for Geographical Scene Classification

PubMed Central

Wu, Lin

2017-01-01

With the popular use of geotagging images, more and more research efforts have been placed on geographical scene classification. In geographical scene classification, valid spatial feature selection can significantly boost the final performance. Bag of visual words (BoVW) can do well in selecting feature in geographical scene classification; nevertheless, it works effectively only if the provided feature extractor is well-matched. In this paper, we use convolutional neural networks (CNNs) for optimizing proposed feature extractor, so that it can learn more suitable visual vocabularies from the geotagging images. Our approach achieves better performance than BoVW as a tool for geographical scene classification, respectively, in three datasets which contain a variety of scene categories. PMID:28706534

Method for the reduction of image content redundancy in large image databases

DOEpatents

Tobin, Kenneth William; Karnowski, Thomas P.

2010-03-02

A method of increasing information content for content-based image retrieval (CBIR) systems includes the steps of providing a CBIR database, the database having an index for a plurality of stored digital images using a plurality of feature vectors, the feature vectors corresponding to distinct descriptive characteristics of the images. A visual similarity parameter value is calculated based on a degree of visual similarity between features vectors of an incoming image being considered for entry into the database and feature vectors associated with a most similar of the stored images. Based on said visual similarity parameter value it is determined whether to store or how long to store the feature vectors associated with the incoming image in the database.

Build a Robust Learning Feature Descriptor by Using a New Image Visualization Method for Indoor Scenario Recognition

PubMed Central

Wang, Xin; Deng, Zhongliang

2017-01-01

In order to recognize indoor scenarios, we extract image features for detecting objects, however, computers can make some unexpected mistakes. After visualizing the histogram of oriented gradient (HOG) features, we find that the world through the eyes of a computer is indeed different from human eyes, which assists researchers to see the reasons that cause a computer to make errors. Additionally, according to the visualization, we notice that the HOG features can obtain rich texture information. However, a large amount of background interference is also introduced. In order to enhance the robustness of the HOG feature, we propose an improved method for suppressing the background interference. On the basis of the original HOG feature, we introduce a principal component analysis (PCA) to extract the principal components of the image colour information. Then, a new hybrid feature descriptor, which is named HOG–PCA (HOGP), is made by deeply fusing these two features. Finally, the HOGP is compared to the state-of-the-art HOG feature descriptor in four scenes under different illumination. In the simulation and experimental tests, the qualitative and quantitative assessments indicate that the visualizing images of the HOGP feature are close to the observation results obtained by human eyes, which is better than the original HOG feature for object detection. Furthermore, the runtime of our proposed algorithm is hardly increased in comparison to the classic HOG feature. PMID:28677635

Combined theory of reflectance and emittance spectroscopy

NASA Technical Reports Server (NTRS)

Hapke, Bruce

1995-01-01

The theory in which either or both reflected sunlight and thermally emitted radiation contribute to the power received by a detector viewing a particulate medium, such as a powder in the laboratory or a planetary regolith, is considered theoretically. This theory is of considerable interest for the interpretation of data from field or spacecraft instruments that are sensitive to the near-infrared region of the spectrum, such as NIMS (near-infrared mapping spectrometer) and VIMS (visual and infrared mapping spectrometer), as well as thermal infrared detectors.

Visual Features Involving Motion Seen from Airport Control Towers

NASA Technical Reports Server (NTRS)

Ellis, Stephen R.; Liston, Dorion

2010-01-01

Visual motion cues are used by tower controllers to support both visual and anticipated separation. Some of these cues are tabulated as part of the overall set of visual features used in towers to separate aircraft. An initial analyses of one motion cue, landing deceleration, is provided as a basis for evaluating how controllers detect and use it for spacing aircraft on or near the surface. Understanding cues like it will help determine if they can be safely used in a remote/virtual tower in which their presentation may be visually degraded.

Detection of Emotional Faces: Salient Physical Features Guide Effective Visual Search

ERIC Educational Resources Information Center

Calvo, Manuel G.; Nummenmaa, Lauri

2008-01-01

In this study, the authors investigated how salient visual features capture attention and facilitate detection of emotional facial expressions. In a visual search task, a target emotional face (happy, disgusted, fearful, angry, sad, or surprised) was presented in an array of neutral faces. Faster detection of happy and, to a lesser extent,…

Extraction of linear features on SAR imagery

NASA Astrophysics Data System (ADS)

Liu, Junyi; Li, Deren; Mei, Xin

2006-10-01

Linear features are usually extracted from SAR imagery by a few edge detectors derived from the contrast ratio edge detector with a constant probability of false alarm. On the other hand, the Hough Transform is an elegant way of extracting global features like curve segments from binary edge images. Randomized Hough Transform can reduce the computation time and memory usage of the HT drastically. While Randomized Hough Transform will bring about a great deal of cells invalid during the randomized sample. In this paper, we propose a new approach to extract linear features on SAR imagery, which is an almost automatic algorithm based on edge detection and Randomized Hough Transform. The presented improved method makes full use of the directional information of each edge candidate points so as to solve invalid cumulate problems. Applied result is in good agreement with the theoretical study, and the main linear features on SAR imagery have been extracted automatically. The method saves storage space and computational time, which shows its effectiveness and applicability.

Cortical Neural Synchronization Underlies Primary Visual Consciousness of Qualia: Evidence from Event-Related Potentials

PubMed Central

Babiloni, Claudio; Marzano, Nicola; Soricelli, Andrea; Cordone, Susanna; Millán-Calenti, José Carlos; Del Percio, Claudio; Buján, Ana

2016-01-01

This article reviews three experiments on event-related potentials (ERPs) testing the hypothesis that primary visual consciousness (stimulus self-report) is related to enhanced cortical neural synchronization as a function of stimulus features. ERP peak latency and sources were compared between “seen” trials and “not seen” trials, respectively related and unrelated to the primary visual consciousness. Three salient features of visual stimuli were considered (visuospatial, emotional face expression, and written words). Results showed the typical visual ERP components in both “seen” and “not seen” trials. There was no statistical difference in the ERP peak latencies between the “seen” and “not seen” trials, suggesting a similar timing of the cortical neural synchronization regardless the primary visual consciousness. In contrast, ERP sources showed differences between “seen” and “not seen” trials. For the visuospatial stimuli, the primary consciousness was related to higher activity in dorsal occipital and parietal sources at about 400 ms post-stimulus. For the emotional face expressions, there was greater activity in parietal and frontal sources at about 180 ms post-stimulus. For the written letters, there was higher activity in occipital, parietal and temporal sources at about 230 ms post-stimulus. These results hint that primary visual consciousness is associated with an enhanced cortical neural synchronization having entirely different spatiotemporal characteristics as a function of the features of the visual stimuli and possibly, the relative qualia (i.e., visuospatial, face expression, and words). In this framework, the dorsal visual stream may be synchronized in association with the primary consciousness of visuospatial and emotional face contents. Analogously, both dorsal and ventral visual streams may be synchronized in association with the primary consciousness of linguistic contents. In this line of reasoning, the ensemble of the cortical neural networks underpinning the single visual features would constitute a sort of multi-dimensional palette of colors, shapes, regions of the visual field, movements, emotional face expressions, and words. The synchronization of one or more of these cortical neural networks, each with its peculiar timing, would produce the primary consciousness of one or more of the visual features of the scene. PMID:27445750

Feature Binding in Visual Working Memory Evaluated by Type Identification Paradigm

ERIC Educational Resources Information Center

Saiki, Jun; Miyatsuji, Hirofumi

2007-01-01

Memory for feature binding comprises a key ingredient in coherent object representations. Previous studies have been equivocal about human capacity for objects in the visual working memory. To evaluate memory for feature binding, a type identification paradigm was devised and used with a multiple-object permanence tracking task. Using objects…

Parylene supported 20um*20um uncooled thermoelectric infrared detector with high fill factor

NASA Astrophysics Data System (ADS)

Modarres-Zadeh, Mohammad J.; Carpenter, Zachary S.; Rockley, Mark G.; Abdolvand, Reza

2012-06-01

Presented is a novel design for an uncooled surface-micromachined thermoelectric (TE) infrared (IR) detector. The detector features a P-doped polysilicon/Nichrome (Cr20-Ni80) thermocouple, which is embedded into a thin layer of Parylene-N to provide structural support. The low thermal conductivity (~0.1W/m.K), chemical resistance, and ease of deposition/patterning of Parylene-N make it an excellent choice of material for use in MEMS thermal detectors. This detector also features an umbrella-like IR absorber composed of a three layer stack of NiCr/SiN/NiCr to optimize IR absorption. The total device area is 20 um * 20 um per pixel with an absorber area of ~19 um * 19 um resulting in a fill factor of 90%. At room temperature, a DC responsivity of ~170V/W with a rise time of less than 8 ms is measured from the fabricated devices in vacuum when viewing a 500K blackbody without any concentrating optics. The dominant source of noise in thermoelectric IR detectors is typically Johnson noise when the detectors are operating in an open circuit condition. The fabricated detectors have resistances about 85KOhm which results in Johnson noise of about 38nV/Hz^0.5. The D* is calculated to be 9 * 106 cm*Hz0.5/ W. Preliminary finite element analysis indicates that the thermal conduction from the hot junction to the substrate through the TE wires is dominant ( GTE >> Gparylene) considering the fabricated dimensions of the parylene film and the TE wires. Thus, by further reducing the size of the TE wires, GTE can be decreased and hence, responsivity can be improved while the parylene film sustains the structural integrity of the cell.

Perceptual learning of basic visual features remains task specific with Training-Plus-Exposure (TPE) training.

PubMed

Cong, Lin-Juan; Wang, Ru-Jie; Yu, Cong; Zhang, Jun-Yun

2016-01-01

Visual perceptual learning is known to be specific to the trained retinal location, feature, and task. However, location and feature specificity can be eliminated by double-training or TPE training protocols, in which observers receive additional exposure to the transfer location or feature dimension via an irrelevant task besides the primary learning task Here we tested whether these new training protocols could even make learning transfer across different tasks involving discrimination of basic visual features (e.g., orientation and contrast). Observers practiced a near-threshold orientation (or contrast) discrimination task. Following a TPE training protocol, they also received exposure to the transfer task via performing suprathreshold contrast (or orientation) discrimination in alternating blocks of trials in the same sessions. The results showed no evidence for significant learning transfer to the untrained near-threshold contrast (or orientation) discrimination task after discounting the pretest effects and the suprathreshold practice effects. These results thus do not support a hypothetical task-independent component in perceptual learning of basic visual features. They also set the boundary of the new training protocols in their capability to enable learning transfer.

Evaluation of a GEM and CAT-based detector for radiation therapy beam monitoring

NASA Astrophysics Data System (ADS)

Brahme, A.; Danielsson, M.; Iacobaeus, C.; Ostling, J.; Peskov, V.; Wallmark, M.

2000-11-01

We are developing a radiation therapy beam monitor for the Karolinska Institute. This monitor will consist of two consecutive detectors confined in one gas chamber: a "keV-photon detector", which will allow diagnostic quality visualization of the patient, and a "MeV-photon detector", that will measure the absolute intensity of the therapy beam and its position with respect to the patient. Both detectors are based on highly radiation resistant gas and solid photon to electron converters, combined with GEMs and a CAT as amplification structures. We have performed systematic studies of the high-rate characteristics of the GEM and the CAT, as well as tested the electron transfer through these electron multipliers and various types of converters. The tests show that the GEM and the CAT satisfy all requirements for the beam monitoring system. As a result of these studies we successfully developed and tested a full section of the beam monitor equipped with a MeV-photon converter placed between the GEM and the CAT.

Visual Pattern Analysis in Histopathology Images Using Bag of Features

NASA Astrophysics Data System (ADS)

Cruz-Roa, Angel; Caicedo, Juan C.; González, Fabio A.

This paper presents a framework to analyse visual patterns in a collection of medical images in a two stage procedure. First, a set of representative visual patterns from the image collection is obtained by constructing a visual-word dictionary under a bag-of-features approach. Second, an analysis of the relationships between visual patterns and semantic concepts in the image collection is performed. The most important visual patterns for each semantic concept are identified using correlation analysis. A matrix visualization of the structure and organization of the image collection is generated using a cluster analysis. The experimental evaluation was conducted on a histopathology image collection and results showed clear relationships between visual patterns and semantic concepts, that in addition, are of easy interpretation and understanding.

Facial recognition using multisensor images based on localized kernel eigen spaces.

PubMed

Gundimada, Satyanadh; Asari, Vijayan K

2009-06-01

A feature selection technique along with an information fusion procedure for improving the recognition accuracy of a visual and thermal image-based facial recognition system is presented in this paper. A novel modular kernel eigenspaces approach is developed and implemented on the phase congruency feature maps extracted from the visual and thermal images individually. Smaller sub-regions from a predefined neighborhood within the phase congruency images of the training samples are merged to obtain a large set of features. These features are then projected into higher dimensional spaces using kernel methods. The proposed localized nonlinear feature selection procedure helps to overcome the bottlenecks of illumination variations, partial occlusions, expression variations and variations due to temperature changes that affect the visual and thermal face recognition techniques. AR and Equinox databases are used for experimentation and evaluation of the proposed technique. The proposed feature selection procedure has greatly improved the recognition accuracy for both the visual and thermal images when compared to conventional techniques. Also, a decision level fusion methodology is presented which along with the feature selection procedure has outperformed various other face recognition techniques in terms of recognition accuracy.

Selection-for-action in visual search.

PubMed

Hannus, Aave; Cornelissen, Frans W; Lindemann, Oliver; Bekkering, Harold

2005-01-01

Grasping an object rather than pointing to it enhances processing of its orientation but not its color. Apparently, visual discrimination is selectively enhanced for a behaviorally relevant feature. In two experiments we investigated the limitations and targets of this bias. Specifically, in Experiment 1 we were interested to find out whether the effect is capacity demanding, therefore we manipulated the set-size of the display. The results indicated a clear cognitive processing capacity requirement, i.e. the magnitude of the effect decreased for a larger set size. Consequently, in Experiment 2, we investigated if the enhancement effect occurs only at the level of behaviorally relevant feature or at a level common to different features. Therefore we manipulated the discriminability of the behaviorally neutral feature (color). Again, results showed that this manipulation influenced the action enhancement of the behaviorally relevant feature. Particularly, the effect of the color manipulation on the action enhancement suggests that the action effect is more likely to bias the competition between different visual features rather than to enhance the processing of the relevant feature. We offer a theoretical account that integrates the action-intention effect within the biased competition model of visual selective attention.

NASA/NOAA: Earth Science Electronic Theater 1999

NASA Technical Reports Server (NTRS)

Hasler, A. Fritz

1999-01-01

The Electronic Theater (E-theater) presents visualizations which span the period from the original Suomi/Hasler animations of the first ATS-1 GEO weather satellite images in 1966 to the latest 1999 NASA Earth Science Vision for the next 25 years. Hot off the SGI-Onyx Graphics-Supercomputer are NASA's visualizations of Hurricanes Mitch, Georges, Fran and Linda. These storms have been recently featured on the covers of National Geographic, Time, Newsweek and Popular Science. Highlights will be shown from the NASA hurricane visualization resource video tape that has been used repeatedly this season on National and International network TV. Results will be presented from a new paper on automatic wind measurements in Hurricane Luis from 1-min GOES images that appeared in the November BAMS. The visualizations are produced by the NASA Goddard Visualization and Analysis Laboratory (VAL/912), and Scientific Visualization Studio (SVS/930), as well as other Goddard and NASA groups using NASA, NOAA, ESA, and NASDA Earth science datasets. Visualizations will be shown from the Earth Science E-Theater 1999 recently presented in Tokyo, Paris, Munich, Sydney, Melbourne, Honolulu, Washington, New York, and Dallas. The presentation Jan 11-14 at the AMS meeting in Dallas used a 4-CPU SGI/CRAY Onyx Infinite Reality Super Graphics Workstation with 8 GB RAM and a Terabyte Disk at 3840 X 1024 resolution with triple synchronized BarcoReality 9200 projectors on a 60ft wide screen. Visualizations will also be featured from the new Earth Today Exhibit which was opened by Vice President Gore on July 2, 1998 at the Smithsonian Air & Space museum in Washington, as well as those presented for possible use at the American Museum of Natural History (NYC), Disney EPCOT, and other venues. New methods are demonstrated for visualizing, interpreting, comparing, organizing and analyzing immense HyperImage remote sensing datasets and three dimensional numerical model results. We call the data from many new Earth sensing satellites, HyperImage datasets, because they have such high resolution in the spectral, temporal, spatial, and dynamic range domains. The traditional numerical spreadsheet paradigm has been extended to develop a scientific visualization approach for processing HyperImage datasets and 3D model results interactively. The advantages of extending the powerful spreadsheet style of computation to multiple sets of images and organizing image processing were demonstrated using the Distributed image SpreadSheet (DISS). The DISS is being used as a high performance testbed Next Generation Internet (NGI) VisAnalysis of: 1) El Nino SSTs and NDVI response 2) Latest GOES 10 5-min rapid Scans of 26 day 5000 frame movie of March & April '98 weather and tornadic storms 3) TRMM rainfall and lightning 4)GOES 9 satellite images/winds and NOAA aircraft radar of hurricane Luis, 5) lightning detector data merged with GOES image sequences, 6) Japanese GMS, TRMM, & ADEOS data 7) Chinese FY2 data 8) Meteosat & ERS/ATSR data 9) synchronized manipulation of multiple 3D numerical model views; and others will be illustrated. The Image SpreadSheet has been highly successful in producing Earth science visualizations for public outreach. Many of these visualizations have been widely disseminated through the world wide web pages of the HPCC/LTP/RSD program which can be found at http://rsd.gsfc.nasa.gov/rsd The one min interval animations of Hurricane Luis on ABC Nightline and the color perspective rendering of Hurricane Fran published by TIME, LIFE, Newsweek, Popular Science, National Geographic, Scientific American, and the "Weekly Reader" are some of the examples which will be shown.

Attentional Bias in Human Category Learning: The Case of Deep Learning.

PubMed

Hanson, Catherine; Caglar, Leyla Roskan; Hanson, Stephen José

2018-01-01

Category learning performance is influenced by both the nature of the category's structure and the way category features are processed during learning. Shepard (1964, 1987) showed that stimuli can have structures with features that are statistically uncorrelated (separable) or statistically correlated (integral) within categories. Humans find it much easier to learn categories having separable features, especially when attention to only a subset of relevant features is required, and harder to learn categories having integral features, which require consideration of all of the available features and integration of all the relevant category features satisfying the category rule (Garner, 1974). In contrast to humans, a single hidden layer backpropagation (BP) neural network has been shown to learn both separable and integral categories equally easily, independent of the category rule (Kruschke, 1993). This "failure" to replicate human category performance appeared to be strong evidence that connectionist networks were incapable of modeling human attentional bias. We tested the presumed limitations of attentional bias in networks in two ways: (1) by having networks learn categories with exemplars that have high feature complexity in contrast to the low dimensional stimuli previously used, and (2) by investigating whether a Deep Learning (DL) network, which has demonstrated humanlike performance in many different kinds of tasks (language translation, autonomous driving, etc.), would display human-like attentional bias during category learning. We were able to show a number of interesting results. First, we replicated the failure of BP to differentially process integral and separable category structures when low dimensional stimuli are used (Garner, 1974; Kruschke, 1993). Second, we show that using the same low dimensional stimuli, Deep Learning (DL), unlike BP but similar to humans, learns separable category structures more quickly than integral category structures. Third, we show that even BP can exhibit human like learning differences between integral and separable category structures when high dimensional stimuli (face exemplars) are used. We conclude, after visualizing the hidden unit representations, that DL appears to extend initial learning due to feature development thereby reducing destructive feature competition by incrementally refining feature detectors throughout later layers until a tipping point (in terms of error) is reached resulting in rapid asymptotic learning.

Multispectral atmospheric mapping sensor of mesoscale water vapor features

NASA Technical Reports Server (NTRS)

Menzel, P.; Jedlovec, G.; Wilson, G.; Atkinson, R.; Smith, W.

1985-01-01

The Multispectral atmospheric mapping sensor was checked out for specified spectral response and detector noise performance in the eight visible and three infrared (6.7, 11.2, 12.7 micron) spectral bands. A calibration algorithm was implemented for the infrared detectors. Engineering checkout flights on board the ER-2 produced imagery at 50 m resolution in which water vapor features in the 6.7 micron spectral band are most striking. These images were analyzed on the Man computer Interactive Data Access System (McIDAS). Ground truth and ancillary data was accessed to verify the calibration.

Neural pathways for visual speech perception

PubMed Central

Bernstein, Lynne E.; Liebenthal, Einat

2014-01-01

This paper examines the questions, what levels of speech can be perceived visually, and how is visual speech represented by the brain? Review of the literature leads to the conclusions that every level of psycholinguistic speech structure (i.e., phonetic features, phonemes, syllables, words, and prosody) can be perceived visually, although individuals differ in their abilities to do so; and that there are visual modality-specific representations of speech qua speech in higher-level vision brain areas. That is, the visual system represents the modal patterns of visual speech. The suggestion that the auditory speech pathway receives and represents visual speech is examined in light of neuroimaging evidence on the auditory speech pathways. We outline the generally agreed-upon organization of the visual ventral and dorsal pathways and examine several types of visual processing that might be related to speech through those pathways, specifically, face and body, orthography, and sign language processing. In this context, we examine the visual speech processing literature, which reveals widespread diverse patterns of activity in posterior temporal cortices in response to visual speech stimuli. We outline a model of the visual and auditory speech pathways and make several suggestions: (1) The visual perception of speech relies on visual pathway representations of speech qua speech. (2) A proposed site of these representations, the temporal visual speech area (TVSA) has been demonstrated in posterior temporal cortex, ventral and posterior to multisensory posterior superior temporal sulcus (pSTS). (3) Given that visual speech has dynamic and configural features, its representations in feedforward visual pathways are expected to integrate these features, possibly in TVSA. PMID:25520611

Visual search deficits in amblyopia.

PubMed

Tsirlin, Inna; Colpa, Linda; Goltz, Herbert C; Wong, Agnes M F

2018-04-01

Amblyopia is a neurodevelopmental disorder defined as a reduction in visual acuity that cannot be corrected by optical means. It has been associated with low-level deficits. However, research has demonstrated a link between amblyopia and visual attention deficits in counting, tracking, and identifying objects. Visual search is a useful tool for assessing visual attention but has not been well studied in amblyopia. Here, we assessed the extent of visual search deficits in amblyopia using feature and conjunction search tasks. We compared the performance of participants with amblyopia (n = 10) to those of controls (n = 12) on both feature and conjunction search tasks using Gabor patch stimuli, varying spatial bandwidth and orientation. To account for the low-level deficits inherent in amblyopia, we measured individual contrast and crowding thresholds and monitored eye movements. The display elements were then presented at suprathreshold levels to ensure that visibility was equalized across groups. There was no performance difference between groups on feature search, indicating that our experimental design controlled successfully for low-level amblyopia deficits. In contrast, during conjunction search, median reaction times and reaction time slopes were significantly larger in participants with amblyopia compared with controls. Amblyopia differentially affects performance on conjunction visual search, a more difficult task that requires feature binding and possibly the involvement of higher-level attention processes. Deficits in visual search may affect day-to-day functioning in people with amblyopia.

Main features of detectors and isotopes to investigate double beta decay with increased sensitivity

NASA Astrophysics Data System (ADS)

Barabash, A. S.

2018-03-01

The current situation in double beta decay experiments, the characteristics of modern detectors and the possibility of increasing the sensitivity to neutrino mass in future experiments are discussed. The issue of the production and use of enriched isotopes in double beta decay experiments is discussed in addition.

Improved neutron-gamma discrimination for a 3He neutron detector using subspace learning methods

DOE PAGES

Wang, C. L.; Funk, L. L.; Riedel, R. A.; ...

2017-02-10

3He gas based neutron linear-position-sensitive detectors (LPSDs) have been applied for many neutron scattering instruments. Traditional Pulse-Height Analysis (PHA) for Neutron-Gamma Discrimination (NGD) resulted in the neutron-gamma efficiency ratio on the orders of 10 5-10 6. The NGD ratios of 3He detectors need to be improved for even better scientific results from neutron scattering. Digital Signal Processing (DSP) analyses of waveforms were proposed for obtaining better NGD ratios, based on features extracted from rise-time, pulse amplitude, charge integration, a simplified Wiener filter, and the cross-correlation between individual and template waveforms of neutron and gamma events. Fisher linear discriminant analysis (FLDA)more » and three multivariate analyses (MVAs) of the features were performed. The NGD ratios are improved by about 10 2-10 3 times compared with the traditional PHA method. Finally, our results indicate the NGD capabilities of 3He tube detectors can be significantly improved with subspace-learning based methods, which may result in a reduced data-collection time and better data quality for further data reduction.« less

Exploring the capabilities of support vector machines in detecting silent data corruptions

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

Subasi, Omer; Di, Sheng; Bautista-Gomez, Leonardo

As the exascale era approaches, the increasing capacity of high-performance computing (HPC) systems with targeted power and energy budget goals introduces significant challenges in reliability. Silent data corruptions (SDCs), or silent errors, are one of the major sources that corrupt the execution results of HPC applications without being detected. Here in this paper, we explore a set of novel SDC detectors – by leveraging epsilon-insensitive support vector machine regression – to detect SDCs that occur in HPC applications. The key contributions are threefold. (1) Our exploration takes temporal, spatial, and spatiotemporal features into account and analyzes different detectors based onmore » different features. (2) We provide an in-depth study on the detection ability and performance with different parameters, and we optimize the detection range carefully. (3) Experiments with eight real-world HPC applications show that support-vector-machine-based detectors can achieve detection sensitivity (i.e., recall) up to 99% yet suffer a less than 1% false positive rate for most cases. Our detectors incur low performance overhead, 5% on average, for all benchmarks studied in this work.« less

Exploring the capabilities of support vector machines in detecting silent data corruptions

DOE PAGES

Subasi, Omer; Di, Sheng; Bautista-Gomez, Leonardo; ...

2018-02-01

As the exascale era approaches, the increasing capacity of high-performance computing (HPC) systems with targeted power and energy budget goals introduces significant challenges in reliability. Silent data corruptions (SDCs), or silent errors, are one of the major sources that corrupt the execution results of HPC applications without being detected. Here in this paper, we explore a set of novel SDC detectors – by leveraging epsilon-insensitive support vector machine regression – to detect SDCs that occur in HPC applications. The key contributions are threefold. (1) Our exploration takes temporal, spatial, and spatiotemporal features into account and analyzes different detectors based onmore » different features. (2) We provide an in-depth study on the detection ability and performance with different parameters, and we optimize the detection range carefully. (3) Experiments with eight real-world HPC applications show that support-vector-machine-based detectors can achieve detection sensitivity (i.e., recall) up to 99% yet suffer a less than 1% false positive rate for most cases. Our detectors incur low performance overhead, 5% on average, for all benchmarks studied in this work.« less

NEW DEVELOPMENTS AND APPLICATIONS OF SUPERHEATED EMULSIONS: WARHEAD VERIFICATION AND SPECIAL NUCLEAR MATERIAL INTERDICTION.

PubMed

d'Errico, F; Chierici, A; Gattas-Sethi, M; Philippe, S; Goldston, R; Glaser, A

2018-04-25

In recent years, neutron detection with superheated emulsions has received renewed attention thanks to improved detector manufacturing and read-out techniques, and thanks to successful applications in warhead verification and special nuclear material (SNM) interdiction. Detectors are currently manufactured with methods allowing high uniformity of the drop sizes, which in turn allows the use of optical read-out techniques based on dynamic light scattering. Small detector cartridges arranged in 2D matrices are developed for the verification of a declared warhead without revealing its design. For this application, the enabling features of the emulsions are that bubbles formed at different times cannot be distinguished from each other, while the passive nature of the detectors avoids the susceptibility to electronic snooping and tampering. Large modules of emulsions are developed to detect the presence of shielded special nuclear materials hidden in cargo containers 'interrogated' with high energy X-rays. In this case, the enabling features of the emulsions are photon discrimination, a neutron detection threshold close to 3 MeV and a rate-insensitive read-out.

A stable biologically motivated learning mechanism for visual feature extraction to handle facial categorization.

PubMed

Rajaei, Karim; Khaligh-Razavi, Seyed-Mahdi; Ghodrati, Masoud; Ebrahimpour, Reza; Shiri Ahmad Abadi, Mohammad Ebrahim

2012-01-01

The brain mechanism of extracting visual features for recognizing various objects has consistently been a controversial issue in computational models of object recognition. To extract visual features, we introduce a new, biologically motivated model for facial categorization, which is an extension of the Hubel and Wiesel simple-to-complex cell hierarchy. To address the synaptic stability versus plasticity dilemma, we apply the Adaptive Resonance Theory (ART) for extracting informative intermediate level visual features during the learning process, which also makes this model stable against the destruction of previously learned information while learning new information. Such a mechanism has been suggested to be embedded within known laminar microcircuits of the cerebral cortex. To reveal the strength of the proposed visual feature learning mechanism, we show that when we use this mechanism in the training process of a well-known biologically motivated object recognition model (the HMAX model), it performs better than the HMAX model in face/non-face classification tasks. Furthermore, we demonstrate that our proposed mechanism is capable of following similar trends in performance as humans in a psychophysical experiment using a face versus non-face rapid categorization task.

Detection of emotional faces: salient physical features guide effective visual search.

PubMed

Calvo, Manuel G; Nummenmaa, Lauri

2008-08-01

In this study, the authors investigated how salient visual features capture attention and facilitate detection of emotional facial expressions. In a visual search task, a target emotional face (happy, disgusted, fearful, angry, sad, or surprised) was presented in an array of neutral faces. Faster detection of happy and, to a lesser extent, surprised and disgusted faces was found both under upright and inverted display conditions. Inversion slowed down the detection of these faces less than that of others (fearful, angry, and sad). Accordingly, the detection advantage involves processing of featural rather than configural information. The facial features responsible for the detection advantage are located in the mouth rather than the eye region. Computationally modeled visual saliency predicted both attentional orienting and detection. Saliency was greatest for the faces (happy) and regions (mouth) that were fixated earlier and detected faster, and there was close correspondence between the onset of the modeled saliency peak and the time at which observers initially fixated the faces. The authors conclude that visual saliency of specific facial features--especially the smiling mouth--is responsible for facilitated initial orienting, which thus shortens detection. (PsycINFO Database Record (c) 2008 APA, all rights reserved).

Shape and color conjunction stimuli are represented as bound objects in visual working memory.

PubMed

Luria, Roy; Vogel, Edward K

2011-05-01

The integrated object view of visual working memory (WM) argues that objects (rather than features) are the building block of visual WM, so that adding an extra feature to an object does not result in any extra cost to WM capacity. Alternative views have shown that complex objects consume additional WM storage capacity so that it may not be represented as bound objects. Additionally, it was argued that two features from the same dimension (i.e., color-color) do not form an integrated object in visual WM. This led some to argue for a "weak" object view of visual WM. We used the contralateral delay activity (the CDA) as an electrophysiological marker of WM capacity, to test those alternative hypotheses to the integrated object account. In two experiments we presented complex stimuli and color-color conjunction stimuli, and compared performance in displays that had one object but varying degrees of feature complexity. The results supported the integrated object account by showing that the CDA amplitude corresponded to the number of objects regardless of the number of features within each object, even for complex objects or color-color conjunction stimuli. Copyright © 2010 Elsevier Ltd. All rights reserved.

Modelling and Characterisation of Detection Models in WAMI for Handling Negative Information

DTIC Science & Technology

2014-02-01

behaviour of the multi-stage detectors used in LoFT. This model is then used in a Probabilistic Hypothesis Density Filter (PHD). Unlike most multitarget...Therefore, we decided to use machine learning techniques which could model — and pre- dict — the behaviour of the detectors in LoFT. Because we are using...on feature detectors [8], motion models [13] and descriptor and template adaptation [9]. 2.3.2 State Model The state space of LoFT is defined in 2D

Digital PCM bit synchronizer and detector

NASA Astrophysics Data System (ADS)

Moghazy, A. E.; Maral, G.; Blanchard, A.

1980-08-01

A theoretical analysis of a digital self-bit synchronizer and detector is presented and supported by the implementation of an experimental model that utilizes standard TTL logic circuits. This synchronizer is based on the generation of spectral line components by nonlinear filtering of the received bit stream, and extracting the line by a digital phase-locked loop (DPLL). The extracted reference signal instructs a digital matched filter (DMF) data detector. This realization features a short acquisition time and an all-digital structure.

Xenon gamma-ray detector for ecological applications

NASA Astrophysics Data System (ADS)

Novikov, Alexander S.; Ulin, Sergey E.; Chernysheva, Irina V.; Dmitrenko, Valery V.; Grachev, Victor M.; Petrenko, Denis V.; Shustov, Alexander E.; Uteshev, Ziyaetdin M.; Vlasik, Konstantin F.

2015-01-01

A description of the xenon detector (XD) for ecological applications is presented. The detector provides high energy resolution and is able to operate under extreme environmental conditions (wide temperature range and unfavorable acoustic action). Resistance to acoustic noise as well as improvement in energy resolution has been achieved by means of real-time digital pulse processing. Another important XD feature is the ionization chamber's thin wall with composite housing, which significantly decreases the mass of the device and expands its energy range, especially at low energies.

TCPD: A micropattern photon detector hybrid for RICH applications

NASA Astrophysics Data System (ADS)

Hamar, G.; Varga, D.

2017-03-01

A micropattern and wire chamber hybrid has been constructed for UV photon detection, and its performance evaluated. It is revealed that such combination retains some key advantages of both the Thick-GEM primary and CCC secondary amplification stages, and results in a high gain gaseous photon detector with outstanding stability. Key features such as MIP suppression, detection efficiency and photon cluster size are discussed. The capability of the detector for UV photon detection has been established and proven with Cherenkov photons in particle beam tests.

Neural correlates of context-dependent feature conjunction learning in visual search tasks.

PubMed

Reavis, Eric A; Frank, Sebastian M; Greenlee, Mark W; Tse, Peter U

2016-06-01

Many perceptual learning experiments show that repeated exposure to a basic visual feature such as a specific orientation or spatial frequency can modify perception of that feature, and that those perceptual changes are associated with changes in neural tuning early in visual processing. Such perceptual learning effects thus exert a bottom-up influence on subsequent stimulus processing, independent of task-demands or endogenous influences (e.g., volitional attention). However, it is unclear whether such bottom-up changes in perception can occur as more complex stimuli such as conjunctions of visual features are learned. It is not known whether changes in the efficiency with which people learn to process feature conjunctions in a task (e.g., visual search) reflect true bottom-up perceptual learning versus top-down, task-related learning (e.g., learning better control of endogenous attention). Here we show that feature conjunction learning in visual search leads to bottom-up changes in stimulus processing. First, using fMRI, we demonstrate that conjunction learning in visual search has a distinct neural signature: an increase in target-evoked activity relative to distractor-evoked activity (i.e., a relative increase in target salience). Second, we demonstrate that after learning, this neural signature is still evident even when participants passively view learned stimuli while performing an unrelated, attention-demanding task. This suggests that conjunction learning results in altered bottom-up perceptual processing of the learned conjunction stimuli (i.e., a perceptual change independent of the task). We further show that the acquired change in target-evoked activity is contextually dependent on the presence of distractors, suggesting that search array Gestalts are learned. Hum Brain Mapp 37:2319-2330, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Feature-based attention elicits surround suppression in feature space.

PubMed

Störmer, Viola S; Alvarez, George A

2014-09-08

It is known that focusing attention on a particular feature (e.g., the color red) facilitates the processing of all objects in the visual field containing that feature [1-7]. Here, we show that such feature-based attention not only facilitates processing but also actively inhibits processing of similar, but not identical, features globally across the visual field. We combined behavior and electrophysiological recordings of frequency-tagged potentials in human observers to measure this inhibitory surround in feature space. We found that sensory signals of an attended color (e.g., red) were enhanced, whereas sensory signals of colors similar to the target color (e.g., orange) were suppressed relative to colors more distinct from the target color (e.g., yellow). Importantly, this inhibitory effect spreads globally across the visual field, thus operating independently of location. These findings suggest that feature-based attention comprises an excitatory peak surrounded by a narrow inhibitory zone in color space to attenuate the most distracting and potentially confusable stimuli during visual perception. This selection profile is akin to what has been reported for location-based attention [8-10] and thus suggests that such center-surround mechanisms are an overarching principle of attention across different domains in the human brain. Copyright © 2014 Elsevier Ltd. All rights reserved.

Saliency Detection of Stereoscopic 3D Images with Application to Visual Discomfort Prediction

NASA Astrophysics Data System (ADS)

Li, Hong; Luo, Ting; Xu, Haiyong

2017-06-01

Visual saliency detection is potentially useful for a wide range of applications in image processing and computer vision fields. This paper proposes a novel bottom-up saliency detection approach for stereoscopic 3D (S3D) images based on regional covariance matrix. As for S3D saliency detection, besides the traditional 2D low-level visual features, additional 3D depth features should also be considered. However, only limited efforts have been made to investigate how different features (e.g. 2D and 3D features) contribute to the overall saliency of S3D images. The main contribution of this paper is that we introduce a nonlinear feature integration descriptor, i.e., regional covariance matrix, to fuse both 2D and 3D features for S3D saliency detection. The regional covariance matrix is shown to be effective for nonlinear feature integration by modelling the inter-correlation of different feature dimensions. Experimental results demonstrate that the proposed approach outperforms several existing relevant models including 2D extended and pure 3D saliency models. In addition, we also experimentally verified that the proposed S3D saliency map can significantly improve the prediction accuracy of experienced visual discomfort when viewing S3D images.

Improved background suppression for radiative capture reactions at LUNA with HPGe and BGO detectors

NASA Astrophysics Data System (ADS)

Boeltzig, A.; Best, A.; Imbriani, G.; Junker, M.; Aliotta, M.; Bemmerer, D.; Broggini, C.; Bruno, C. G.; Buompane, R.; Caciolli, A.; Cavanna, F.; Chillery, T.; Ciani, G. F.; Corvisiero, P.; Csedreki, L.; Davinson, T.; deBoer, R. J.; Depalo, R.; Di Leva, A.; Elekes, Z.; Ferraro, F.; Fiore, E. M.; Formicola, A.; Fülöp, Z.; Gervino, G.; Guglielmetti, A.; Gustavino, C.; Gyürky, G.; Kochanek, I.; Menegazzo, R.; Mossa, V.; Pantaleo, F. R.; Paticchio, V.; Perrino, R.; Piatti, D.; Prati, P.; Schiavulli, L.; Stöckel, K.; Straniero, O.; Strieder, F.; Szücs, T.; Takács, M. P.; Trezzi, D.; Wiescher, M.; Zavatarelli, S.

2018-02-01

Direct measurements of small nuclear reaction cross sections require a low background in the signal region of interest to achieve the necessary sensitivity. We describe two complementary detector setups that have been used for studies of ({{p}},γ ) reactions with solid targets at the Laboratory for Underground Nuclear Astrophysics (LUNA): a high-purity germanium detector and a bismuth germanate (BGO) detector. We present the effect of a customised lead shielding on the measured background spectra in the two detector setups at LUNA. We developed a model to describe the contributions of environmental and intrinsic backgrounds in the BGO detector measurements. Furthermore we present an upgrade of the data acquisition system for our BGO detector, which allows us to exploit the features of the segmented detector and overcome some of the limitations encountered in previous experiments. We conclude with a discussion on the improved sensitivity of the presented setups, and the benefits for ongoing and possible future measurements.

Smile detectors correlation

NASA Astrophysics Data System (ADS)

Yuksel, Kivanc; Chang, Xin; Skarbek, Władysław

2017-08-01

The novel smile recognition algorithm is presented based on extraction of 68 facial salient points (fp68) using the ensemble of regression trees. The smile detector exploits the Support Vector Machine linear model. It is trained with few hundreds exemplar images by SVM algorithm working in 136 dimensional space. It is shown by the strict statistical data analysis that such geometric detector strongly depends on the geometry of mouth opening area, measured by triangulation of outer lip contour. To this goal two Bayesian detectors were developed and compared with SVM detector. The first uses the mouth area in 2D image, while the second refers to the mouth area in 3D animated face model. The 3D modeling is based on Candide-3 model and it is performed in real time along with three smile detectors and statistics estimators. The mouth area/Bayesian detectors exhibit high correlation with fp68/SVM detector in a range [0:8; 1:0], depending mainly on light conditions and individual features with advantage of 3D technique, especially in hard light conditions.

Obligatory encoding of task-irrelevant features depletes working memory resources.

PubMed

Marshall, Louise; Bays, Paul M

2013-02-18

Selective attention is often considered the "gateway" to visual working memory (VWM). However, the extent to which we can voluntarily control which of an object's features enter memory remains subject to debate. Recent research has converged on the concept of VWM as a limited commodity distributed between elements of a visual scene. Consequently, as memory load increases, the fidelity with which each visual feature is stored decreases. Here we used changes in recall precision to probe whether task-irrelevant features were encoded into VWM when individuals were asked to store specific feature dimensions. Recall precision for both color and orientation was significantly enhanced when task-irrelevant features were removed, but knowledge of which features would be probed provided no advantage over having to memorize both features of all items. Next, we assessed the effect an interpolated orientation-or color-matching task had on the resolution with which orientations in a memory array were stored. We found that the presence of orientation information in the second array disrupted memory of the first array. The cost to recall precision was identical whether the interfering features had to be remembered, attended to, or could be ignored. Therefore, it appears that storing, or merely attending to, one feature of an object is sufficient to promote automatic encoding of all its features, depleting VWM resources. However, the precision cost was abolished when the match task preceded the memory array. So, while encoding is automatic, maintenance is voluntary, allowing resources to be reallocated to store new visual information.

The effect of gamma-enhancing binaural beats on the control of feature bindings.

PubMed

Colzato, Lorenza S; Steenbergen, Laura; Sellaro, Roberta

2017-07-01

Binaural beats represent the auditory experience of an oscillating sound that occurs when two sounds with neighboring frequencies are presented to one's left and right ear separately. Binaural beats have been shown to impact information processing via their putative role in increasing neural synchronization. Recent studies of feature-repetition effects demonstrated interactions between perceptual features and action-related features: repeating only some, but not all features of a perception-action episode hinders performance. These partial-repetition (or binding) costs point to the existence of temporary episodic bindings (event files) that are automatically retrieved by repeating at least one of their features. Given that neural synchronization in the gamma band has been associated with visual feature bindings, we investigated whether the impact of binaural beats extends to the top-down control of feature bindings. Healthy adults listened to gamma-frequency (40 Hz) binaural beats or to a constant tone of 340 Hz (control condition) for ten minutes before and during a feature-repetition task. While the size of visuomotor binding costs (indicating the binding of visual and action features) was unaffected by the binaural beats, the size of visual feature binding costs (which refer to the binding between the two visual features) was considerably smaller during gamma-frequency binaural beats exposure than during the control condition. Our results suggest that binaural beats enhance selectivity in updating episodic memory traces and further strengthen the hypothesis that neural activity in the gamma band is critically associated with the control of feature binding.

Cherenkov light identification in TeO2 crystals with Si low-temperature detectors

NASA Astrophysics Data System (ADS)

Gironi, L.; Biassoni, M.; Brofferio, C.; Capelli, S.; Carniti, P.; Cassina, L.; Clemenza, M.; Cremonesi, O.; Faverzani, M.; Ferri, E.; Giachero, A.; Gotti, C.; Maino, M.; Margesin, B.; Nucciotti, A.; Pavan, M.; Pessina, G.; Pozzi, S.; Previtali, E.; Puiu, A.; Sisti, M.; Terranova, F.

2017-09-01

Low temperature thermal detectors with particle identification capabilities are among the best detectors for next generation experiments for the search of neutrinoless double beta decay. Thermal detectors allow to reach excellent energy resolution and to optimize the detection efficiency, while the possibility to identify the interacting particle allows to greatly reduce the background. Tellurium dioxide is one of the favourite compounds since it has long demonstrated the first two features and could reach the third through Cherenkov emission tagging [1]. A new generation of cryogenic light detectors are however required to detect the few Cherenkov photons emitted by electrons of few MeV energy. Preliminary measurements with new Si light detectors demonstrated a clear event-by-event discrimination between alpha and beta/gamma interactions at the 130Te neutrinoless double beta decay Q-value (2528 keV).

Nebula: reconstruction and visualization of scattering data in reciprocal space.

PubMed

Reiten, Andreas; Chernyshov, Dmitry; Mathiesen, Ragnvald H

2015-04-01

Two-dimensional solid-state X-ray detectors can now operate at considerable data throughput rates that allow full three-dimensional sampling of scattering data from extended volumes of reciprocal space within second to minute time-scales. For such experiments, simultaneous analysis and visualization allows for remeasurements and a more dynamic measurement strategy. A new software, Nebula , is presented. It efficiently reconstructs X-ray scattering data, generates three-dimensional reciprocal space data sets that can be visualized interactively, and aims to enable real-time processing in high-throughput measurements by employing parallel computing on commodity hardware.

Nebula: reconstruction and visualization of scattering data in reciprocal space

PubMed Central

Reiten, Andreas; Chernyshov, Dmitry; Mathiesen, Ragnvald H.

2015-01-01

Two-dimensional solid-state X-ray detectors can now operate at considerable data throughput rates that allow full three-dimensional sampling of scattering data from extended volumes of reciprocal space within second to minute time­scales. For such experiments, simultaneous analysis and visualization allows for remeasurements and a more dynamic measurement strategy. A new software, Nebula, is presented. It efficiently reconstructs X-ray scattering data, generates three-dimensional reciprocal space data sets that can be visualized interactively, and aims to enable real-time processing in high-throughput measurements by employing parallel computing on commodity hardware. PMID:25844083

Electrometer Amplifier With Overload Protection

NASA Technical Reports Server (NTRS)

Woeller, F. H.; Alexander, R.

1986-01-01

Circuit features low noise, input offset, and high linearity. Input preamplifier includes input-overload protection and nulling circuit to subtract dc offset from output. Prototype dc amplifier designed for use with ion detector has features desirable in general laboratory and field instrumentation.

Dorsal hippocampus is necessary for visual categorization in rats.

PubMed

Kim, Jangjin; Castro, Leyre; Wasserman, Edward A; Freeman, John H

2018-02-23

The hippocampus may play a role in categorization because of the need to differentiate stimulus categories (pattern separation) and to recognize category membership of stimuli from partial information (pattern completion). We hypothesized that the hippocampus would be more crucial for categorization of low-density (few relevant features) stimuli-due to the higher demand on pattern separation and pattern completion-than for categorization of high-density (many relevant features) stimuli. Using a touchscreen apparatus, rats were trained to categorize multiple abstract stimuli into two different categories. Each stimulus was a pentagonal configuration of five visual features; some of the visual features were relevant for defining the category whereas others were irrelevant. Two groups of rats were trained with either a high (dense, n = 8) or low (sparse, n = 8) number of category-relevant features. Upon reaching criterion discrimination (≥75% correct, on 2 consecutive days), bilateral cannulas were implanted in the dorsal hippocampus. The rats were then given either vehicle or muscimol infusions into the hippocampus just prior to various testing sessions. They were tested with: the previously trained stimuli (trained), novel stimuli involving new irrelevant features (novel), stimuli involving relocated features (relocation), and a single relevant feature (singleton). In training, the dense group reached criterion faster than the sparse group, indicating that the sparse task was more difficult than the dense task. In testing, accuracy of both groups was equally high for trained and novel stimuli. However, both groups showed impaired accuracy in the relocation and singleton conditions, with a greater deficit in the sparse group. The testing data indicate that rats encode both the relevant features and the spatial locations of the features. Hippocampal inactivation impaired visual categorization regardless of the density of the category-relevant features for the trained, novel, relocation, and singleton stimuli. Hippocampus-mediated pattern completion and pattern separation mechanisms may be necessary for visual categorization involving overlapping irrelevant features. © 2018 Wiley Periodicals, Inc.

A Photon Interference Detector with Continuous Display.

ERIC Educational Resources Information Center

Gilmore, R. S.

1978-01-01

Describes an apparatus which attempts to give a direct visual impression of the random detection of individual photons coupled with the recognition of the classical intensity distribution as a result of fairly high proton statistics. (Author/GA)

Evidence against the temporal subsampling account of illusory motion reversal

PubMed Central

Kline, Keith A.; Eagleman, David M.

2010-01-01

An illusion of reversed motion may occur sporadically while viewing continuous smooth motion. This has been suggested as evidence of discrete temporal sampling by the visual system in analogy to the sampling that generates the wagon–wheel effect on film. In an alternative theory, the illusion is not the result of discrete sampling but instead of perceptual rivalry between appropriately activated and spuriously activated motion detectors. Results of the current study demonstrate that illusory reversals of two spatially overlapping and orthogonal motions often occur separately, providing evidence against the possibility that illusory motion reversal (IMR) is caused by temporal sampling within a visual region. Further, we find that IMR occurs with non-uniform and non-periodic stimuli—an observation that is not accounted for by the temporal sampling hypothesis. We propose, that a motion aftereffect is superimposed on the moving stimulus, sporadically allowing motion detectors for the reverse direction to dominate perception. PMID:18484852

The Role of Target-Distractor Relationships in Guiding Attention and the Eyes in Visual Search

ERIC Educational Resources Information Center

Becker, Stefanie I.

2010-01-01

Current models of visual search assume that visual attention can be guided by tuning attention toward specific feature values (e.g., particular size, color) or by inhibiting the features of the irrelevant nontargets. The present study demonstrates that attention and eye movements can also be guided by a relational specification of how the target…

Characterization of electroencephalography signals for estimating saliency features in videos.

PubMed

Liang, Zhen; Hamada, Yasuyuki; Oba, Shigeyuki; Ishii, Shin

2018-05-12

Understanding the functions of the visual system has been one of the major targets in neuroscience formany years. However, the relation between spontaneous brain activities and visual saliency in natural stimuli has yet to be elucidated. In this study, we developed an optimized machine learning-based decoding model to explore the possible relationships between the electroencephalography (EEG) characteristics and visual saliency. The optimal features were extracted from the EEG signals and saliency map which was computed according to an unsupervised saliency model ( Tavakoli and Laaksonen, 2017). Subsequently, various unsupervised feature selection/extraction techniques were examined using different supervised regression models. The robustness of the presented model was fully verified by means of ten-fold or nested cross validation procedure, and promising results were achieved in the reconstruction of saliency features based on the selected EEG characteristics. Through the successful demonstration of using EEG characteristics to predict the real-time saliency distribution in natural videos, we suggest the feasibility of quantifying visual content through measuring brain activities (EEG signals) in real environments, which would facilitate the understanding of cortical involvement in the processing of natural visual stimuli and application developments motivated by human visual processing. Copyright © 2018 Elsevier Ltd. All rights reserved.

Sci-Fin: Visual Mining Spatial and Temporal Behavior Features from Social Media

PubMed Central

Pu, Jiansu; Teng, Zhiyao; Gong, Rui; Wen, Changjiang; Xu, Yang

2016-01-01

Check-in records are usually available in social services, which offer us the opportunity to capture and analyze users’ spatial and temporal behaviors. Mining such behavior features is essential to social analysis and business intelligence. However, the complexity and incompleteness of check-in records bring challenges to achieve such a task. Different from the previous work on social behavior analysis, in this paper, we present a visual analytics system, Social Check-in Fingerprinting (Sci-Fin), to facilitate the analysis and visualization of social check-in data. We focus on three major components of user check-in data: location, activity, and profile. Visual fingerprints for location, activity, and profile are designed to intuitively represent the high-dimensional attributes. To visually mine and demonstrate the behavior features, we integrate WorldMapper and Voronoi Treemap into our glyph-like designs. Such visual fingerprint designs offer us the opportunity to summarize the interesting features and patterns from different check-in locations, activities and users (groups). We demonstrate the effectiveness and usability of our system by conducting extensive case studies on real check-in data collected from a popular microblogging service. Interesting findings are reported and discussed at last. PMID:27999398

Sci-Fin: Visual Mining Spatial and Temporal Behavior Features from Social Media.

PubMed

Pu, Jiansu; Teng, Zhiyao; Gong, Rui; Wen, Changjiang; Xu, Yang

2016-12-20

Check-in records are usually available in social services, which offer us the opportunity to capture and analyze users' spatial and temporal behaviors. Mining such behavior features is essential to social analysis and business intelligence. However, the complexity and incompleteness of check-in records bring challenges to achieve such a task. Different from the previous work on social behavior analysis, in this paper, we present a visual analytics system, Social Check-in Fingerprinting (Sci-Fin), to facilitate the analysis and visualization of social check-in data. We focus on three major components of user check-in data: location, activity, and profile. Visual fingerprints for location, activity, and profile are designed to intuitively represent the high-dimensional attributes. To visually mine and demonstrate the behavior features, we integrate WorldMapper and Voronoi Treemap into our glyph-like designs. Such visual fingerprint designs offer us the opportunity to summarize the interesting features and patterns from different check-in locations, activities and users (groups). We demonstrate the effectiveness and usability of our system by conducting extensive case studies on real check-in data collected from a popular microblogging service. Interesting findings are reported and discussed at last.

Nonlinear detection for a high rate extended binary phase shift keying system.

PubMed

Chen, Xian-Qing; Wu, Le-Nan

2013-03-28

The algorithm and the results of a nonlinear detector using a machine learning technique called support vector machine (SVM) on an efficient modulation system with high data rate and low energy consumption is presented in this paper. Simulation results showed that the performance achieved by the SVM detector is comparable to that of a conventional threshold decision (TD) detector. The two detectors detect the received signals together with the special impacting filter (SIF) that can improve the energy utilization efficiency. However, unlike the TD detector, the SVM detector concentrates not only on reducing the BER of the detector, but also on providing accurate posterior probability estimates (PPEs), which can be used as soft-inputs of the LDPC decoder. The complexity of this detector is considered in this paper by using four features and simplifying the decision function. In addition, a bandwidth efficient transmission is analyzed with both SVM and TD detector. The SVM detector is more robust to sampling rate than TD detector. We find that the SVM is suitable for extended binary phase shift keying (EBPSK) signal detection and can provide accurate posterior probability for LDPC decoding.

Nonlinear Detection for a High Rate Extended Binary Phase Shift Keying System

PubMed Central

Chen, Xian-Qing; Wu, Le-Nan

2013-01-01

The algorithm and the results of a nonlinear detector using a machine learning technique called support vector machine (SVM) on an efficient modulation system with high data rate and low energy consumption is presented in this paper. Simulation results showed that the performance achieved by the SVM detector is comparable to that of a conventional threshold decision (TD) detector. The two detectors detect the received signals together with the special impacting filter (SIF) that can improve the energy utilization efficiency. However, unlike the TD detector, the SVM detector concentrates not only on reducing the BER of the detector, but also on providing accurate posterior probability estimates (PPEs), which can be used as soft-inputs of the LDPC decoder. The complexity of this detector is considered in this paper by using four features and simplifying the decision function. In addition, a bandwidth efficient transmission is analyzed with both SVM and TD detector. The SVM detector is more robust to sampling rate than TD detector. We find that the SVM is suitable for extended binary phase shift keying (EBPSK) signal detection and can provide accurate posterior probability for LDPC decoding. PMID:23539034

Light-weight spherical mirrors for Cherenkov detectors

NASA Astrophysics Data System (ADS)

Cisbani, E.; Colilli, S.; Crateri, R.; Cusanno, F.; Fratoni, R.; Frullani, S.; Garibaldi, F.; Giuliani, F.; Gricia, M.; Iodice, M.; Iommi, R.; Lucentini, M.; Mostarda, A.; Pierangeli, L.; Santavenere, F.; Urciuoli, G. M.; De Leo, R.; Lagamba, L.; Nappi, E.; Braem, A.; Vernin, P.

2003-01-01

Light-weight spherical mirrors have been appositely designed and built for the gas threshold Cherenkov detectors of the two Hall A spectrometers. The mirrors are made of a 1 mm thick aluminized plexiglass sheet, reinforced by a rigid backing consisting of a phenolic honeycomb sandwiched between two carbon fiber mats epoxy glued. The produced mirrors have a thickness equivalent to 0.55% of radiation length, and an optical slope error of about 5.5 mrad. These characteristics make these mirrors suitable for the implementation in Cherenkov threshold detectors. Ways to improve the mirror features are also discussed in view of their possible employment in RICH detectors.

Learning and Recognition of Clothing Genres From Full-Body Images.

PubMed

Hidayati, Shintami C; You, Chuang-Wen; Cheng, Wen-Huang; Hua, Kai-Lung

2018-05-01

According to the theory of clothing design, the genres of clothes can be recognized based on a set of visually differentiable style elements, which exhibit salient features of visual appearance and reflect high-level fashion styles for better describing clothing genres. Instead of using less-discriminative low-level features or ambiguous keywords to identify clothing genres, we proposed a novel approach for automatically classifying clothing genres based on the visually differentiable style elements. A set of style elements, that are crucial for recognizing specific visual styles of clothing genres, were identified based on the clothing design theory. In addition, the corresponding salient visual features of each style element were identified and formulated with variables that can be computationally derived with various computer vision algorithms. To evaluate the performance of our algorithm, a dataset containing 3250 full-body shots crawled from popular online stores was built. Recognition results show that our proposed algorithms achieved promising overall precision, recall, and -score of 88.76%, 88.53%, and 88.64% for recognizing upperwear genres, and 88.21%, 88.17%, and 88.19% for recognizing lowerwear genres, respectively. The effectiveness of each style element and its visual features on recognizing clothing genres was demonstrated through a set of experiments involving different sets of style elements or features. In summary, our experimental results demonstrate the effectiveness of the proposed method in clothing genre recognition.

A scale-invariant keypoint detector in log-polar space

NASA Astrophysics Data System (ADS)

Tao, Tao; Zhang, Yun

2017-02-01

The scale-invariant feature transform (SIFT) algorithm is devised to detect keypoints via the difference of Gaussian (DoG) images. However, the DoG data lacks the high-frequency information, which can lead to a performance drop of the algorithm. To address this issue, this paper proposes a novel log-polar feature detector (LPFD) to detect scale-invariant blubs (keypoints) in log-polar space, which, in contrast, can retain all the image information. The algorithm consists of three components, viz. keypoint detection, descriptor extraction and descriptor matching. Besides, the algorithm is evaluated in detecting keypoints from the INRIA dataset by comparing with the SIFT algorithm and one of its fast versions, the speed up robust features (SURF) algorithm in terms of three performance measures, viz. correspondences, repeatability, correct matches and matching score.

How Object-Specific Are Object Files? Evidence for Integration by Location

ERIC Educational Resources Information Center

van Dam, Wessel O.; Hommel, Bernhard

2010-01-01

Given the distributed representation of visual features in the human brain, binding mechanisms are necessary to integrate visual information about the same perceptual event. It has been assumed that feature codes are bound into object files--pointers to the neural codes of the features of a given event. The present study investigated the…

Rotation invariant fast features for large-scale recognition

NASA Astrophysics Data System (ADS)

Takacs, Gabriel; Chandrasekhar, Vijay; Tsai, Sam; Chen, David; Grzeszczuk, Radek; Girod, Bernd

2012-10-01

We present an end-to-end feature description pipeline which uses a novel interest point detector and Rotation- Invariant Fast Feature (RIFF) descriptors. The proposed RIFF algorithm is 15× faster than SURF1 while producing large-scale retrieval results that are comparable to SIFT.2 Such high-speed features benefit a range of applications from Mobile Augmented Reality (MAR) to web-scale image retrieval and analysis.

Visual Aggregate Analysis of Eligibility Features of Clinical Trials

PubMed Central

He, Zhe; Carini, Simona; Sim, Ida; Weng, Chunhua

2015-01-01

Objective To develop a method for profiling the collective populations targeted for recruitment by multiple clinical studies addressing the same medical condition using one eligibility feature each time. Methods Using a previously published database COMPACT as the backend, we designed a scalable method for visual aggregate analysis of clinical trial eligibility features. This method consists of four modules for eligibility feature frequency analysis, query builder, distribution analysis, and visualization, respectively. This method is capable of analyzing (1) frequently used qualitative and quantitative features for recruiting subjects for a selected medical condition, (2) distribution of study enrollment on consecutive value points or value intervals of each quantitative feature, and (3) distribution of studies on the boundary values, permissible value ranges, and value range widths of each feature. All analysis results were visualized using Google Charts API. Five recruited potential users assessed the usefulness of this method for identifying common patterns in any selected eligibility feature for clinical trial participant selection. Results We implemented this method as a Web-based analytical system called VITTA (Visual Analysis Tool of Clinical Study Target Populations). We illustrated the functionality of VITTA using two sample queries involving quantitative features BMI and HbA1c for conditions “hypertension” and “Type 2 diabetes”, respectively. The recruited potential users rated the user-perceived usefulness of VITTA with an average score of 86.4/100. Conclusions We contributed a novel aggregate analysis method to enable the interrogation of common patterns in quantitative eligibility criteria and the collective target populations of multiple related clinical studies. A larger-scale study is warranted to formally assess the usefulness of VITTA among clinical investigators and sponsors in various therapeutic areas. PMID:25615940

Visual aggregate analysis of eligibility features of clinical trials.

PubMed

He, Zhe; Carini, Simona; Sim, Ida; Weng, Chunhua

2015-04-01

To develop a method for profiling the collective populations targeted for recruitment by multiple clinical studies addressing the same medical condition using one eligibility feature each time. Using a previously published database COMPACT as the backend, we designed a scalable method for visual aggregate analysis of clinical trial eligibility features. This method consists of four modules for eligibility feature frequency analysis, query builder, distribution analysis, and visualization, respectively. This method is capable of analyzing (1) frequently used qualitative and quantitative features for recruiting subjects for a selected medical condition, (2) distribution of study enrollment on consecutive value points or value intervals of each quantitative feature, and (3) distribution of studies on the boundary values, permissible value ranges, and value range widths of each feature. All analysis results were visualized using Google Charts API. Five recruited potential users assessed the usefulness of this method for identifying common patterns in any selected eligibility feature for clinical trial participant selection. We implemented this method as a Web-based analytical system called VITTA (Visual Analysis Tool of Clinical Study Target Populations). We illustrated the functionality of VITTA using two sample queries involving quantitative features BMI and HbA1c for conditions "hypertension" and "Type 2 diabetes", respectively. The recruited potential users rated the user-perceived usefulness of VITTA with an average score of 86.4/100. We contributed a novel aggregate analysis method to enable the interrogation of common patterns in quantitative eligibility criteria and the collective target populations of multiple related clinical studies. A larger-scale study is warranted to formally assess the usefulness of VITTA among clinical investigators and sponsors in various therapeutic areas. Copyright © 2015 Elsevier Inc. All rights reserved.

Neural evidence reveals the rapid effects of reward history on selective attention.

PubMed

MacLean, Mary H; Giesbrecht, Barry

2015-05-05

Selective attention is often framed as being primarily driven by two factors: task-relevance and physical salience. However, factors like selection and reward history, which are neither currently task-relevant nor physically salient, can reliably and persistently influence visual selective attention. The current study investigated the nature of the persistent effects of irrelevant, physically non-salient, reward-associated features. These features affected one of the earliest reliable neural indicators of visual selective attention in humans, the P1 event-related potential, measured one week after the reward associations were learned. However, the effects of reward history were moderated by current task demands. The modulation of visually evoked activity supports the hypothesis that reward history influences the innate salience of reward associated features, such that even when no longer relevant, nor physically salient, these features have a rapid, persistent, and robust effect on early visual selective attention. Copyright © 2015 Elsevier B.V. All rights reserved.

A computational visual saliency model based on statistics and machine learning.

PubMed

Lin, Ru-Je; Lin, Wei-Song

2014-08-01

Identifying the type of stimuli that attracts human visual attention has been an appealing topic for scientists for many years. In particular, marking the salient regions in images is useful for both psychologists and many computer vision applications. In this paper, we propose a computational approach for producing saliency maps using statistics and machine learning methods. Based on four assumptions, three properties (Feature-Prior, Position-Prior, and Feature-Distribution) can be derived and combined by a simple intersection operation to obtain a saliency map. These properties are implemented by a similarity computation, support vector regression (SVR) technique, statistical analysis of training samples, and information theory using low-level features. This technique is able to learn the preferences of human visual behavior while simultaneously considering feature uniqueness. Experimental results show that our approach performs better in predicting human visual attention regions than 12 other models in two test databases. © 2014 ARVO.

Perceptual Discrimination of Basic Object Features Is Not Facilitated When Priming Stimuli Are Prevented From Reaching Awareness by Means of Visual Masking

PubMed Central

Peel, Hayden J.; Sperandio, Irene; Laycock, Robin; Chouinard, Philippe A.

2018-01-01

Our understanding of how form, orientation and size are processed within and outside of awareness is limited and requires further investigation. Therefore, we investigated whether or not the visual discrimination of basic object features can be influenced by subliminal processing of stimuli presented beforehand. Visual masking was used to render stimuli perceptually invisible. Three experiments examined if visible and invisible primes could facilitate the subsequent feature discrimination of visible targets. The experiments differed in the kind of perceptual discrimination that participants had to make. Namely, participants were asked to discriminate visual stimuli on the basis of their form, orientation, or size. In all three experiments, we demonstrated reliable priming effects when the primes were visible but not when the primes were made invisible. Our findings underscore the importance of conscious awareness in facilitating the perceptual discrimination of basic object features. PMID:29725292

Perceptual Discrimination of Basic Object Features Is Not Facilitated When Priming Stimuli Are Prevented From Reaching Awareness by Means of Visual Masking.

PubMed

Peel, Hayden J; Sperandio, Irene; Laycock, Robin; Chouinard, Philippe A

2018-01-01

Our understanding of how form, orientation and size are processed within and outside of awareness is limited and requires further investigation. Therefore, we investigated whether or not the visual discrimination of basic object features can be influenced by subliminal processing of stimuli presented beforehand. Visual masking was used to render stimuli perceptually invisible. Three experiments examined if visible and invisible primes could facilitate the subsequent feature discrimination of visible targets. The experiments differed in the kind of perceptual discrimination that participants had to make. Namely, participants were asked to discriminate visual stimuli on the basis of their form, orientation, or size. In all three experiments, we demonstrated reliable priming effects when the primes were visible but not when the primes were made invisible. Our findings underscore the importance of conscious awareness in facilitating the perceptual discrimination of basic object features.

Neuronal population coding of perceived and memorized visual features in the lateral prefrontal cortex

PubMed Central

Mendoza-Halliday, Diego; Martinez-Trujillo, Julio C.

2017-01-01

The primate lateral prefrontal cortex (LPFC) encodes visual stimulus features while they are perceived and while they are maintained in working memory. However, it remains unclear whether perceived and memorized features are encoded by the same or different neurons and population activity patterns. Here we record LPFC neuronal activity while monkeys perceive the motion direction of a stimulus that remains visually available, or memorize the direction if the stimulus disappears. We find neurons with a wide variety of combinations of coding strength for perceived and memorized directions: some neurons encode both to similar degrees while others preferentially or exclusively encode either one. Reading out the combined activity of all neurons, a machine-learning algorithm reliably decode the motion direction and determine whether it is perceived or memorized. Our results indicate that a functionally diverse population of LPFC neurons provides a substrate for discriminating between perceptual and mnemonic representations of visual features. PMID:28569756

Fire protection for launch facilities using machine vision fire detection

NASA Astrophysics Data System (ADS)

Schwartz, Douglas B.

1993-02-01

Fire protection of critical space assets, including launch and fueling facilities and manned flight hardware, demands automatic sensors for continuous monitoring, and in certain high-threat areas, fast-reacting automatic suppression systems. Perhaps the most essential characteristic for these fire detection and suppression systems is high reliability; in other words, fire detectors should alarm only on actual fires and not be falsely activated by extraneous sources. Existing types of fire detectors have been greatly improved in the past decade; however, fundamental limitations of their method of operation leaves open a significant possibility of false alarms and restricts their usefulness. At the Civil Engineering Laboratory at Tyndall Air Force Base in Florida, a new type of fire detector is under development which 'sees' a fire visually, like a human being, and makes a reliable decision based on known visual characteristics of flames. Hardware prototypes of the Machine Vision (MV) Fire Detection System have undergone live fire tests and demonstrated extremely high accuracy in discriminating actual fires from false alarm sources. In fact, this technology promises to virtually eliminate false activations. This detector could be used to monitor fueling facilities, launch towers, clean rooms, and other high-value and high-risk areas. Applications can extend to space station and in-flight shuttle operations as well; fiber optics and remote camera heads enable the system to see around obstructed areas and crew compartments. The capability of the technology to distinguish fires means that fire detection can be provided even during maintenance operations, such as welding.

Application of CORSIKA Simulation Code to Study Lateral and Longitudinal Distribution of Fluorescence Light in Cosmic Ray Extensive Air Showers

NASA Astrophysics Data System (ADS)

Bagheri, Zahra; Davoudifar, Pantea; Rastegarzadeh, Gohar; Shayan, Milad

2017-03-01

In this paper, we used CORSIKA code to understand the characteristics of cosmic ray induced showers at extremely high energy as a function of energy, detector distance to shower axis, number, and density of secondary charged particles and the nature particle producing the shower. Based on the standard properties of the atmosphere, lateral and longitudinal development of the shower for photons and electrons has been investigated. Fluorescent light has been collected by the detector for protons, helium, oxygen, silicon, calcium and iron primary cosmic rays in different energies. So we have obtained a number of electrons per unit area, distance to the shower axis, shape function of particles density, percentage of fluorescent light, lateral distribution of energy dissipated in the atmosphere and visual field angle of detector as well as size of the shower image. We have also shown that location of highest percentage of fluorescence light is directly proportional to atomic number of elements. Also we have shown when the distance from shower axis increases and the shape function of particles density decreases severely. At the first stages of development, shower axis distance from detector is high and visual field angle is small; then with shower moving toward the Earth, angle increases. Overall, in higher energies, the fluorescent light method has more efficiency. The paper provides standard calibration lines for high energy showers which can be used to determine the nature of the particles.

Fire protection for launch facilities using machine vision fire detection

NASA Technical Reports Server (NTRS)

Schwartz, Douglas B.

1993-01-01

Fire protection of critical space assets, including launch and fueling facilities and manned flight hardware, demands automatic sensors for continuous monitoring, and in certain high-threat areas, fast-reacting automatic suppression systems. Perhaps the most essential characteristic for these fire detection and suppression systems is high reliability; in other words, fire detectors should alarm only on actual fires and not be falsely activated by extraneous sources. Existing types of fire detectors have been greatly improved in the past decade; however, fundamental limitations of their method of operation leaves open a significant possibility of false alarms and restricts their usefulness. At the Civil Engineering Laboratory at Tyndall Air Force Base in Florida, a new type of fire detector is under development which 'sees' a fire visually, like a human being, and makes a reliable decision based on known visual characteristics of flames. Hardware prototypes of the Machine Vision (MV) Fire Detection System have undergone live fire tests and demonstrated extremely high accuracy in discriminating actual fires from false alarm sources. In fact, this technology promises to virtually eliminate false activations. This detector could be used to monitor fueling facilities, launch towers, clean rooms, and other high-value and high-risk areas. Applications can extend to space station and in-flight shuttle operations as well; fiber optics and remote camera heads enable the system to see around obstructed areas and crew compartments. The capability of the technology to distinguish fires means that fire detection can be provided even during maintenance operations, such as welding.

Characterization of Stress in Thallium Bromide Devices

NASA Astrophysics Data System (ADS)

Datta, Amlan; Motakef, Shariar

2015-04-01

Thallium bromide (TlBr) is a wide bandgap, compound semiconductor with high gamma-ray stopping power and promising physical properties. Several surface modification techniques have been demonstrated to increase the lifetime of TlBr devices at room temperature. However, absence of reproducibility in the performance of TlBr detectors (even with low ionic conduction at -20°C) suggests presence of unexplored bulk phenomena. Stress in the TlBr crystal due to various intrinsic (e.g. grain boundaries and dislocations networks) in conjunction with external factors such as thermal, mechanical, and electrical loadings explains detector-to-detector variations. Photoelasticity and opto-electrical techniques were applied to visualize and qualitatively correlate the device performance with stress. Changes in stress patterns with variations in ambient temperature were clearly demonstrated. Electric field fluctuations in TlBr detectors with time were for the first time observed using the Pockels effect.

Relationship between visual binding, reentry and awareness.

PubMed

Koivisto, Mika; Silvanto, Juha

2011-12-01

Visual feature binding has been suggested to depend on reentrant processing. We addressed the relationship between binding, reentry, and visual awareness by asking the participants to discriminate the color and orientation of a colored bar (presented either alone or simultaneously with a white distractor bar) and to report their phenomenal awareness of the target features. The success of reentry was manipulated with object substitution masking and backward masking. The results showed that late reentrant processes are necessary for successful binding but not for phenomenal awareness of the bound features. Binding errors were accompanied by phenomenal awareness of the misbound feature conjunctions, demonstrating that they were experienced as real properties of the stimuli (i.e., illusory conjunctions). Our results suggest that early preattentive binding and local recurrent processing enable features to reach phenomenal awareness, while later attention-related reentrant iterations modulate the way in which the features are bound and experienced in awareness. Copyright © 2011 Elsevier Inc. All rights reserved.

Evaluation of position-estimation methods applied to CZT-based photon-counting detectors for dedicated breast CT

PubMed Central

Makeev, Andrey; Clajus, Martin; Snyder, Scott; Wang, Xiaolang; Glick, Stephen J.

2015-01-01

Abstract. Semiconductor photon-counting detectors based on high atomic number, high density materials [cadmium zinc telluride (CZT)/cadmium telluride (CdTe)] for x-ray computed tomography (CT) provide advantages over conventional energy-integrating detectors, including reduced electronic and Swank noise, wider dynamic range, capability of spectral CT, and improved signal-to-noise ratio. Certain CT applications require high spatial resolution. In breast CT, for example, visualization of microcalcifications and assessment of tumor microvasculature after contrast enhancement require resolution on the order of 100  μm. A straightforward approach to increasing spatial resolution of pixellated CZT-based radiation detectors by merely decreasing the pixel size leads to two problems: (1) fabricating circuitry with small pixels becomes costly and (2) inter-pixel charge spreading can obviate any improvement in spatial resolution. We have used computer simulations to investigate position estimation algorithms that utilize charge sharing to achieve subpixel position resolution. To study these algorithms, we model a simple detector geometry with a 5×5 array of 200  μm pixels, and use a conditional probability function to model charge transport in CZT. We used COMSOL finite element method software to map the distribution of charge pulses and the Monte Carlo package PENELOPE for simulating fluorescent radiation. Performance of two x-ray interaction position estimation algorithms was evaluated: the method of maximum-likelihood estimation and a fast, practical algorithm that can be implemented in a readout application-specific integrated circuit and allows for identification of a quadrant of the pixel in which the interaction occurred. Both methods demonstrate good subpixel resolution; however, their actual efficiency is limited by the presence of fluorescent K-escape photons. Current experimental breast CT systems typically use detectors with a pixel size of 194  μm, with 2×2 binning during the acquisition giving an effective pixel size of 388  μm. Thus, it would be expected that the position estimate accuracy reported in this study would improve detection and visualization of microcalcifications as compared to that with conventional detectors. PMID:26158095

Evaluation of position-estimation methods applied to CZT-based photon-counting detectors for dedicated breast CT.

PubMed

Makeev, Andrey; Clajus, Martin; Snyder, Scott; Wang, Xiaolang; Glick, Stephen J

2015-04-01

Semiconductor photon-counting detectors based on high atomic number, high density materials [cadmium zinc telluride (CZT)/cadmium telluride (CdTe)] for x-ray computed tomography (CT) provide advantages over conventional energy-integrating detectors, including reduced electronic and Swank noise, wider dynamic range, capability of spectral CT, and improved signal-to-noise ratio. Certain CT applications require high spatial resolution. In breast CT, for example, visualization of microcalcifications and assessment of tumor microvasculature after contrast enhancement require resolution on the order of [Formula: see text]. A straightforward approach to increasing spatial resolution of pixellated CZT-based radiation detectors by merely decreasing the pixel size leads to two problems: (1) fabricating circuitry with small pixels becomes costly and (2) inter-pixel charge spreading can obviate any improvement in spatial resolution. We have used computer simulations to investigate position estimation algorithms that utilize charge sharing to achieve subpixel position resolution. To study these algorithms, we model a simple detector geometry with a [Formula: see text] array of [Formula: see text] pixels, and use a conditional probability function to model charge transport in CZT. We used COMSOL finite element method software to map the distribution of charge pulses and the Monte Carlo package PENELOPE for simulating fluorescent radiation. Performance of two x-ray interaction position estimation algorithms was evaluated: the method of maximum-likelihood estimation and a fast, practical algorithm that can be implemented in a readout application-specific integrated circuit and allows for identification of a quadrant of the pixel in which the interaction occurred. Both methods demonstrate good subpixel resolution; however, their actual efficiency is limited by the presence of fluorescent [Formula: see text]-escape photons. Current experimental breast CT systems typically use detectors with a pixel size of [Formula: see text], with [Formula: see text] binning during the acquisition giving an effective pixel size of [Formula: see text]. Thus, it would be expected that the position estimate accuracy reported in this study would improve detection and visualization of microcalcifications as compared to that with conventional detectors.

Preattentive binding of auditory and visual stimulus features.

PubMed

Winkler, István; Czigler, István; Sussman, Elyse; Horváth, János; Balázs, Lászlo

2005-02-01

We investigated the role of attention in feature binding in the auditory and the visual modality. One auditory and one visual experiment used the mismatch negativity (MMN and vMMN, respectively) event-related potential to index the memory representations created from stimulus sequences, which were either task-relevant and, therefore, attended or task-irrelevant and ignored. In the latter case, the primary task was a continuous demanding within-modality task. The test sequences were composed of two frequently occurring stimuli, which differed from each other in two stimulus features (standard stimuli) and two infrequently occurring stimuli (deviants), which combined one feature from one standard stimulus with the other feature of the other standard stimulus. Deviant stimuli elicited MMN responses of similar parameters across the different attentional conditions. These results suggest that the memory representations involved in the MMN deviance detection response encoded the frequently occurring feature combinations whether or not the test sequences were attended. A possible alternative to the memory-based interpretation of the visual results, the elicitation of the McCollough color-contingent aftereffect, was ruled out by the results of our third experiment. The current results are compared with those supporting the attentive feature integration theory. We conclude that (1) with comparable stimulus paradigms, similar results have been obtained in the two modalities, (2) there exist preattentive processes of feature binding, however, (3) conjoining features within rich arrays of objects under time pressure and/or longterm retention of the feature-conjoined memory representations may require attentive processes.

Automatic Sea Bird Detection from High Resolution Aerial Imagery

NASA Astrophysics Data System (ADS)

Mader, S.; Grenzdörffer, G. J.

2016-06-01

Great efforts are presently taken in the scientific community to develop computerized and (fully) automated image processing methods allowing for an efficient and automatic monitoring of sea birds and marine mammals in ever-growing amounts of aerial imagery. Currently the major part of the processing, however, is still conducted by especially trained professionals, visually examining the images and detecting and classifying the requested subjects. This is a very tedious task, particularly when the rate of void images regularly exceeds the mark of 90%. In the content of this contribution we will present our work aiming to support the processing of aerial images by modern methods from the field of image processing. We will especially focus on the combination of local, region-based feature detection and piecewise global image segmentation for automatic detection of different sea bird species. Large image dimensions resulting from the use of medium and large-format digital cameras in aerial surveys inhibit the applicability of image processing methods based on global operations. In order to efficiently handle those image sizes and to nevertheless take advantage of globally operating segmentation algorithms, we will describe the combined usage of a simple performant feature detector based on local operations on the original image with a complex global segmentation algorithm operating on extracted sub-images. The resulting exact segmentation of possible candidates then serves as a basis for the determination of feature vectors for subsequent elimination of false candidates and for classification tasks.

Using Anisotropic 3D Minkowski Functionals for Trabecular Bone Characterization and Biomechanical Strength Prediction in Proximal Femur Specimens

PubMed Central

Nagarajan, Mahesh B.; De, Titas; Lochmüller, Eva-Maria; Eckstein, Felix; Wismüller, Axel

2017-01-01

The ability of Anisotropic Minkowski Functionals (AMFs) to capture local anisotropy while evaluating topological properties of the underlying gray-level structures has been previously demonstrated. We evaluate the ability of this approach to characterize local structure properties of trabecular bone micro-architecture in ex vivo proximal femur specimens, as visualized on multi-detector CT, for purposes of biomechanical bone strength prediction. To this end, volumetric AMFs were computed locally for each voxel of volumes of interest (VOI) extracted from the femoral head of 146 specimens. The local anisotropy captured by such AMFs was quantified using a fractional anisotropy measure; the magnitude and direction of anisotropy at every pixel was stored in histograms that served as a feature vectors that characterized the VOIs. A linear multi-regression analysis algorithm was used to predict the failure load (FL) from the feature sets; the predicted FL was compared to the true FL determined through biomechanical testing. The prediction performance was measured by the root mean square error (RMSE) for each feature set. The best prediction performance was obtained from the fractional anisotropy histogram of AMF Euler Characteristic (RMSE = 1.01 ± 0.13), which was significantly better than MDCT-derived mean BMD (RMSE = 1.12 ± 0.16, p<0.05). We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding regional trabecular bone quality and contribute to improved bone strength prediction, which is important for improving the clinical assessment of osteoporotic fracture risk. PMID:29170581

Multi-kernel aggregation of local and global features in long-wave infrared for detection of SWAT teams in challenging environments

NASA Astrophysics Data System (ADS)

Arya, Ankit S.; Anderson, Derek T.; Bethel, Cindy L.; Carruth, Daniel

2013-05-01

A vision system was designed for people detection to provide support to SWAT team members operating in challenging environments such as low-to-no light, smoke, etc. When the vision system is mounted on a mobile robot platform: it will enable the robot to function as an effective member of the SWAT team; to provide surveillance information; to make first contact with suspects; and provide safe entry for team members. The vision task is challenging because SWAT team members are typically concealed, carry various equipment such as shields, and perform tactical and stealthy maneuvers. Occlusion is a particular challenge because team members operate in close proximity to one another. An uncooled electro-opticaljlong wav e infrared (EO/ LWIR) camera, 7.5 to 13.5 m, was used. A unique thermal dataset was collected of SWAT team members from multiple teams performing tactical maneuvers during monthly training exercises. Our approach consisted of two stages: an object detector trained on people to find candidate windows, and a secondary feature extraction, multi-kernel (MK) aggregation and classification step to distinguish between SWAT team members and civilians. Two types of thermal features, local and global, are presented based on ma ximally stable extremal region (MSER) blob detection. Support vector machine (SVM) classification results of approximately [70, 93]% for SWAT team member detection are reported based on the exploration of different combinations of visual information in terms of training data.

X-ray characterization of a multichannel smart-pixel array detector.

PubMed

Ross, Steve; Haji-Sheikh, Michael; Huntington, Andrew; Kline, David; Lee, Adam; Li, Yuelin; Rhee, Jehyuk; Tarpley, Mary; Walko, Donald A; Westberg, Gregg; Williams, George; Zou, Haifeng; Landahl, Eric

2016-01-01

The Voxtel VX-798 is a prototype X-ray pixel array detector (PAD) featuring a silicon sensor photodiode array of 48 × 48 pixels, each 130 µm × 130 µm × 520 µm thick, coupled to a CMOS readout application specific integrated circuit (ASIC). The first synchrotron X-ray characterization of this detector is presented, and its ability to selectively count individual X-rays within two independent arrival time windows, a programmable energy range, and localized to a single pixel is demonstrated. During our first trial run at Argonne National Laboratory's Advance Photon Source, the detector achieved a 60 ns gating time and 700 eV full width at half-maximum energy resolution in agreement with design parameters. Each pixel of the PAD holds two independent digital counters, and the discriminator for X-ray energy features both an upper and lower threshold to window the energy of interest discarding unwanted background. This smart-pixel technology allows energy and time resolution to be set and optimized in software. It is found that the detector linearity follows an isolated dead-time model, implying that megahertz count rates should be possible in each pixel. Measurement of the line and point spread functions showed negligible spatial blurring. When combined with the timing structure of the synchrotron storage ring, it is demonstrated that the area detector can perform both picosecond time-resolved X-ray diffraction and fluorescence spectroscopy measurements.

Android application for handwriting segmentation using PerTOHS theory

NASA Astrophysics Data System (ADS)

Akouaydi, Hanen; Njah, Sourour; Alimi, Adel M.

2017-03-01

The paper handles the problem of segmentation of handwriting on mobile devices. Many applications have been developed in order to facilitate the recognition of handwriting and to skip the limited numbers of keys in keyboards and try to introduce a space of drawing for writing instead of using keyboards. In this one, we will present a mobile theory for the segmentation of for handwriting uses PerTOHS theory, Perceptual Theory of On line Handwriting Segmentation, where handwriting is defined as a sequence of elementary and perceptual codes. In fact, the theory analyzes the written script and tries to learn the handwriting visual codes features in order to generate new ones via the generated perceptual sequences. To get this classification we try to apply the Beta-elliptic model, fuzzy detector and also genetic algorithms in order to get the EPCs (Elementary Perceptual Codes) and GPCs (Global Perceptual Codes) that composed the script. So, we will present our Android application M-PerTOHS for segmentation of handwriting.

Multiplexing of Motor Information in the Discharge of a Collision Detecting Neuron during Escape Behaviors

PubMed Central

Fotowat, Haleh; Harrison, Reid R; Gabbiani, Fabrizio

2010-01-01

Locusts possess an identified neuron, the descending contralateral movement detector (DCMD), conveying visual information about impending collision from the brain to thoracic motor centers. We built a telemetry system to simultaneously record, in freely behaving animals, the activity of the DCMD and of motoneurons involved in jump execution. Co-contraction of antagonistic leg muscles, a required preparatory phase, was triggered after the DCMD firing rate crossed a threshold. Thereafter, the number of DCMD spikes predicted precisely motoneuron activity and jump occurrence. Additionally, the time of DCMD peak firing rate predicted that of jump. Ablation experiments suggest that the DCMD, together with a nearly identical ipsilateral descending neuron, is responsible for the timely execution of the escape. Thus, three distinct features that are multiplexed in a single neuron’s sensory response to impending collision – firing rate threshold, peak firing time, and spike count – likely control three distinct motor aspects of escape behaviors. PMID:21220105

Direct Visualization of Local Electromagnetic Field Structures by Scanning Transmission Electron Microscopy.

PubMed

Shibata, Naoya; Findlay, Scott D; Matsumoto, Takao; Kohno, Yuji; Seki, Takehito; Sánchez-Santolino, Gabriel; Ikuhara, Yuichi

2017-07-18

The functional properties of materials and devices are critically determined by the electromagnetic field structures formed inside them, especially at nanointerface and surface regions, because such structures are strongly associated with the dynamics of electrons, holes and ions. To understand the fundamental origin of many exotic properties in modern materials and devices, it is essential to directly characterize local electromagnetic field structures at such defect regions, even down to atomic dimensions. In recent years, rapid progress in the development of high-speed area detectors for aberration-corrected scanning transmission electron microscopy (STEM) with sub-angstrom spatial resolution has opened new possibilities to directly image such electromagnetic field structures at very high-resolution. In this Account, we give an overview of our recent development of differential phase contrast (DPC) microscopy for aberration-corrected STEM and its application to many materials problems. In recent years, we have developed segmented-type STEM detectors which divide the detector plane into 16 segments and enable simultaneous imaging of 16 STEM images which are sensitive to the positions and angles of transmitted/scattered electrons on the detector plane. These detectors also have atomic-resolution imaging capability. Using these segmented-type STEM detectors, we show DPC STEM imaging to be a very powerful tool for directly imaging local electromagnetic field structures in materials and devices in real space. For example, DPC STEM can clearly visualize the local electric field variation due to the abrupt potential change across a p-n junction in a GaAs semiconductor, which cannot be observed by normal in-focus bright-field or annular type dark-field STEM imaging modes. DPC STEM is also very effective for imaging magnetic field structures in magnetic materials, such as magnetic domains and skyrmions. Moreover, real-time imaging of electromagnetic field structures can now be realized through very fast data acquisition, processing, and reconstruction algorithms. If we use DPC STEM for atomic-resolution imaging using a sub-angstrom size electron probe, it has been shown that we can directly observe the atomic electric field inside atoms within crystals and even inside single atoms, the field between the atomic nucleus and the surrounding electron cloud, which possesses information about the atomic species, local chemical bonding and charge redistribution between bonded atoms. This possibility may open an alternative way for directly visualizing atoms and nanostructures, that is, seeing atoms as an entity of electromagnetic fields that reflect the intra- and interatomic electronic structures. In this Account, the current status of aberration-corrected DPC STEM is highlighted, along with some applications in real material and device studies.

How many CT detector rows are necessary to perform adequate three dimensional visualization?

PubMed

Fischer, Lars; Tetzlaff, Ralf; Schöbinger, Max; Radeleff, Boris; Bruckner, Thomas; Meinzer, H P; Büchler, M W; Schemmer, Peter

2010-06-01

The technical development of computer tomography (CT) imaging has experienced great progress. As consequence, CT data to be used for 3D visualization is not only based on 4 row CTs and 16 row CTs but also on 64 row CTs, respectively. The main goal of this study was to examine whether the increased amount of CT detector rows is correlated with improved quality of the 3D images. All CTs were acquired during routinely performed preoperative evaluation. Overall, there were 12 data sets based on 4 detector row CT, 12 data sets based on 16 detector row CT, and 10 data sets based on 64 detector row CT. Imaging data sets were transferred to the DKFZ Heidelberg using the CHILI teleradiology system. For the analysis all CT scans were examined in a blinded fashion, i.e. both the name of the patient as well as the name of the CT brand were erased. For analysis, the time for segmentation of liver, both portal and hepatic veins as well as the branching depth of portal veins and hepatic veins was recorded automatically. In addition, all results were validated in a blinded fashion based on given quality index. Segmentation of the liver was performed in significantly shorter time (p<0.01, Kruskal-Wallis test) in the 16 row CT (median 479 s) compared to 4 row CT (median 611 s), and 64 row CT (median 670 s), respectively. The branching depth of the portal vein did not differ significantly among the 3 different data sets (p=0.37, Kruskal-Wallis test). However, the branching depth of the hepatic veins was significantly better (p=0.028, Kruskal-Wallis test) in the 4 row CT and 16 row CT compared to 64 row CT. The grading of the quality index was not statistically different for portal veins and hepatic veins (p=0.80, Kruskal-Wallis test). Even though the total quality index was better for the vessel tree based on 64 row CT data sets (mean scale 2.6) compared to 4 CT row data (mean scale 3.25) and 16 row CT data (mean scale 3.0), these differences did not reach statistical difference (p=0.53, Kruskal-Wallis test). Even though 3D visualization is useful in operation planning, the quality of the 3D images appears to be not dependent of the number of CT detector rows. Copyright (c) 2009. Published by Elsevier Ireland Ltd.

iview: an interactive WebGL visualizer for protein-ligand complex.

PubMed

Li, Hongjian; Leung, Kwong-Sak; Nakane, Takanori; Wong, Man-Hon

2014-02-25

Visualization of protein-ligand complex plays an important role in elaborating protein-ligand interactions and aiding novel drug design. Most existing web visualizers either rely on slow software rendering, or lack virtual reality support. The vital feature of macromolecular surface construction is also unavailable. We have developed iview, an easy-to-use interactive WebGL visualizer of protein-ligand complex. It exploits hardware acceleration rather than software rendering. It features three special effects in virtual reality settings, namely anaglyph, parallax barrier and oculus rift, resulting in visually appealing identification of intermolecular interactions. It supports four surface representations including Van der Waals surface, solvent excluded surface, solvent accessible surface and molecular surface. Moreover, based on the feature-rich version of iview, we have also developed a neat and tailor-made version specifically for our istar web platform for protein-ligand docking purpose. This demonstrates the excellent portability of iview. Using innovative 3D techniques, we provide a user friendly visualizer that is not intended to compete with professional visualizers, but to enable easy accessibility and platform independence.

Decoding the time-course of object recognition in the human brain: From visual features to categorical decisions.

PubMed

Contini, Erika W; Wardle, Susan G; Carlson, Thomas A

2017-10-01

Visual object recognition is a complex, dynamic process. Multivariate pattern analysis methods, such as decoding, have begun to reveal how the brain processes complex visual information. Recently, temporal decoding methods for EEG and MEG have offered the potential to evaluate the temporal dynamics of object recognition. Here we review the contribution of M/EEG time-series decoding methods to understanding visual object recognition in the human brain. Consistent with the current understanding of the visual processing hierarchy, low-level visual features dominate decodable object representations early in the time-course, with more abstract representations related to object category emerging later. A key finding is that the time-course of object processing is highly dynamic and rapidly evolving, with limited temporal generalisation of decodable information. Several studies have examined the emergence of object category structure, and we consider to what degree category decoding can be explained by sensitivity to low-level visual features. Finally, we evaluate recent work attempting to link human behaviour to the neural time-course of object processing. Copyright © 2017 Elsevier Ltd. All rights reserved.

Stimulus Dependency of Object-Evoked Responses in Human Visual Cortex: An Inverse Problem for Category Specificity

PubMed Central

Graewe, Britta; De Weerd, Peter; Farivar, Reza; Castelo-Branco, Miguel

2012-01-01

Many studies have linked the processing of different object categories to specific event-related potentials (ERPs) such as the face-specific N170. Despite reports showing that object-related ERPs are influenced by visual stimulus features, there is consensus that these components primarily reflect categorical aspects of the stimuli. Here, we re-investigated this idea by systematically measuring the effects of visual feature manipulations on ERP responses elicited by both structure-from-motion (SFM)-defined and luminance-defined object stimuli. SFM objects elicited a novel component at 200–250 ms (N250) over parietal and posterior temporal sites. We found, however, that the N250 amplitude was unaffected by restructuring SFM stimuli into meaningless objects based on identical visual cues. This suggests that this N250 peak was not uniquely linked to categorical aspects of the objects, but is strongly determined by visual stimulus features. We provide strong support for this hypothesis by parametrically manipulating the depth range of both SFM- and luminance-defined object stimuli and showing that the N250 evoked by SFM stimuli as well as the well-known N170 to static faces were sensitive to this manipulation. Importantly, this effect could not be attributed to compromised object categorization in low depth stimuli, confirming a strong impact of visual stimulus features on object-related ERP signals. As ERP components linked with visual categorical object perception are likely determined by multiple stimulus features, this creates an interesting inverse problem when deriving specific perceptual processes from variations in ERP components. PMID:22363479

Stimulus dependency of object-evoked responses in human visual cortex: an inverse problem for category specificity.

PubMed

Graewe, Britta; De Weerd, Peter; Farivar, Reza; Castelo-Branco, Miguel

2012-01-01

Many studies have linked the processing of different object categories to specific event-related potentials (ERPs) such as the face-specific N170. Despite reports showing that object-related ERPs are influenced by visual stimulus features, there is consensus that these components primarily reflect categorical aspects of the stimuli. Here, we re-investigated this idea by systematically measuring the effects of visual feature manipulations on ERP responses elicited by both structure-from-motion (SFM)-defined and luminance-defined object stimuli. SFM objects elicited a novel component at 200-250 ms (N250) over parietal and posterior temporal sites. We found, however, that the N250 amplitude was unaffected by restructuring SFM stimuli into meaningless objects based on identical visual cues. This suggests that this N250 peak was not uniquely linked to categorical aspects of the objects, but is strongly determined by visual stimulus features. We provide strong support for this hypothesis by parametrically manipulating the depth range of both SFM- and luminance-defined object stimuli and showing that the N250 evoked by SFM stimuli as well as the well-known N170 to static faces were sensitive to this manipulation. Importantly, this effect could not be attributed to compromised object categorization in low depth stimuli, confirming a strong impact of visual stimulus features on object-related ERP signals. As ERP components linked with visual categorical object perception are likely determined by multiple stimulus features, this creates an interesting inverse problem when deriving specific perceptual processes from variations in ERP components.

The emergence of polychronization and feature binding in a spiking neural network model of the primate ventral visual system.

PubMed

Eguchi, Akihiro; Isbister, James B; Ahmad, Nasir; Stringer, Simon

2018-07-01

We present a hierarchical neural network model, in which subpopulations of neurons develop fixed and regularly repeating temporal chains of spikes (polychronization), which respond specifically to randomized Poisson spike trains representing the input training images. The performance is improved by including top-down and lateral synaptic connections, as well as introducing multiple synaptic contacts between each pair of pre- and postsynaptic neurons, with different synaptic contacts having different axonal delays. Spike-timing-dependent plasticity thus allows the model to select the most effective axonal transmission delay between neurons. Furthermore, neurons representing the binding relationship between low-level and high-level visual features emerge through visually guided learning. This begins to provide a way forward to solving the classic feature binding problem in visual neuroscience and leads to a new hypothesis concerning how information about visual features at every spatial scale may be projected upward through successive neuronal layers. We name this hypothetical upward projection of information the "holographic principle." (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Exploring EFL Students' Visual Literacy Skills and Global Understanding through Their Analysis of Louis Vuitton's Advertisement Featuring Mikhail Gorbachev

ERIC Educational Resources Information Center

Takaya, Kentei

2016-01-01

Visual literacy is an important skill for students to have in order to interpret embedded messages on signs and in advertisements successfully. As advertisements today tend to feature iconic people or events that shaped the modern world, it is crucial to develop students' visual literacy skills so they can comprehend the intended messages. This…

Generalization in visual recognition by the honeybee (Apis mellifera): a review and explanation.

PubMed

Horridge, Adrian

2009-06-01

During a century of studies on honeybee vision, generalization was the word for the acceptance of an unfamiliar pattern in the place of the training pattern, or the ability to learn a common factor in a group of related patterns. The ideas that bees generalize one pattern for another, detect similarity and differences, or form categories, were derived from the use of the same terms in the human cognitive sciences. Recent work now reveals a mechanistic explanation for bees. Small groups of ommatidia converge upon feature detectors that respond selectively to certain parameters that are in the pattern: modulation in the receptors, edge orientations, or to areas of black or colour. Within each local region of the eye the responses of each type of feature detector are summed to form a cue. The cues are therefore not in the pattern, but are local totals in the bee. Each cue has a quality, a quantity and a position on the eye, like a neuron response. This summation of edge detector responses destroys the local pattern based on edge orientation but preserves a coarse, sparse and simplified version of the panorama. In order of preference, the cues are: local receptor modulation, positions of well-separated black areas, a small black spot, colour and positions of the centres of each cue, radial edges, the averaged edge orientation and tangential edges. A pattern is always accepted by a trained bee that detects the expected cues in the expected places and no unexpected cues. The actual patterns are irrelevant. Therefore we have an explanation of generalization that is based on experimental testing of trained bees, not by analogy with other animals. Historically, generalization appeared when the training patterns were regularly interchanged to make the bees examine them. This strategy forced the bees to ignore parameters outside the training pattern, so that learning was restricted to one local eye region. This in turn limited the memory to one cue of each type, so that recognition was ambiguous because the cues were insufficient to distinguish all patterns. On the other hand, bees trained on very large targets, or by landing on the pattern, learned cues in several eye regions, and were able to recognize the coarse configural layout.

A prototype feature system for feature retrieval using relationships

USGS Publications Warehouse

Choi, J.; Usery, E.L.

2009-01-01

Using a feature data model, geographic phenomena can be represented effectively by integrating space, theme, and time. This paper extends and implements a feature data model that supports query and visualization of geographic features using their non-spatial and temporal relationships. A prototype feature-oriented geographic information system (FOGIS) is then developed and storage of features named Feature Database is designed. Buildings from the U.S. Marine Corps Base, Camp Lejeune, North Carolina and subways in Chicago, Illinois are used to test the developed system. The results of the applications show the strength of the feature data model and the developed system 'FOGIS' when they utilize non-spatial and temporal relationships in order to retrieve and visualize individual features.

ViA: a perceptual visualization assistant

NASA Astrophysics Data System (ADS)

Healey, Chris G.; St. Amant, Robert; Elhaddad, Mahmoud S.

2000-05-01

This paper describes an automated visualized assistant called ViA. ViA is designed to help users construct perceptually optical visualizations to represent, explore, and analyze large, complex, multidimensional datasets. We have approached this problem by studying what is known about the control of human visual attention. By harnessing the low-level human visual system, we can support our dual goals of rapid and accurate visualization. Perceptual guidelines that we have built using psychophysical experiments form the basis for ViA. ViA uses modified mixed-initiative planning algorithms from artificial intelligence to search of perceptually optical data attribute to visual feature mappings. Our perceptual guidelines are integrated into evaluation engines that provide evaluation weights for a given data-feature mapping, and hints on how that mapping might be improved. ViA begins by asking users a set of simple questions about their dataset and the analysis tasks they want to perform. Answers to these questions are used in combination with the evaluation engines to identify and intelligently pursue promising data-feature mappings. The result is an automatically-generated set of mappings that are perceptually salient, but that also respect the context of the dataset and users' preferences about how they want to visualize their data.

Region of interest extraction based on multiscale visual saliency analysis for remote sensing images

NASA Astrophysics Data System (ADS)

Zhang, Yinggang; Zhang, Libao; Yu, Xianchuan

2015-01-01

Region of interest (ROI) extraction is an important component of remote sensing image processing. However, traditional ROI extraction methods are usually prior knowledge-based and depend on classification, segmentation, and a global searching solution, which are time-consuming and computationally complex. We propose a more efficient ROI extraction model for remote sensing images based on multiscale visual saliency analysis (MVS), implemented in the CIE L*a*b* color space, which is similar to visual perception of the human eye. We first extract the intensity, orientation, and color feature of the image using different methods: the visual attention mechanism is used to eliminate the intensity feature using a difference of Gaussian template; the integer wavelet transform is used to extract the orientation feature; and color information content analysis is used to obtain the color feature. Then, a new feature-competition method is proposed that addresses the different contributions of each feature map to calculate the weight of each feature image for combining them into the final saliency map. Qualitative and quantitative experimental results of the MVS model as compared with those of other models show that it is more effective and provides more accurate ROI extraction results with fewer holes inside the ROI.

The Benefit of Surface Uniformity for Encoding Boundary Features in Visual Working Memory

ERIC Educational Resources Information Center

Kim, Sung-Ho; Kim, Jung-Oh

2011-01-01

Using a change detection paradigm, the present study examined an object-based encoding benefit in visual working memory (VWM) for two boundary features (two orientations in Experiments 1-2 and two shapes in Experiments 3-4) assigned to a single object. Participants remembered more boundary features when they were conjoined into a single object of…

Visual search in Dementia with Lewy Bodies and Alzheimer's disease.

PubMed

Landy, Kelly M; Salmon, David P; Filoteo, J Vincent; Heindel, William C; Galasko, Douglas; Hamilton, Joanne M

2015-12-01

Visual search is an aspect of visual cognition that may be more impaired in Dementia with Lewy Bodies (DLB) than Alzheimer's disease (AD). To assess this possibility, the present study compared patients with DLB (n = 17), AD (n = 30), or Parkinson's disease with dementia (PDD; n = 10) to non-demented patients with PD (n = 18) and normal control (NC) participants (n = 13) on single-feature and feature-conjunction visual search tasks. In the single-feature task participants had to determine if a target stimulus (i.e., a black dot) was present among 3, 6, or 12 distractor stimuli (i.e., white dots) that differed in one salient feature. In the feature-conjunction task participants had to determine if a target stimulus (i.e., a black circle) was present among 3, 6, or 12 distractor stimuli (i.e., white dots and black squares) that shared either of the target's salient features. Results showed that target detection time in the single-feature task was not influenced by the number of distractors (i.e., "pop-out" effect) for any of the groups. In contrast, target detection time increased as the number of distractors increased in the feature-conjunction task for all groups, but more so for patients with AD or DLB than for any of the other groups. These results suggest that the single-feature search "pop-out" effect is preserved in DLB and AD patients, whereas ability to perform the feature-conjunction search is impaired. This pattern of preserved single-feature search with impaired feature-conjunction search is consistent with a deficit in feature binding that may be mediated by abnormalities in networks involving the dorsal occipito-parietal cortex. Copyright © 2015 Elsevier Ltd. All rights reserved.

Visual Search in Dementia with Lewy Bodies and Alzheimer’s Disease

PubMed Central

Landy, Kelly M.; Salmon, David P.; Filoteo, J. Vincent; Heindel, William C.; Galasko, Douglas; Hamilton, Joanne M.

2016-01-01

Visual search is an aspect of visual cognition that may be more impaired in Dementia with Lewy Bodies (DLB) than Alzheimer’s disease (AD). To assess this possibility, the present study compared patients with DLB (n=17), AD (n=30), or Parkinson’s disease with dementia (PDD; n=10) to non-demented patients with PD (n=18) and normal control (NC) participants (n=13) on single-feature and feature-conjunction visual search tasks. In the single-feature task participants had to determine if a target stimulus (i.e., a black dot) was present among 3, 6, or 12 distractor stimuli (i.e., white dots) that differed in one salient feature. In the feature-conjunction task participants had to determine if a target stimulus (i.e., a black circle) was present among 3, 6, or 12 distractor stimuli (i.e., white dots and black squares) that shared either of the target’s salient features. Results showed that target detection time in the single-feature task was not influenced by the number of distractors (i.e., “pop-out” effect) for any of the groups. In contrast, target detection time increased as the number of distractors increased in the feature-conjunction task for all groups, but more so for patients with AD or DLB than for any of the other groups. These results suggest that the single-feature search “pop-out” effect is preserved in DLB and AD patients, whereas ability to perform the feature-conjunction search is impaired. This pattern of preserved single-feature search with impaired feature-conjunction search is consistent with a deficit in feature binding that may be mediated by abnormalities in networks involving the dorsal occipito-parietal cortex. PMID:26476402

Perceptual learning of basic visual features remains task specific with Training-Plus-Exposure (TPE) training

PubMed Central

Cong, Lin-Juan; Wang, Ru-Jie; Yu, Cong; Zhang, Jun-Yun

2016-01-01

Visual perceptual learning is known to be specific to the trained retinal location, feature, and task. However, location and feature specificity can be eliminated by double-training or TPE training protocols, in which observers receive additional exposure to the transfer location or feature dimension via an irrelevant task besides the primary learning task Here we tested whether these new training protocols could even make learning transfer across different tasks involving discrimination of basic visual features (e.g., orientation and contrast). Observers practiced a near-threshold orientation (or contrast) discrimination task. Following a TPE training protocol, they also received exposure to the transfer task via performing suprathreshold contrast (or orientation) discrimination in alternating blocks of trials in the same sessions. The results showed no evidence for significant learning transfer to the untrained near-threshold contrast (or orientation) discrimination task after discounting the pretest effects and the suprathreshold practice effects. These results thus do not support a hypothetical task-independent component in perceptual learning of basic visual features. They also set the boundary of the new training protocols in their capability to enable learning transfer. PMID:26873777

Feature-selective attention enhances color signals in early visual areas of the human brain.

PubMed

Müller, M M; Andersen, S; Trujillo, N J; Valdés-Sosa, P; Malinowski, P; Hillyard, S A

2006-09-19

We used an electrophysiological measure of selective stimulus processing (the steady-state visual evoked potential, SSVEP) to investigate feature-specific attention to color cues. Subjects viewed a display consisting of spatially intermingled red and blue dots that continually shifted their positions at random. The red and blue dots flickered at different frequencies and thereby elicited distinguishable SSVEP signals in the visual cortex. Paying attention selectively to either the red or blue dot population produced an enhanced amplitude of its frequency-tagged SSVEP, which was localized by source modeling to early levels of the visual cortex. A control experiment showed that this selection was based on color rather than flicker frequency cues. This signal amplification of attended color items provides an empirical basis for the rapid identification of feature conjunctions during visual search, as proposed by "guided search" models.

Eyes Matched to the Prize: The State of Matched Filters in Insect Visual Circuits.

PubMed

Kohn, Jessica R; Heath, Sarah L; Behnia, Rudy

2018-01-01

Confronted with an ever-changing visual landscape, animals must be able to detect relevant stimuli and translate this information into behavioral output. A visual scene contains an abundance of information: to interpret the entirety of it would be uneconomical. To optimally perform this task, neural mechanisms exist to enhance the detection of important features of the sensory environment while simultaneously filtering out irrelevant information. This can be accomplished by using a circuit design that implements specific "matched filters" that are tuned to relevant stimuli. Following this rule, the well-characterized visual systems of insects have evolved to streamline feature extraction on both a structural and functional level. Here, we review examples of specialized visual microcircuits for vital behaviors across insect species, including feature detection, escape, and estimation of self-motion. Additionally, we discuss how these microcircuits are modulated to weigh relevant input with respect to different internal and behavioral states.

Progress on uncooled PbSe detectors for low-cost applications

NASA Astrophysics Data System (ADS)

Vergara, German; Gomez, Luis J.; Villamayor, Victor; Alvarez, M.; Rodrigo, Maria T.; del Carmen Torquemada, Maria; Sanchez, Fernando J.; Verdu, Marina; Diezhandino, Jorge; Rodriguez, Purificacion; Catalan, Irene; Almazan, Rosa; Plaza, Julio; Montojo, Maria T.

2004-08-01

This work reports on progress on development of polycrystalline PbSe infrared detectors at the Centro de Investigacion y Desarrollo de la Armada (CIDA). Since mid nineties, the CIDA owns an innovative technology for processing uncooled MWIR detectors of polycrystalline PbSe. Based on this technology, some applications have been developed. However, future applications demand smarter, more complex, faster yet cheaper detectors. Aiming to open new perspectives to polycrystalline PbSe detectors, we are currently working on different directions: 1) Processing of 2D arrays: a) Designing and processing low density x-y addressed arrays with 16x16 and 32x32 elements, as an extension of our standard technology. b) Trying to make compatible standard CMOS and polycrystalline PbSe technologies in order to process monolithic large format arrays. 2) Adding new features to the detector such as monolithically integrated spectral discrimination.

Waveguide integrated low noise NbTiN nanowire single-photon detectors with milli-Hz dark count rate

PubMed Central

Schuck, Carsten; Pernice, Wolfram H. P.; Tang, Hong X.

2013-01-01

Superconducting nanowire single-photon detectors are an ideal match for integrated quantum photonic circuits due to their high detection efficiency for telecom wavelength photons. Quantum optical technology also requires single-photon detection with low dark count rate and high timing accuracy. Here we present very low noise superconducting nanowire single-photon detectors based on NbTiN thin films patterned directly on top of Si3N4 waveguides. We systematically investigate a large variety of detector designs and characterize their detection noise performance. Milli-Hz dark count rates are demonstrated over the entire operating range of the nanowire detectors which also feature low timing jitter. The ultra-low dark count rate, in combination with the high detection efficiency inherent to our travelling wave detector geometry, gives rise to a measured noise equivalent power at the 10−20 W/Hz1/2 level. PMID:23714696

Centroid measurement error of CMOS detector in the presence of detector noise for inter-satellite optical communications

NASA Astrophysics Data System (ADS)

Li, Xin; Zhou, Shihong; Ma, Jing; Tan, Liying; Shen, Tao

2013-08-01

CMOS is a good candidate tracking detector for satellite optical communications systems with outstanding feature of sub-window for the development of APS (Active Pixel Sensor) technology. For inter-satellite optical communications it is critical to estimate the direction of incident laser beam precisely by measuring the centroid position of incident beam spot. The presence of detector noise results in measurement error, which degrades the tracking performance of systems. In this research, the measurement error of CMOS is derived taking consideration of detector noise. It is shown that the measurement error depends on pixel noise, size of the tracking sub-window (pixels number), intensity of incident laser beam, relative size of beam spot. The influences of these factors are analyzed by numerical simulation. We hope the results obtained in this research will be helpful in the design of CMOS detector satellite optical communications systems.

Assembly and Commissioning of a Liquid Argon Detector and Development of a Slow Control System for the COHERENT Experiment

NASA Astrophysics Data System (ADS)

Kaemingk, Michael; Cooper, Robert; Coherent Collaboration

2016-09-01

COHERENT is a collaboration whose goal is to measure coherent elastic neutrino-nucleus scattering (CEvNS). COHERENT plans to deploy a suite of detectors to measure the expected number-of-neutrons squared dependence of CEvNS at the Spallation Neutron Source at Oak Ridge National Laboratory. One of these detectors is a liquid argon detector which can measure these low energy nuclear recoil interactions. Ensuring optimal functionality requires the development of a slow control system to monitor and control various aspects, such as the temperature and pressure, of these detectors. Electronics manufactured by Beckhoff, Digilent, and Arduino among others are being used to create these slow control systems. This poster will generally discuss the assembly and commissioning of this CENNS-10 liquid argon detector at Indiana University and will feature work on the slow control systems.

Anticipatory Attentional Suppression of Visual Features Indexed by Oscillatory Alpha-Band Power Increases: A High-Density Electrical Mapping Study

PubMed Central

Snyder, Adam C.; Foxe, John J.

2010-01-01

Retinotopically specific increases in alpha-band (~10 Hz) oscillatory power have been strongly implicated in the suppression of processing for irrelevant parts of the visual field during the deployment of visuospatial attention. Here, we asked whether this alpha suppression mechanism also plays a role in the nonspatial anticipatory biasing of feature-based attention. Visual word cues informed subjects what the task-relevant feature of an upcoming visual stimulus (S2) was, while high-density electroencephalographic recordings were acquired. We examined anticipatory oscillatory activity in the Cue-to-S2 interval (~2 s). Subjects were cued on a trial-by-trial basis to attend to either the color or direction of motion of an upcoming dot field array, and to respond when they detected that a subset of the dots differed from the majority along the target feature dimension. We used the features of color and motion, expressly because they have well known, spatially separated cortical processing areas, to distinguish shifts in alpha power over areas processing each feature. Alpha power from dorsal regions increased when motion was the irrelevant feature (i.e., color was cued), and alpha power from ventral regions increased when color was irrelevant. Thus, alpha-suppression mechanisms appear to operate during feature-based selection in much the same manner as has been shown for space-based attention. PMID:20237273

Label-free visualization of ultrastructural features of artificial synapses via cryo-EM.

PubMed

Gopalakrishnan, Gopakumar; Yam, Patricia T; Madwar, Carolin; Bostina, Mihnea; Rouiller, Isabelle; Colman, David R; Lennox, R Bruce

2011-12-21

The ultrastructural details of presynapses formed between artificial substrates of submicrometer silica beads and hippocampal neurons are visualized via cryo-electron microscopy (cryo-EM). The silica beads are derivatized by poly-d-lysine or lipid bilayers. Molecular features known to exist at presynapses are clearly present at these artificial synapses, as visualized by cryo-EM. Key synaptic features such as the membrane contact area at synaptic junctions, the presynaptic bouton containing presynaptic vesicles, as well as microtubular structures can be identified. This is the first report of the direct, label-free observation of ultrastructural details of artificial synapses.

An integrative view of storage of low- and high-level visual dimensions in visual short-term memory.

PubMed

Magen, Hagit

2017-03-01

Efficient performance in an environment filled with complex objects is often achieved through the temporal maintenance of conjunctions of features from multiple dimensions. The most striking finding in the study of binding in visual short-term memory (VSTM) is equal memory performance for single features and for integrated multi-feature objects, a finding that has been central to several theories of VSTM. Nevertheless, research on binding in VSTM focused almost exclusively on low-level features, and little is known about how items from low- and high-level visual dimensions (e.g., colored manmade objects) are maintained simultaneously in VSTM. The present study tested memory for combinations of low-level features and high-level representations. In agreement with previous findings, Experiments 1 and 2 showed decrements in memory performance when non-integrated low- and high-level stimuli were maintained simultaneously compared to maintaining each dimension in isolation. However, contrary to previous findings the results of Experiments 3 and 4 showed decrements in memory performance even when integrated objects of low- and high-level stimuli were maintained in memory, compared to maintaining single-dimension objects. Overall, the results demonstrate that low- and high-level visual dimensions compete for the same limited memory capacity, and offer a more comprehensive view of VSTM.

Comparative study of palm print authentication system using geometric features

NASA Astrophysics Data System (ADS)

Shreyas, Kamath K. M.; Rajeev, Srijith; Panetta, Karen; Agaian, Sos S.

2017-05-01

Biometrics, particularly palm print authentication has been a stimulating research area due to its abundance of features. Stable features and effective matching are the most crucial steps for an authentication system. In conventional palm print authentication systems, matching is based on flexion creases, friction ridges, and minutiae points. Currently, contactless palm print imaging is an emerging technology. However, they tend to involve fluctuations in the image quality and texture loss due to factors such as varying illumination conditions, occlusions, noise, pose, and ghosting. These variations decrease the performance of the authentication systems. Furthermore, real-time palm print authentication in large databases continue to be a challenging task. In order to effectively solve these problems, features which are invariant to these anomalies are required. This paper proposes a robust palm print matching framework by making a comparative study of different local geometric features such as Difference-of-Gaussian, Hessian, Hessian-Laplace, Harris-Laplace, and Multiscale Harris for feature detection. These detectors are coupled with Scale Invariant Feature Transformation (SIFT) descriptor to describe the identified features. Additionally, a two-stage refinement process is carried out to obtain the best stable matches. Computer simulations demonstrate that the accuracy of the system has increased effectively with an EER of 0.86% when Harris-Laplace detector is used on IITD database.

Manifold structure preservative for hyperspectral target detection

NASA Astrophysics Data System (ADS)

Imani, Maryam

2018-05-01

A nonparametric method termed as manifold structure preservative (MSP) is proposed in this paper for hyperspectral target detection. MSP transforms the feature space of data to maximize the separation between target and background signals. Moreover, it minimizes the reconstruction error of targets and preserves the topological structure of data in the projected feature space. MSP does not need to consider any distribution for target and background data. So, it can achieve accurate results in real scenarios due to avoiding unreliable assumptions. The proposed MSP detector is compared to several popular detectors and the experiments on a synthetic data and two real hyperspectral images indicate the superior ability of it in target detection.

Combination of image descriptors for the exploration of cultural photographic collections

NASA Astrophysics Data System (ADS)

Bhowmik, Neelanjan; Gouet-Brunet, Valérie; Bloch, Gabriel; Besson, Sylvain

2017-01-01

The rapid growth of image digitization and collections in recent years makes it challenging and burdensome to organize, categorize, and retrieve similar images from voluminous collections. Content-based image retrieval (CBIR) is immensely convenient in this context. A considerable number of local feature detectors and descriptors are present in the literature of CBIR. We propose a model to anticipate the best feature combinations for image retrieval-related applications. Several spatial complementarity criteria of local feature detectors are analyzed and then engaged in a regression framework to find the optimal combination of detectors for a given dataset and are better adapted for each given image; the proposed model is also useful to optimally fix some other parameters, such as the k in k-nearest neighbor retrieval. Three public datasets of various contents and sizes are employed to evaluate the proposal, which is legitimized by improving the quality of retrieval notably facing classical approaches. Finally, the proposed image search engine is applied to the cultural photographic collections of a French museum, where it demonstrates its added value for the exploration and promotion of these contents at different levels from their archiving up to their exhibition in or ex situ.

Multi-class geospatial object detection and geographic image classification based on collection of part detectors

NASA Astrophysics Data System (ADS)

Cheng, Gong; Han, Junwei; Zhou, Peicheng; Guo, Lei

2014-12-01

The rapid development of remote sensing technology has facilitated us the acquisition of remote sensing images with higher and higher spatial resolution, but how to automatically understand the image contents is still a big challenge. In this paper, we develop a practical and rotation-invariant framework for multi-class geospatial object detection and geographic image classification based on collection of part detectors (COPD). The COPD is composed of a set of representative and discriminative part detectors, where each part detector is a linear support vector machine (SVM) classifier used for the detection of objects or recurring spatial patterns within a certain range of orientation. Specifically, when performing multi-class geospatial object detection, we learn a set of seed-based part detectors where each part detector corresponds to a particular viewpoint of an object class, so the collection of them provides a solution for rotation-invariant detection of multi-class objects. When performing geographic image classification, we utilize a large number of pre-trained part detectors to discovery distinctive visual parts from images and use them as attributes to represent the images. Comprehensive evaluations on two remote sensing image databases and comparisons with some state-of-the-art approaches demonstrate the effectiveness and superiority of the developed framework.

Energy resolution and efficiency of phonon-mediated kinetic inductance detectors for light detection

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

Cardani, L., E-mail: laura.cardani@roma1.infn.it; Physics Department, Princeton University, Washington Road, 08544, Princeton, New Jersey; Colantoni, I.

The development of sensitive cryogenic light detectors is of primary interest for bolometric experiments searching for rare events like dark matter interactions or neutrino-less double beta decay. Thanks to their good energy resolution and the natural multiplexed read-out, Kinetic Inductance Detectors (KIDs) are particularly suitable for this purpose. To efficiently couple KIDs-based light detectors to the large crystals used by the most advanced bolometric detectors, active surfaces of several cm{sup 2} are needed. For this reason, we are developing phonon-mediated detectors. In this paper, we present the results obtained with a prototype consisting of four 40 nm thick aluminum resonators patternedmore » on a 2 × 2 cm{sup 2} silicon chip, and calibrated with optical pulses and X-rays. The detector features a noise resolution σ{sub E} = 154 ± 7 eV and an (18 ± 2)% efficiency.« less

Detectors Requirements for the ODIN Beamline at ESS

NASA Astrophysics Data System (ADS)

Morgano, Manuel; Lehmann, Eberhard; Strobl, Markus

The upcoming high intensity pulsed spallationneutron source ESS, now in construction in Sweden, will provide unprecedented opportunities for neutron science worldwide. In particular, neutron imaging will benefit from the time structure of the source and its high brilliance. These features will unlock new opportunities at the imaging beamline ODIN, but only if suitable detectors are employed and, in some cases, upgraded. In this paper, we highlight the current state-of-the-art for neutron imaging detectors, pointing out that, while no single presently existing detector can fulfill all the requirements currently needed to exploit the source to its limits, the wide range of applications of ODIN can be successfully covered by a suite of current state-of-the-art detectors. Furthermore we speculate on improvements to the current detector technologies that would expand the range of the existing detectors and application range and we outline a strategy to have the best possible combined system for the foreseen day 1 operations of ODIN in 2019.

New installation for inclined EAS investigations

NASA Astrophysics Data System (ADS)

Zadeba, E. A.; Ampilogov, N. V.; Barbashina, N. S.; Bogdanov, A. G.; Borisov, A. A.; Chernov, D. V.; Dushkin, L. I.; Fakhrutdinov, R. M.; Kokoulin, R. P.; Kompaniets, K. G.; Kozhin, A. S.; Ovchinnikov, V. V.; Ovechkin, A. S.; Petrukhin, A. A.; Shutenko, V. V.; Volkov, N. S.; Vorobjev, V. S.; Yashin, I. I.

2017-06-01

The large-scale coordinate-tracking detector TREK for registration of inclined EAS is being developed in MEPhI. The detector is based on multiwire drift chambers from the neutrino experiment at the IHEP U-70 accelerator. Their key advantages are a large effective area (1.85 m2), a good coordinate and angular resolution with a small number of measuring channels. The detector will be operated as part of the experimental complex NEVOD, in particular, jointly with a Cherenkov water detector (CWD) with a volume of 2000 cubic meters and the coordinate detector DECOR. The first part of the detector named Coordinate-Tracking Unit based on the Drift Chambers (CTUDC), representing two coordinate planes of 8 drift chambers in each, has been developed and mounted on opposite sides of the CWD. It has the same principle of joint operation with the NEVOD-DECOR triggering system and the same drift chambers alignment, so the main features of the TREK detector will be examined. Results of the CTUDC development and a joint operation with NEVOD-DECOR complex are presented.

Feature-based attention: it is all bottom-up priming.

PubMed

Theeuwes, Jan

2013-10-19

Feature-based attention (FBA) enhances the representation of image characteristics throughout the visual field, a mechanism that is particularly useful when searching for a specific stimulus feature. Even though most theories of visual search implicitly or explicitly assume that FBA is under top-down control, we argue that the role of top-down processing in FBA may be limited. Our review of the literature indicates that all behavioural and neuro-imaging studies investigating FBA suffer from the shortcoming that they cannot rule out an effect of priming. The mere attending to a feature enhances the mandatory processing of that feature across the visual field, an effect that is likely to occur in an automatic, bottom-up way. Studies that have investigated the feasibility of FBA by means of cueing paradigms suggest that the role of top-down processing in FBA is limited (e.g. prepare for red). Instead, the actual processing of the stimulus is needed to cause the mandatory tuning of responses throughout the visual field. We conclude that it is likely that all FBA effects reported previously are the result of bottom-up priming.

Feature-based interference from unattended visual field during attentional tracking in younger and older adults.

PubMed

Störmer, Viola S; Li, Shu-Chen; Heekeren, Hauke R; Lindenberger, Ulman

2011-02-01

The ability to attend to multiple objects that move in the visual field is important for many aspects of daily functioning. The attentional capacity for such dynamic tracking, however, is highly limited and undergoes age-related decline. Several aspects of the tracking process can influence performance. Here, we investigated effects of feature-based interference from distractor objects that appear in unattended regions of the visual field with a hemifield-tracking task. Younger and older participants performed an attentional tracking task in one hemifield while distractor objects were concurrently presented in the unattended hemifield. Feature similarity between objects in the attended and unattended hemifields as well as motion speed and the number of to-be-tracked objects were parametrically manipulated. The results show that increasing feature overlap leads to greater interference from the unattended visual field. This effect of feature-based interference was only present in the slow speed condition, indicating that the interference is mainly modulated by perceptual demands. High-performing older adults showed a similar interference effect as younger adults, whereas low-performing adults showed poor tracking performance overall.

Inter-area correlations in the ventral visual pathway reflect feature integration

PubMed Central

Freeman, Jeremy; Donner, Tobias H.; Heeger, David J.

2011-01-01

During object perception, the brain integrates simple features into representations of complex objects. A perceptual phenomenon known as visual crowding selectively interferes with this process. Here, we use crowding to characterize a neural correlate of feature integration. Cortical activity was measured with functional magnetic resonance imaging, simultaneously in multiple areas of the ventral visual pathway (V1–V4 and the visual word form area, VWFA, which responds preferentially to familiar letters), while human subjects viewed crowded and uncrowded letters. Temporal correlations between cortical areas were lower for crowded letters than for uncrowded letters, especially between V1 and VWFA. These differences in correlation were retinotopically specific, and persisted when attention was diverted from the letters. But correlation differences were not evident when we substituted the letters with grating patches that were not crowded under our stimulus conditions. We conclude that inter-area correlations reflect feature integration and are disrupted by crowding. We propose that crowding may perturb the transformations between neural representations along the ventral pathway that underlie the integration of features into objects. PMID:21521832

Feature-based attention: it is all bottom-up priming

PubMed Central

Theeuwes, Jan

2013-01-01

Feature-based attention (FBA) enhances the representation of image characteristics throughout the visual field, a mechanism that is particularly useful when searching for a specific stimulus feature. Even though most theories of visual search implicitly or explicitly assume that FBA is under top-down control, we argue that the role of top-down processing in FBA may be limited. Our review of the literature indicates that all behavioural and neuro-imaging studies investigating FBA suffer from the shortcoming that they cannot rule out an effect of priming. The mere attending to a feature enhances the mandatory processing of that feature across the visual field, an effect that is likely to occur in an automatic, bottom-up way. Studies that have investigated the feasibility of FBA by means of cueing paradigms suggest that the role of top-down processing in FBA is limited (e.g. prepare for red). Instead, the actual processing of the stimulus is needed to cause the mandatory tuning of responses throughout the visual field. We conclude that it is likely that all FBA effects reported previously are the result of bottom-up priming. PMID:24018717

An "artificial retina" processor for track reconstruction at the full LHC crossing rate

NASA Astrophysics Data System (ADS)

Abba, A.; Bedeschi, F.; Caponio, F.; Cenci, R.; Citterio, M.; Cusimano, A.; Fu, J.; Geraci, A.; Grizzuti, M.; Lusardi, N.; Marino, P.; Morello, M. J.; Neri, N.; Ninci, D.; Petruzzo, M.; Piucci, A.; Punzi, G.; Ristori, L.; Spinella, F.; Stracka, S.; Tonelli, D.; Walsh, J.

2016-07-01

We present the latest results of an R&D study for a specialized processor capable of reconstructing, in a silicon pixel detector, high-quality tracks from high-energy collision events at 40 MHz. The processor applies a highly parallel pattern-recognition algorithm inspired to quick detection of edges in mammals visual cortex. After a detailed study of a real-detector application, demonstrating that online reconstruction of offline-quality tracks is feasible at 40 MHz with sub-microsecond latency, we are implementing a prototype using common high-bandwidth FPGA devices.

Arachne—A web-based event viewer for MINERνA

NASA Astrophysics Data System (ADS)

Tagg, N.; Brangham, J.; Chvojka, J.; Clairemont, M.; Day, M.; Eberly, B.; Felix, J.; Fields, L.; Gago, A. M.; Gran, R.; Harris, D. A.; Kordosky, M.; Lee, H.; Maggi, G.; Maher, E.; Mann, W. A.; Marshall, C. M.; McFarland, K. S.; McGowan, A. M.; Mislivec, A.; Mousseau, J.; Osmanov, B.; Osta, J.; Paolone, V.; Perdue, G.; Ransome, R. D.; Ray, H.; Schellman, H.; Schmitz, D. W.; Simon, C.; Solano Salinas, C. J.; Tice, B. G.; Walding, J.; Walton, T.; Wolcott, J.; Zhang, D.; Ziemer, B. P.; MinerνA Collaboration

2012-06-01

Neutrino interaction events in the MINERνA detector are visually represented with a web-based tool called Arachne. Data are retrieved from a central server via AJAX, and client-side JavaScript draws images into the user's browser window using the draft HTML 5 standard. These technologies allow neutrino interactions to be viewed by anyone with a web browser, allowing for easy hand-scanning of particle interactions. Arachne has been used in MINERνA to evaluate neutrino data in a prototype detector, to tune reconstruction algorithms, and for public outreach and education.

Arachne - A web-based event viewer for MINERvA

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

Tagg, N.; /Otterbein Coll.; Brangham, J.

2011-11-01

Neutrino interaction events in the MINERvA detector are visually represented with a web-based tool called Arachne. Data are retrieved from a central server via AJAX, and client-side JavaScript draws images into the user's browser window using the draft HTML 5 standard. These technologies allow neutrino interactions to be viewed by anyone with a web browser, allowing for easy hand-scanning of particle interactions. Arachne has been used in MINERvA to evaluate neutrino data in a prototype detector, to tune reconstruction algorithms, and for public outreach and education.

An "artificial retina" processor for track reconstruction at the full LHC crossing rate

DOE PAGES

Abba, A.; F. Bedeschi; Caponio, F.; ...

2015-10-23

Here, we present the latest results of an R&D; study for a specialized processor capable of reconstructing, in a silicon pixel detector, high-quality tracks from high-energy collision events at 40 MHz. The processor applies a highly parallel pattern-recognition algorithm inspired to quick detection of edges in mammals visual cortex. After a detailed study of a real-detector application, demonstrating that online reconstruction of offline-quality tracks is feasible at 40 MHz with sub-microsecond latency, we are implementing a prototype using common high-bandwidth FPGA devices.

Decomposition and extraction: a new framework for visual classification.

PubMed

Fang, Yuqiang; Chen, Qiang; Sun, Lin; Dai, Bin; Yan, Shuicheng

2014-08-01

In this paper, we present a novel framework for visual classification based on hierarchical image decomposition and hybrid midlevel feature extraction. Unlike most midlevel feature learning methods, which focus on the process of coding or pooling, we emphasize that the mechanism of image composition also strongly influences the feature extraction. To effectively explore the image content for the feature extraction, we model a multiplicity feature representation mechanism through meaningful hierarchical image decomposition followed by a fusion step. In particularly, we first propose a new hierarchical image decomposition approach in which each image is decomposed into a series of hierarchical semantical components, i.e, the structure and texture images. Then, different feature extraction schemes can be adopted to match the decomposed structure and texture processes in a dissociative manner. Here, two schemes are explored to produce property related feature representations. One is based on a single-stage network over hand-crafted features and the other is based on a multistage network, which can learn features from raw pixels automatically. Finally, those multiple midlevel features are incorporated by solving a multiple kernel learning task. Extensive experiments are conducted on several challenging data sets for visual classification, and experimental results demonstrate the effectiveness of the proposed method.

Pornography classification: The hidden clues in video space-time.

PubMed

Moreira, Daniel; Avila, Sandra; Perez, Mauricio; Moraes, Daniel; Testoni, Vanessa; Valle, Eduardo; Goldenstein, Siome; Rocha, Anderson

2016-11-01

As web technologies and social networks become part of the general public's life, the problem of automatically detecting pornography is into every parent's mind - nobody feels completely safe when their children go online. In this paper, we focus on video-pornography classification, a hard problem in which traditional methods often employ still-image techniques - labeling frames individually prior to a global decision. Frame-based approaches, however, ignore significant cogent information brought by motion. Here, we introduce a space-temporal interest point detector and descriptor called Temporal Robust Features (TRoF). TRoF was custom-tailored for efficient (low processing time and memory footprint) and effective (high classification accuracy and low false negative rate) motion description, particularly suited to the task at hand. We aggregate local information extracted by TRoF into a mid-level representation using Fisher Vectors, the state-of-the-art model of Bags of Visual Words (BoVW). We evaluate our original strategy, contrasting it both to commercial pornography detection solutions, and to BoVW solutions based upon other space-temporal features from the scientific literature. The performance is assessed using the Pornography-2k dataset, a new challenging pornographic benchmark, comprising 2000 web videos and 140h of video footage. The dataset is also a contribution of this work and is very assorted, including both professional and amateur content, and it depicts several genres of pornography, from cartoon to live action, with diverse behavior and ethnicity. The best approach, based on a dense application of TRoF, yields a classification error reduction of almost 79% when compared to the best commercial classifier. A sparse description relying on TRoF detector is also noteworthy, for yielding a classification error reduction of over 69%, with 19× less memory footprint than the dense solution, and yet can also be implemented to meet real-time requirements. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Development and Design of a User Interface for a Computer Automated Heating, Ventilation, and Air Conditioning System

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

Anderson, B.; /Fermilab

1999-10-08

A user interface is created to monitor and operate the heating, ventilation, and air conditioning system. The interface is networked to the system's programmable logic controller. The controller maintains automated control of the system. The user through the interface is able to see the status of the system and override or adjust the automatic control features. The interface is programmed to show digital readouts of system equipment as well as visual queues of system operational statuses. It also provides information for system design and component interaction. The interface is made easier to read by simple designs, color coordination, and graphics.more » Fermi National Accelerator Laboratory (Fermi lab) conducts high energy particle physics research. Part of this research involves collision experiments with protons, and anti-protons. These interactions are contained within one of two massive detectors along Fermilab's largest particle accelerator the Tevatron. The D-Zero Assembly Building houses one of these detectors. At this time detector systems are being upgraded for a second experiment run, titled Run II. Unlike the previous run, systems at D-Zero must be computer automated so operators do not have to continually monitor and adjust these systems during the run. Human intervention should only be necessary for system start up and shut down, and equipment failure. Part of this upgrade includes the heating, ventilation, and air conditioning system (HVAC system). The HVAC system is responsible for controlling two subsystems, the air temperatures of the D-Zero Assembly Building and associated collision hall, as well as six separate water systems used in the heating and cooling of the air and detector components. The BYAC system is automated by a programmable logic controller. In order to provide system monitoring and operator control a user interface is required. This paper will address methods and strategies used to design and implement an effective user interface. Background material pertinent to the BYAC system will cover the separate water and air subsystems and their purposes. In addition programming and system automation will also be covered.« less

Xenon detector with high energy resolution for gamma-ray line emission registration

NASA Astrophysics Data System (ADS)

Novikov, Alexander S.; Ulin, Sergey E.; Chernysheva, Irina V.; Dmitrenko, Valery V.; Grachev, Victor M.; Petrenko, Denis V.; Shustov, Alexander E.; Uteshev, Ziyaetdin M.; Vlasik, Konstantin F.

2014-09-01

A description of the xenon detector (XD) for gamma-ray line emission registration is presented. The detector provides high energy resolution and is able to operate under extreme environmental conditions (wide temperature range and unfavorable acoustic action). Resistance to acoustic noise as well as improvement in energy resolution has been achieved by means of real-time digital pulse processing. Another important XD feature is the ionization chamber's thin wall with composite housing, which significantly decreases the mass of the device and expands its energy range, especially at low energies.

Simulation of the GEM detector for BM@N experiment

NASA Astrophysics Data System (ADS)

Baranov, Dmitriy; Rogachevsky, Oleg

2017-03-01

The Gas Electron Multiplier (GEM) detector is one of the basic parts of the BM@N experiment included in the NICA project. The simulation model that takes into account features of signal generation process in an ionization GEM chamber is presented in this article. Proper parameters for the simulation were extracted from data retrieved with the help of Garfield++ (a toolkit for the detailed simulation of particle detectors). Due to this, we are able to generate clusters in layers of the micro-strip readout that correspond to clusters retrieved from a real physics experiment.

The very low angle detector for high-energy inelastic neutron scattering on the VESUVIO spectrometer

NASA Astrophysics Data System (ADS)

Perelli Cippo, E.; Gorini, G.; Tardocchi, M.; Pietropaolo, A.; Andreani, C.; Senesi, R.; Rhodes, N. J.; Schooneveld, E. M.

2008-05-01

The Very Low Angle Detector (VLAD) bank has been installed on the VESUVIO spectrometer at the ISIS spallation neutron source. The new device allows for high-energy inelastic neutron scattering measurements, at energies above 1 eV, maintaining the wave vector transfer lower than 10Å-1. This opens a still unexplored region of the kinematical (q, ω) space, enabling new and challenging experimental investigations in condensed matter. This paper describes the main instrumental features of the VLAD device, including instrument design, detector response, and calibration procedure.

Technical instrumentation R&D for ILD SiW ECAL large scale device

NASA Astrophysics Data System (ADS)

Balagura, V.

2018-03-01

Calorimeters with silicon detectors have many unique features and are proposed for several world-leading experiments. We describe the R&D program of the large scale detector element with up to 12 000 readout channels for the International Large Detector (ILD) at the future e+e‑ ILC collider. The program is focused on the readout front-end electronics embedded inside the calorimeter. The first part with 2 000 channels and two small silicon sensors has already been constructed, the full prototype is planned for the beginning of 2018.

Feature-Based Memory-Driven Attentional Capture: Visual Working Memory Content Affects Visual Attention

ERIC Educational Resources Information Center

Olivers, Christian N. L.; Meijer, Frank; Theeuwes, Jan

2006-01-01

In 7 experiments, the authors explored whether visual attention (the ability to select relevant visual information) and visual working memory (the ability to retain relevant visual information) share the same content representations. The presence of singleton distractors interfered more strongly with a visual search task when it was accompanied by…

a Novel Ship Detection Method for Large-Scale Optical Satellite Images Based on Visual Lbp Feature and Visual Attention Model

NASA Astrophysics Data System (ADS)

Haigang, Sui; Zhina, Song

2016-06-01

Reliably ship detection in optical satellite images has a wide application in both military and civil fields. However, this problem is very difficult in complex backgrounds, such as waves, clouds, and small islands. Aiming at these issues, this paper explores an automatic and robust model for ship detection in large-scale optical satellite images, which relies on detecting statistical signatures of ship targets, in terms of biologically-inspired visual features. This model first selects salient candidate regions across large-scale images by using a mechanism based on biologically-inspired visual features, combined with visual attention model with local binary pattern (CVLBP). Different from traditional studies, the proposed algorithm is high-speed and helpful to focus on the suspected ship areas avoiding the separation step of land and sea. Largearea images are cut into small image chips and analyzed in two complementary ways: Sparse saliency using visual attention model and detail signatures using LBP features, thus accordant with sparseness of ship distribution on images. Then these features are employed to classify each chip as containing ship targets or not, using a support vector machine (SVM). After getting the suspicious areas, there are still some false alarms such as microwaves and small ribbon clouds, thus simple shape and texture analysis are adopted to distinguish between ships and nonships in suspicious areas. Experimental results show the proposed method is insensitive to waves, clouds, illumination and ship size.

Visual search in Alzheimer's disease: a deficiency in processing conjunctions of features.

PubMed

Tales, A; Butler, S R; Fossey, J; Gilchrist, I D; Jones, R W; Troscianko, T

2002-01-01

Human vision often needs to encode multiple characteristics of many elements of the visual field, for example their lightness and orientation. The paradigm of visual search allows a quantitative assessment of the function of the underlying mechanisms. It measures the ability to detect a target element among a set of distractor elements. We asked whether Alzheimer's disease (AD) patients are particularly affected in one type of search, where the target is defined by a conjunction of features (orientation and lightness) and where performance depends on some shifting of attention. Two non-conjunction control conditions were employed. The first was a pre-attentive, single-feature, "pop-out" task, detecting a vertical target among horizontal distractors. The second was a single-feature, partly attentive task in which the target element was slightly larger than the distractors-a "size" task. This was chosen to have a similar level of attentional load as the conjunction task (for the control group), but lacked the conjunction of two features. In an experiment, 15 AD patients were compared to age-matched controls. The results suggested that AD patients have a particular impairment in the conjunction task but not in the single-feature size or pre-attentive tasks. This may imply that AD particularly affects those mechanisms which compare across more than one feature type, and spares the other systems and is not therefore simply an 'attention-related' impairment. Additionally, these findings show a double dissociation with previous data on visual search in Parkinson's disease (PD), suggesting a different effect of these diseases on the visual pathway.

Attention improves encoding of task-relevant features in the human visual cortex.

PubMed

Jehee, Janneke F M; Brady, Devin K; Tong, Frank

2011-06-01

When spatial attention is directed toward a particular stimulus, increased activity is commonly observed in corresponding locations of the visual cortex. Does this attentional increase in activity indicate improved processing of all features contained within the attended stimulus, or might spatial attention selectively enhance the features relevant to the observer's task? We used fMRI decoding methods to measure the strength of orientation-selective activity patterns in the human visual cortex while subjects performed either an orientation or contrast discrimination task, involving one of two laterally presented gratings. Greater overall BOLD activation with spatial attention was observed in visual cortical areas V1-V4 for both tasks. However, multivariate pattern analysis revealed that orientation-selective responses were enhanced by attention only when orientation was the task-relevant feature and not when the contrast of the grating had to be attended. In a second experiment, observers discriminated the orientation or color of a specific lateral grating. Here, orientation-selective responses were enhanced in both tasks, but color-selective responses were enhanced only when color was task relevant. In both experiments, task-specific enhancement of feature-selective activity was not confined to the attended stimulus location but instead spread to other locations in the visual field, suggesting the concurrent involvement of a global feature-based attentional mechanism. These results suggest that attention can be remarkably selective in its ability to enhance particular task-relevant features and further reveal that increases in overall BOLD amplitude are not necessarily accompanied by improved processing of stimulus information.

Oblique reconstructions in tomosynthesis. II. Super-resolution

PubMed Central

Acciavatti, Raymond J.; Maidment, Andrew D. A.

2013-01-01

Purpose: In tomosynthesis, super-resolution has been demonstrated using reconstruction planes parallel to the detector. Super-resolution allows for subpixel resolution relative to the detector. The purpose of this work is to develop an analytical model that generalizes super-resolution to oblique reconstruction planes. Methods: In a digital tomosynthesis system, a sinusoidal test object is modeled along oblique angles (i.e., “pitches”) relative to the plane of the detector in a 3D divergent-beam acquisition geometry. To investigate the potential for super-resolution, the input frequency is specified to be greater than the alias frequency of the detector. Reconstructions are evaluated in an oblique plane along the extent of the object using simple backprojection (SBP) and filtered backprojection (FBP). By comparing the amplitude of the reconstruction against the attenuation coefficient of the object at various frequencies, the modulation transfer function (MTF) is calculated to determine whether modulation is within detectable limits for super-resolution. For experimental validation of super-resolution, a goniometry stand was used to orient a bar pattern phantom along various pitches relative to the breast support in a commercial digital breast tomosynthesis system. Results: Using theoretical modeling, it is shown that a single projection image cannot resolve a sine input whose frequency exceeds the detector alias frequency. The high frequency input is correctly visualized in SBP or FBP reconstruction using a slice along the pitch of the object. The Fourier transform of this reconstructed slice is maximized at the input frequency as proof that the object is resolved. Consistent with the theoretical results, experimental images of a bar pattern phantom showed super-resolution in oblique reconstructions. At various pitches, the highest frequency with detectable modulation was determined by visual inspection of the bar patterns. The dependency of the highest detectable frequency on pitch followed the same trend as the analytical model. It was demonstrated that super-resolution is not achievable if the pitch of the object approaches 90°, corresponding to the case in which the test frequency is perpendicular to the breast support. Only low frequency objects are detectable at pitches close to 90°. Conclusions: This work provides a platform for investigating super-resolution in oblique reconstructions for tomosynthesis. In breast imaging, this study should have applications in visualizing microcalcifications and other subtle signs of cancer. PMID:24320445

Preliminary design report, Large Space Telescope OTA/SI Phase B study: High speed area photometer. [systems analysis

NASA Technical Reports Server (NTRS)

1975-01-01

A photometer is examined which combines several features from separate instruments into a single package. The design presented has both point and area photometry capability with provision for inserting filters to provide spectral discrimination. The electronics provide for photon counting mode for the point detectors and both photon counting and analog modes for the area detector. The area detector also serves as a target locating device for the point detectors. Topics discussed include: (1) electronic equipment requirements, (2) optical properties, (3) structural housing for the instrument, (4) motors and other mechanical components, (5) ground support equipment, and (6) environment control for the instrument. Engineering drawings and block diagrams are shown.

Gaseous detectors for energy dispersive X-ray fluorescence analysis

NASA Astrophysics Data System (ADS)

Veloso, J. F. C. A.; Silva, A. L. M.

2018-01-01

The energy resolution capability of gaseous detectors is being used in the last years to perform studies on the detection of characteristic X-ray lines emitted by elements when excited by external radiation sources. One of the most successful techniques is the Energy Dispersive X-ray Fluorescence (EDXRF) analysis. Recent developments in the new generation of micropatterned gaseous detectors (MPGDs), triggered the possibility not only of recording the photon energy, but also of providing position information, extending their application to EDXRF imaging. The relevant features and strategies to be applied in gaseous detectors in order to better fit the requirements for EDXRF imaging will be reviewed and discussed, and some application examples will be presented.

Emotion recognition abilities across stimulus modalities in schizophrenia and the role of visual attention.

PubMed

Simpson, Claire; Pinkham, Amy E; Kelsven, Skylar; Sasson, Noah J

2013-12-01

Emotion can be expressed by both the voice and face, and previous work suggests that presentation modality may impact emotion recognition performance in individuals with schizophrenia. We investigated the effect of stimulus modality on emotion recognition accuracy and the potential role of visual attention to faces in emotion recognition abilities. Thirty-one patients who met DSM-IV criteria for schizophrenia (n=8) or schizoaffective disorder (n=23) and 30 non-clinical control individuals participated. Both groups identified emotional expressions in three different conditions: audio only, visual only, combined audiovisual. In the visual only and combined conditions, time spent visually fixating salient features of the face were recorded. Patients were significantly less accurate than controls in emotion recognition during both the audio and visual only conditions but did not differ from controls on the combined condition. Analysis of visual scanning behaviors demonstrated that patients attended less than healthy individuals to the mouth in the visual condition but did not differ in visual attention to salient facial features in the combined condition, which may in part explain the absence of a deficit for patients in this condition. Collectively, these findings demonstrate that patients benefit from multimodal stimulus presentations of emotion and support hypotheses that visual attention to salient facial features may serve as a mechanism for accurate emotion identification. © 2013.

SoLid Detector Technology

NASA Astrophysics Data System (ADS)

Labare, Mathieu

2017-09-01

SoLid is a reactor anti-neutrino experiment where a novel detector is deployed at a minimum distance of 5.5 m from a nuclear reactor core. The purpose of the experiment is three-fold: to search for neutrino oscillations at a very short baseline; to measure the pure 235U neutrino energy spectrum; and to demonstrate the feasibility of neutrino detectors for reactor monitoring. This report presents the unique features of the SoLid detector technology. The technology has been optimised for a high background environment resulting from low overburden and the vicinity of a nuclear reactor. The versatility of the detector technology is demonstrated with a 288 kg detector prototype which was deployed at the BR2 nuclear reactor in 2015. The data presented includes both reactor on, reactor off and calibration measurements. The measurement results are compared with Monte Carlo simulations. The 1.6t SoLid detector is currently under construction, with an optimised design and upgraded material technology to enhance the detector capabilities. Its deployement on site is planned for the begin of 2017 and offers the prospect to resolve the reactor anomaly within about two years.

Characterization of AlMn TES Impedance, Noise, and Optical Efficiency in the First 150 mm Multichroic Array for Advanced ACTPol

NASA Technical Reports Server (NTRS)

Crowley, Kevin T.; Choi, Steve K.; Kuan, Jeffrey; Austermann, Jason E.; Beall, James A.; Datta, Rahul; Duff, Shannon M.; Gallardo, Patricia A.; Hasselfield, Matthew; Henderson, Shawn W.;

Human Object-Similarity Judgments Reflect and Transcend the Primate-IT Object Representation

PubMed Central

Mur, Marieke; Meys, Mirjam; Bodurka, Jerzy; Goebel, Rainer; Bandettini, Peter A.; Kriegeskorte, Nikolaus

2013-01-01

Primate inferior temporal (IT) cortex is thought to contain a high-level representation of objects at the interface between vision and semantics. This suggests that the perceived similarity of real-world objects might be predicted from the IT representation. Here we show that objects that elicit similar activity patterns in human IT (hIT) tend to be judged as similar by humans. The IT representation explained the human judgments better than early visual cortex, other ventral-stream regions, and a range of computational models. Human similarity judgments exhibited category clusters that reflected several categorical divisions that are prevalent in the IT representation of both human and monkey, including the animate/inanimate and the face/body division. Human judgments also reflected the within-category representation of IT. However, the judgments transcended the IT representation in that they introduced additional categorical divisions. In particular, human judgments emphasized human-related additional divisions between human and non-human animals and between man-made and natural objects. hIT was more similar to monkey IT than to human judgments. One interpretation is that IT has evolved visual-feature detectors that distinguish between animates and inanimates and between faces and bodies because these divisions are fundamental to survival and reproduction for all primate species, and that other brain systems serve to more flexibly introduce species-dependent and evolutionarily more recent divisions. PMID:23525516

Weighted parallel contributions of binocular correlation and match signals to conscious perception of depth

PubMed Central

2016-01-01

Binocular disparity is detected in the primary visual cortex by a process similar to calculation of local cross-correlation between left and right retinal images. As a consequence, correlation-based neural signals convey information about false disparities as well as the true disparity. The false responses in the initial disparity detectors are eliminated at later stages in order to encode only disparities of the features correctly matched between the two eyes. For a simple stimulus configuration, a feed-forward nonlinear process can transform the correlation signal into the match signal. For human observers, depth judgement is determined by a weighted sum of the correlation and match signals rather than depending solely on the latter. The relative weight changes with spatial and temporal parameters of the stimuli, allowing adaptive recruitment of the two computations under different visual circumstances. A full transformation from correlation-based to match-based representation occurs at the neuronal population level in cortical area V4 and manifests in single-neuron responses of inferior temporal and posterior parietal cortices. Neurons in area V5/MT represent disparity in a manner intermediate between the correlation and match signals. We propose that the correlation and match signals in these areas contribute to depth perception in a weighted, parallel manner. This article is part of the themed issue ‘Vision in our three-dimensional world’. PMID:27269600