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https://www.readbyqxmd.com/read/28335510/gender-recognition-from-human-body-images-using-visible-light-and-thermal-camera-videos-based-on-a-convolutional-neural-network-for-image-feature-extraction
#1
Dat Tien Nguyen, Ki Wan Kim, Hyung Gil Hong, Ja Hyung Koo, Min Cheol Kim, Kang Ryoung Park
Extracting powerful image features plays an important role in computer vision systems. Many methods have previously been proposed to extract image features for various computer vision applications, such as the scale-invariant feature transform (SIFT), speed-up robust feature (SURF), local binary patterns (LBP), histogram of oriented gradients (HOG), and weighted HOG. Recently, the convolutional neural network (CNN) method for image feature extraction and classification in computer vision has been used in various applications...
March 20, 2017: Sensors
https://www.readbyqxmd.com/read/28333644/random-forest-classifier-for-zero-shot-learning-based-on-relative-attribute
#2
Yuhu Cheng, Xue Qiao, Xuesong Wang, Qiang Yu
For the zero-shot image classification with relative attributes (RAs), the traditional method requires that not only all seen and unseen images obey Gaussian distribution, but also the classifications on testing samples are made by maximum likelihood estimation. We therefore propose a novel zero-shot image classifier called random forest based on relative attribute. First, based on the ordered and unordered pairs of images from the seen classes, the idea of ranking support vector machine is used to learn ranking functions for attributes...
March 21, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28333637/multi-scale-multi-feature-context-modeling-for-scene-recognition-in-the-semantic-manifold
#3
Xinhang Song, Shuqiang Jiang, Luis Herranz
Before the big data era, scene recognition was often approached with two-step inference using localized intermediate representations (objects, topics, etc). One of such approaches is the semantic manifold (SM), in which patches and images are modeled as points in a semantic probability simplex. Patch models are learned resorting to weak supervision via image labels, which leads to the problem of scene categories co-occurring in this semantic space. Fortunately, each category has its own cooccurrence patterns that are consistent across the images in that category...
March 22, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28329909/testing-the-boundaries-of-boundary-extension-anticipatory-scene-representation-across-development-and-disorder
#4
G Spanò, H Intraub, J O Edgin
Recent studies have suggested that Boundary Extension (BE), a scene construction error, may be linked to the function of the hippocampus. In this study, we tested BE in two groups with variations in hippocampal development and disorder: a typically developing sample ranging from preschool to adolescence and individuals with Down syndrome. We assessed BE across three different test modalities: drawing, visual recognition, and a 3D scene boundary reconstruction task. Despite confirmed fluctuations in memory function measured through a neuropsychological assessment, the results showed consistent BE in all groups across test modalities, confirming the near universal nature of BE...
March 22, 2017: Hippocampus
https://www.readbyqxmd.com/read/28323824/local-structure-preserving-sparse-coding-for-infrared-target-recognition
#5
Jing Han, Jiang Yue, Yi Zhang, Lianfa Bai
Sparse coding performs well in image classification. However, robust target recognition requires a lot of comprehensive template images and the sparse learning process is complex. We incorporate sparsity into a template matching concept to construct a local sparse structure matching (LSSM) model for general infrared target recognition. A local structure preserving sparse coding (LSPSc) formulation is proposed to simultaneously preserve the local sparse and structural information of objects. By adding a spatial local structure constraint into the classical sparse coding algorithm, LSPSc can improve the stability of sparse representation for targets and inhibit background interference in infrared images...
2017: PloS One
https://www.readbyqxmd.com/read/28301185/embodied-memory-allows-accurate-and-stable-perception-of-hidden-objects-despite-orientation-change
#6
Jing Samantha Pan, Ned Bingham, Geoffrey P Bingham
Rotating a scene in a frontoparallel plane (rolling) yields a change in orientation of constituent images. When using only information provided by static images to perceive a scene after orientation change, identification performance typically decreases (Rock & Heimer, 1957). However, rolling generates optic flow information that relates the discrete, static images (before and after the change) and forms an embodied memory that aids recognition. The embodied memory hypothesis predicts that upon detecting a continuous spatial transformation of image structure, or in other words, seeing the continuous rolling process and objects undergoing rolling observers should accurately perceive objects during and after motion...
March 16, 2017: Journal of Experimental Psychology. Human Perception and Performance
https://www.readbyqxmd.com/read/28299412/tdcs-application-over-the-stg-improves-the-ability-to-recognize-and-appreciate-elements-involved-in-humor-processing
#7
Mirella Manfredi, Alice Mado Proverbio, Ana Paula Gonçalves Donate, Sofia Macarini Gonçalves Vieira, William Edgar Comfort, Mariana De Araújo Andreoli, Paulo Sérgio Boggio
The superior temporal gyrus (STG) has been found to play a crucial role in the recognition of actions and facial expressions and may, therefore, be critical for the processing of humorous information. Here we investigated whether tDCS application to the STG would modulate the ability to recognize and appreciate the comic element in serious and comedic situations of misfortune. To this aim, the effects of different types of tDCS stimulation on the STG were analyzed during a task in which the participants were instructed to categorize various misfortunate situations as "comic" or "not comic"...
March 15, 2017: Experimental Brain Research. Experimentelle Hirnforschung. Expérimentation Cérébrale
https://www.readbyqxmd.com/read/28275708/holistic-processing-of-fingerprints-by-expert-forensic-examiners
#8
Macgregor D Vogelsang, Thomas J Palmeri, Thomas A Busey
Holistic processing is often characterized as a process by which objects are perceived as a whole rather than a compilation of individual features. This mechanism may play an important role in the development of perceptual expertise because it allows for rapid integration across image regions. The present work explores whether holistic processing is present in latent fingerprint examiners, who compare fingerprints collected from crime scenes against a set of standards taken from a suspect. We adapted a composite task widely used in the face recognition and perceptual expertise literatures, in which participants were asked to match only a particular half of a fingerprint with a previous image while ignoring the other half...
2017: Cogn Res Princ Implic
https://www.readbyqxmd.com/read/28263635/global-ensemble-texture-representations-are-critical-to-rapid-scene-perception
#9
Timothy F Brady, Anna Shafer-Skelton, George A Alvarez
Traditionally, recognizing the objects within a scene has been treated as a prerequisite to recognizing the scene itself. However, research now suggests that the ability to rapidly recognize visual scenes could be supported by global properties of the scene itself rather than the objects within the scene. Here, we argue for a particular instantiation of this view: That scenes are recognized by treating them as a global texture and processing the pattern of orientations and spatial frequencies across different areas of the scene without recognizing any objects...
March 6, 2017: Journal of Experimental Psychology. Human Perception and Performance
https://www.readbyqxmd.com/read/28261791/drug-recognition-evaluation-and-chemical-confirmation-of-a-25c-nbome-impaired-driver
#10
James W Rajotte, Jean-Paul F P Palmentier, Helena Rachelle Wallage
This case report details an individual arrested for drug-impaired driving after leaving the scene of multiple motor vehicle collisions and evading police. The driver was examined by a drug recognition expert and failed the drug recognition evaluation. The driver admitted to using cocaine, marijuana, an antidepressant medication and "N-bomb," a novel psychoactive substance that possesses hallucinogenic properties. Toxicological analyses at the Centre of Forensic Sciences' Toronto laboratory revealed only the substance 2-[4-chloro-2,5-dimethoxyphenyl]-N-[(2-methoxyphenyl)methyl]ethanamine (25C-NBOMe) in the accused's urine...
March 6, 2017: Journal of Forensic Sciences
https://www.readbyqxmd.com/read/28252402/knowledge-guided-disambiguation-for-large-scale-scene-classification-with-multi-resolution-cnns
#11
Limin Wang, Sheng Guo, Weilin Huang, Yuanjun Xiong, Yu Qiao
Convolutional Neural Networks (CNNs) have made remarkable progress on scene recognition, partially due to these recent large-scale scene datasets, such as the Places and Places2. Scene categories are often defined by multi-level information, including local objects, global layout, and background environment, thus leading to large intra-class variations. In addition, with the increasing number of scene categories, label ambiguity has become another crucial issue in large-scale classification. This paper focuses on large-scale scene recognition and makes two major contributions to tackle these issues...
February 24, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28245502/temporal-and-peripheral-extraction-of-contextual-cues-from-scenes-during-visual-search
#12
Kathryn Koehler, Miguel P Eckstein
Scene context is known to facilitate object recognition and guide visual search, but little work has focused on isolating image-based cues and evaluating their contributions to eye movement guidance and search performance. Here, we explore three types of contextual cues (a co-occurring object, the configuration of other objects, and the superordinate category of background elements) and assess their joint contributions to search performance in the framework of cue-combination and the temporal unfolding of their extraction...
February 1, 2017: Journal of Vision
https://www.readbyqxmd.com/read/28245490/gaze-behavior-during-3-d-face-identification-is-depth-cue-invariant
#13
Hassan Akhavein, Reza Farivar
Gaze behavior during scene and object recognition can highlight the relevant information for a task. For example, salience maps-highlighting regions that have heightened luminance, contrast, color, etc. in a scene-can be used to predict gaze targets. Certain tasks, such as face recognition, result in a typical pattern of fixations on high salience features. While local salience of a 2-D feature may contribute to gaze behavior and object recognition, we are perfectly capable of recognizing objects from 3-D depth cues devoid of meaningful 2-D features...
February 1, 2017: Journal of Vision
https://www.readbyqxmd.com/read/28238657/frogs-exploit-statistical-regularities-in-noisy-acoustic-scenes-to-solve-cocktail-party-like-problems
#14
Norman Lee, Jessica L Ward, Alejandro Vélez, Christophe Micheyl, Mark A Bee
Noise is a ubiquitous source of errors in all forms of communication [1]. Noise-induced errors in speech communication, for example, make it difficult for humans to converse in noisy social settings, a challenge aptly named the "cocktail party problem" [2]. Many nonhuman animals also communicate acoustically in noisy social groups and thus face biologically analogous problems [3]. However, we know little about how the perceptual systems of receivers are evolutionarily adapted to avoid the costs of noise-induced errors in communication...
March 6, 2017: Current Biology: CB
https://www.readbyqxmd.com/read/28209734/neural-representations-of-observed-actions-generalize-across-static-and-dynamic-visual-input
#15
Alon Hafri, John C Trueswell, Russell A Epstein
People interact with other people and with objects in distinct and categorizable ways (e.g., kicking is making contact with foot). We can recognize these action categories across variations in actors, objects, and settings; moreover, we can recognize them from both dynamic and static visual input. However, the neural systems that support action recognition across these perceptual differences are unclear. Here we used multivoxel pattern analysis of fMRI data to identify brain regions that support visual action categorization in a format-independent way...
February 16, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28207394/weakly-supervised-patchnets-describing-and-aggregating-local-patches-for-scene-recognition
#16
Zhe Wang, Limin Wang, Yali Wang, Bowen Zhang, Yu Qiao
Traditional feature encoding scheme (e.g., Fisher vector) with local descriptors (e.g., SIFT) and recent convolutional neural networks (CNNs) are two classes of successful methods for image recognition. In this paper, we propose a hybrid representation, which leverages the discriminative capacity of CNNs and the simplicity of descriptor encoding schema for image recognition, with a focus on scene recognition. To this end, we make three main contributions from the following aspects. First, we propose a patch-level and end-to-end architecture to model the appearance of local patches, called PatchNet...
February 9, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28207385/24-7-place-recognition-by-view-synthesis
#17
Akihiko Torii, Relja Arandjelovic, Josef Sivic, Masatoshi Okutomi, Tomas Pajdla
We address the problem of large-scale visual place recognition for situations where the scene undergoes a major change in appearance, for example, due to illumination (day/night), change of seasons, aging, or structural modifications over time such as buildings being built or destroyed. Such situations represent a major challenge for current large-scale place recognition methods. This work has the following three principal contributions. First, we demonstrate that matching across large changes in the scene appearance becomes much easier when both the query image and the database image depict the scene from approximately the same viewpoint...
February 13, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28179554/are-there-multiple-kinds-of-episodic-memory-an-fmri-investigation-comparing-autobiographical-and-recognition-memory-tasks
#18
Hung-Yu Chen, Adrian W Gilmore, Steven M Nelson, Kathleen B McDermott
What brain regions underlie retrieval from episodic memory? The bulk of research addressing this question with fMRI has relied upon recognition memory for materials encoded within the laboratory. Another, less dominant tradition has employed autobiographical methods, whereby people recall events from their lifetime, often after being cued with words or pictures. The current study addressed how the neural substrates of successful memory retrieval differ as a function of the targeted memory when the experimental parameters were held constant in the two conditions (except for instructions)...
February 8, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28174533/reward-dependent-invigoration-relates-to-theta-oscillations-and-is-predicted-by-dopaminergic-midbrain-integrity-in-healthy-elderly
#19
Tineke K Steiger, Nico Bunzeck
Motivation can have invigorating effects on behavior via dopaminergic neuromodulation. While this relationship has mainly been established in theoretical models and studies in younger subjects, the impact of structural declines of the dopaminergic system during healthy aging remains unclear. To investigate this issue, we used electroencephalography (EEG) in healthy young and elderly humans in a reward-learning paradigm. Specifically, scene images were initially encoded by combining them with cues predicting monetary reward (high vs...
2017: Frontiers in Aging Neuroscience
https://www.readbyqxmd.com/read/28154991/a-computational-framework-for-attentional-object-discovery-in-rgb-d-videos
#20
Germán Martín García, Mircea Pavel, Simone Frintrop
We present a computational framework for attention-guided visual scene exploration in sequences of RGB-D data. For this, we propose a visual object candidate generation method to produce object hypotheses about the objects in the scene. An attention system is used to prioritise the processing of visual information by (1) localising candidate objects, and (2) integrating an inhibition of return (IOR) mechanism grounded in spatial coordinates. This spatial IOR mechanism naturally copes with camera motions and inhibits objects that have already been the target of attention...
February 2, 2017: Cognitive Processing
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