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https://www.readbyqxmd.com/read/28813564/multi-inducer-grouping-for-curve-completion-perceptual-and-computational-exploration
#1
Nir-Cohen Gal, Arad Boaz, Ben-Shahar Ohad
The human visual system excels in object recognition and scene interpretation even in scenes in which some (or even all) observed objects are partially occluded or fragmented. This highly efficient capacity is facilitated by constructive processes of contour completion between inducers to yield the perception of whole objects across gaps. A fundamental problem of the process is when and how the visual system groups different inducers in the visual scene between which completion occurs. Previous studies on this grouping problem, inspired mostly by relatability theory (Kellman & Shipley, 1991), focused on one good continuation condition that dictates whether a given pair of inducers would group together or not...
August 1, 2017: Journal of Vision
https://www.readbyqxmd.com/read/28808817/electrophysiological-modulation-in-an-effort-to-complete-illusory-figures-configuration-illusory-contour-and-closure-effects
#2
Tommaso Poscoliero, Massimo Girelli
Figure recognition process: From the coarse configuration standing from the background to the closure of a meaningful shape, was investigated by ERP technique. ERP components at different latencies from stimulus onset allowed to tap into the figure recognition process at discrete time-points when different cognitive operations take place. In this study, we present two experiments where the support-ratio (SR) of illusory figures was manipulated to vary continuously the recognition of geometrical figures. In the first experiment three shapes were used to vary the SR and the P1 component (80-130 ms) was modulated by the configuration-effect explained, in part for the first time, with the unbalanced physical stimulation between upper and lower visual field...
August 14, 2017: Brain Topography
https://www.readbyqxmd.com/read/28796618/learning-based-shadow-recognition-and-removal-from-monochromatic-natural-images
#3
Mingliang Xu, Jiejie Zhu, Pei Lv, Bing Zhou, Marshall F Tappen, Rongrong Ji
This paper addresses the problem of recognizing and removing shadows from monochromatic natural images from a learning based perspective. Without chromatic information, shadow recognition and removal are extremely challenging in the literature, mainly due to the missing of invariant color cues. Natural scenes make this problem even harder due to the complex illumination condition and ambiguity from many near-black objects. In this paper, a learning based shadow recognition and removal scheme is proposed to tackle the challenges above...
August 7, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28795834/contrasting-gist-based-and-template-based-guidance-during-real-world-visual-search
#4
Brett Bahle, Michi Matsukura, Andrew Hollingworth
Visual search through real-world scenes is guided both by a representation of target features and by knowledge of the sematic properties of the scene (derived from scene gist recognition). In 3 experiments, we compared the relative roles of these 2 sources of guidance. Participants searched for a target object in the presence of a critical distractor object. The color of the critical distractor either matched or mismatched (a) the color of an item maintained in visual working memory for a secondary task (Experiment 1), or (b) the color of the target, cued by a picture before search commenced (Experiments 2 and 3)...
August 10, 2017: Journal of Experimental Psychology. Human Perception and Performance
https://www.readbyqxmd.com/read/28780400/visual-cortical-networks-align-with-behavioral-measures-of-context-sensitivity-in-early-childhood
#5
Moritz Köster, Johanna Castel, Thomas Gruber, Joscha Kärtner
This study investigates how visual cortical networks align with context-sensitivity, namely the relative focus on the object versus the background of a visual scene, in early childhood. Context-sensitivity was assessed by a picture description and a recognition memory task. To segregate object and background processing in the visual cortex in 5- and 7-year-old children, object and background were presented at different frequencies (12 Hz or 15 Hz), evoking disparate neuronal responses (steady state visually evoked potentials, SSVEPs) in the electroencephalogram...
August 2, 2017: NeuroImage
https://www.readbyqxmd.com/read/28764452/modeling-speech-localization-talker-identification-and-word-recognition-in-a-multi-talker-setting
#6
Angela Josupeit, Volker Hohmann
This study introduces a model for solving three different auditory tasks in a multi-talker setting: target localization, target identification, and word recognition. The model was used to simulate psychoacoustic data from a call-sign-based listening test involving multiple spatially separated talkers [Brungart and Simpson (2007). Percept. Psychophys. 69(1), 79-91]. The main characteristics of the model are (i) the extraction of salient auditory features ("glimpses") from the multi-talker signal and (ii) the use of a classification method that finds the best target hypothesis by comparing feature templates from clean target signals to the glimpses derived from the multi-talker mixture...
July 2017: Journal of the Acoustical Society of America
https://www.readbyqxmd.com/read/28760565/familiarity-and-recollection-vs-representational-models-of-medial-temporal-lobe-structures-a-single-case-study
#7
Emilie Lacot, Stéphane Vautier, Stefan Kőhler, Jérémie Pariente, Chris B Martin, Michèle Puel, Jean-Albert Lotterie, Emmanuel J Barbeau
Although it is known that medial temporal lobe (MTL) structures support declarative memory, the fact these structures have different architectonics and circuitry suggests they may also play different functional roles. Selective lesions of MTL structures offer an opportunity to understand these roles. We report, in this study, on JMG, a patient who presents highly unusual lesions that completely affected all MTL structures except for the right hippocampus and parts of neighbouring medial parahippocampal cortex...
July 29, 2017: Neuropsychologia
https://www.readbyqxmd.com/read/28738074/adversity-emotion-recognition-and-empathic-concern-in-high-risk-youth
#8
Jodi A Quas, Kelli L Dickerson, Richard Matthew, Connor Harron, Catherine M Quas
Little is known about how emotion recognition and empathy jointly operate in youth growing up in contexts defined by persistent adversity. We investigated whether adversity exposure in two groups of youth was associated with reduced empathy and whether deficits in emotion recognition mediated this association. Foster, rural poor, and comparison youth from Swaziland, Africa identified emotional expressions and rated their empathic concern for characters depicted in images showing positive, ambiguous, and negative scenes...
2017: PloS One
https://www.readbyqxmd.com/read/28708559/texture-characterization-using-shape-co-occurrence-patterns
#9
Gui-Song Xia, Gang Liu, Xiang Bai, Liangpei Zhang
Texture characterization is a key problem in image understanding and pattern recognition. In this paper, we present a flexible shape-based texture representation using shape co-occurrence patterns. More precisely, texture images are first represented by a tree of shapes, each of which is associated with several geometrical and radiometric attributes. Then, four typical kinds of shape co-occurrence patterns based on the hierarchical relationships among the shapes in the tree are learned as codewords. Three different coding methods are investigated for learning the codewords, which can be used to encode any given texture image into a descriptive vector...
July 12, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28707123/visual-properties-and-memorising-scenes-effects-of-image-space-sparseness-and-uniformity
#10
Jiří Lukavský, Filip Děchtěrenko
Previous studies have demonstrated that humans have a remarkable capacity to memorise a large number of scenes. The research on memorability has shown that memory performance can be predicted by the content of an image. We explored how remembering an image is affected by the image properties within the context of the reference set, including the extent to which it is different from its neighbours (image-space sparseness) and if it belongs to the same category as its neighbours (uniformity). We used a reference set of 2,048 scenes (64 categories), evaluated pairwise scene similarity using deep features from a pretrained convolutional neural network (CNN), and calculated the image-space sparseness and uniformity for each image...
July 13, 2017: Attention, Perception & Psychophysics
https://www.readbyqxmd.com/read/28692990/discriminative-block-diagonal-representation-learning-for-image-recognition
#11
Zheng Zhang, Yong Xu, Ling Shao, Jian Yang
Existing block-diagonal representation studies mainly focuses on casting block-diagonal regularization on training data, while only little attention is dedicated to concurrently learning both block-diagonal representations of training and test data. In this paper, we propose a discriminative block-diagonal low-rank representation (BDLRR) method for recognition. In particular, the elaborate BDLRR is formulated as a joint optimization problem of shrinking the unfavorable representation from off-block-diagonal elements and strengthening the compact block-diagonal representation under the semisupervised framework of LRR...
July 4, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28692962/bilinear-convolutional-neural-networks-for-fine-grained-visual-recognition
#12
Tsung-Yu Lin, Aruni RoyChowdhury, Subhransu Maji
We present a simple and effective architecture for fine-grained recognition called Bilinear Convolutional Neural Networks (B-CNNs). These networks represent an image as a pooled outer product of features derived from two CNNs and capture localized feature interactions in a translationally invariant manner. B-CNNs are related to orderless texture representations built on deep features but can be trained in an end-to-end manner. Our most accurate model obtains 84.1%, 79.4%, 84.5% and 91.3% per-image accuracy on the Caltech-UCSD birds [66], NABirds [63], FGVC aircraft [42], and Stanford cars [33] dataset respectively and runs at 30 frames-per-second on a NVIDIA Titan X GPU...
July 4, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28692961/places-a-10-million-image-database-for-scene-recognition
#13
Bolei Zhou, Agata Lapedriza, Aditya Khosla, Aude Oliva, Antonio Torralba
The rise of multi-million-item dataset initiatives has enabled data-hungry machine learning algorithms to reach near-human semantic classification performance at tasks such as visual object and scene recognition. Here we describe the Places Database, a repository of 10 million scene photographs, labeled with scene semantic categories, comprising a large and diverse list of the types of environments encountered in the world. Using the state-of-the-art Convolutional Neural Networks (CNNs), we provide scene classification CNNs (Places-CNNs) as baselines, that significantly outperform the previous approaches...
July 4, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28687603/interaction-between-scene-and-object-processing-revealed-by-human-fmri-and-meg-decoding
#14
Talia Brandman, Marius Vincent Peelen
Scenes strongly facilitate object recognition, such as when we make out the shape of a distant boat on the water. Yet, though known to interact in perception, neuroimaging research has primarily provided evidence for separate scene- and object-selective cortical pathways. This raises the question of how these pathways interact to support context-based perception. Here we used a novel approach in human fMRI and MEG studies to reveal supra-additive scene-object interactions. Participants (men and women) viewed degraded objects that were hard to recognize when presented in isolation but easy to recognize within their original scene context, in which no other associated objects were present...
July 7, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28679874/find-your-passion-lead-with-purpose-a-health-informaticians-guide
#15
Mowafa Househ
Health Informatics is an ever evolving, changing and dynamic field that has become the disruptive innovation shaping the future of healthcare. Health informaticians face a number of challenges in the workplace such as gaining acceptance and recognition from other healthcare providers and overcoming the resistance of healthcare providers from using technology in clinical practice. Being a health informatician is not for the faint hearted, especially as resistance to the role of health informaticians continues from both healthcare providers and hospital administrators...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28677635/build-a-robust-learning-feature-descriptor-by-using-a-new-image-visualization-method-for-indoor-scenario-recognition
#16
Jichao Jiao, Xin Wang, Zhongliang Deng
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...
July 4, 2017: Sensors
https://www.readbyqxmd.com/read/28661440/online-recognition-of-daily-activities-by-color-depth-sensing-and-knowledge-models
#17
Carlos Fernando Crispim-Junior, Alvaro Gómez Uría, Carola Strumia, Michal Koperski, Alexandra König, Farhood Negin, Serhan Cosar, Anh Tuan Nghiem, Duc Phu Chau, Guillaume Charpiat, Francois Bremond
Visual activity recognition plays a fundamental role in several research fields as a way to extract semantic meaning of images and videos. Prior work has mostly focused on classification tasks, where a label is given for a video clip. However, real life scenarios require a method to browse a continuous video flow, automatically identify relevant temporal segments and classify them accordingly to target activities. This paper proposes a knowledge-driven event recognition framework to address this problem. The novelty of the method lies in the combination of a constraint-based ontology language for event modeling with robust algorithms to detect, track and re-identify people using color-depth sensing (Kinect(®) sensor)...
June 29, 2017: Sensors
https://www.readbyqxmd.com/read/28659194/out-of-hospital-cardio-pulmonary-arrest-is-there-a-role-for-the-primary-healthcare-teams
#18
Shlomo Vinker
Out of hospital cardiac arrest (OHCA) remains a major cause of morbidity and mortality. The survival rates are poor and even more frustrating are the rates of neurologically favorable outcomes at hospital discharge. In a recent IJHPR article, Einav et al. concluded that many primary care clinics are underequipped and the physicians underprepared to initiate life-saving services. The chance of having an OHCA in a primary care clinic is very low. But although the impact is small, primary care teams as well as other out-of-hospital healthcare personal should be familiar with the telephone number for summoning emergency medical services (EMS), be aware of the location of the defibrillator in their clinic, and know how to use it...
June 28, 2017: Israel Journal of Health Policy Research
https://www.readbyqxmd.com/read/28654817/the-role-of-the-hippocampus-in-recognition-memory
#19
REVIEW
Chris M Bird
Many theories of declarative memory propose that it is supported by partially separable processes underpinned by different brain structures. The hippocampus plays a critical role in binding together item and contextual information together and processing the relationships between individual items. By contrast, the processing of individual items and their later recognition can be supported by extrahippocampal regions of the medial temporal lobes (MTL), particularly when recognition is based on feelings of familiarity without the retrieval of any associated information...
August 2017: Cortex; a Journal Devoted to the Study of the Nervous System and Behavior
https://www.readbyqxmd.com/read/28650721/photographic-memory-the-effects-of-volitional-photo-taking-on-memory-for-visual-and-auditory-aspects-of-an-experience
#20
Alixandra Barasch, Kristin Diehl, Jackie Silverman, Gal Zauberman
How does volitional photo taking affect unaided memory for visual and auditory aspects of experiences? Across one field and three lab studies, we found that, even without revisiting any photos, participants who could freely take photographs during an experience recognized more of what they saw and less of what they heard, compared with those who could not take any photographs. Further, merely taking mental photos had similar effects on memory. These results provide support for the idea that photo taking induces a shift in attention toward visual aspects and away from auditory aspects of an experience...
August 2017: Psychological Science
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