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https://www.readbyqxmd.com/read/28633321/places-in-the-brain-bridging-layout-and-object-geometry-in-scene-selective-cortex
#1
Moira R Dillon, Andrew S Persichetti, Elizabeth S Spelke, Daniel D Dilks
Diverse animal species primarily rely on sense (left-right) and egocentric distance (proximal-distal) when navigating the environment. Recent neuroimaging studies with human adults show that this information is represented in 2 scene-selective cortical regions-the occipital place area (OPA) and retrosplenial complex (RSC)-but not in a third scene-selective region-the parahippocampal place area (PPA). What geometric properties, then, does the PPA represent, and what is its role in scene processing? Here we hypothesize that the PPA represents relative length and angle, the geometric properties classically associated with object recognition, but only in the context of large extended surfaces that compose the layout of a scene...
June 13, 2017: Cerebral Cortex
https://www.readbyqxmd.com/read/28632043/simultanagnosia-and-object-individuation
#2
Veronica Mazza
Simultanagnosic patients have difficulty in perceiving multiple objects when presented simultaneously. In this review article, I discuss how neuropsychological research on simultanagnosia has been inspirational for two interconnected lines of research related to the core mechanisms by which the visual system processes cluttered scenes. First, I review previous studies on enumeration tasks indicating that, despite their inability to identify multiple objects, simultanagnosic patients can enumerate up to 2-3 elements as efficiently as healthy individuals (the so-called "subitizing" phenomenon)...
June 6, 2017: Cognitive Neuropsychology
https://www.readbyqxmd.com/read/28611840/deep-learning-for-plant-identification-in-natural-environment
#3
Yu Sun, Yuan Liu, Guan Wang, Haiyan Zhang
Plant image identification has become an interdisciplinary focus in both botanical taxonomy and computer vision. The first plant image dataset collected by mobile phone in natural scene is presented, which contains 10,000 images of 100 ornamental plant species in Beijing Forestry University campus. A 26-layer deep learning model consisting of 8 residual building blocks is designed for large-scale plant classification in natural environment. The proposed model achieves a recognition rate of 91.78% on the BJFU100 dataset, demonstrating that deep learning is a promising technology for smart forestry...
2017: Computational Intelligence and Neuroscience
https://www.readbyqxmd.com/read/28608811/simple-smartphone-based-guiding-system-for-visually-impaired-people
#4
Bor-Shing Lin, Cheng-Che Lee, Pei-Ying Chiang
Visually impaired people are often unaware of dangers in front of them, even in familiar environments. Furthermore, in unfamiliar environments, such people require guidance to reduce the risk of colliding with obstacles. This study proposes a simple smartphone-based guiding system for solving the navigation problems for visually impaired people and achieving obstacle avoidance to enable visually impaired people to travel smoothly from a beginning point to a destination with greater awareness of their surroundings...
June 13, 2017: Sensors
https://www.readbyqxmd.com/read/28584956/natural-scenes-can-be-identified-as-rapidly-as-individual-features
#5
Piers D L Howe
Can observers determine the gist of a natural scene in a purely feedforward manner, or does this process require deliberation and feedback? Observers can recognise images that are presented for very brief periods of time before being masked. It is unclear whether this recognition process occurs in a purely feedforward manner or whether feedback from higher cortical areas to lower cortical areas is necessary. The current study revealed that the minimum presentation time required to identify or to determine the gist of a natural scene was no different from that required to determine the orientation or colour of an isolated line...
June 5, 2017: Attention, Perception & Psychophysics
https://www.readbyqxmd.com/read/28545983/feedback-from-higher-to-lower-visual-areas-for-visual-recognition-may-be-weaker-in-the-periphery-glimpses-from-the-perception-of-brief-dichoptic-stimuli
#6
Li Zhaoping
Eye movements bring attended visual inputs to the center of vision for further processing. Thus, central and peripheral vision should have different functional roles. Here, we use observations of visual perception under dichoptic stimuli to infer that there is a difference in the top-down feedback from higher brain centers to primary visual cortex. Visual stimuli to the two eyes were designed such that the sum and difference of the binocular input from the two eyes have the form of two different gratings. These gratings differed in their motion direction, tilt direction, or color, and duly evoked ambiguous percepts for the corresponding feature...
June 6, 2017: Vision Research
https://www.readbyqxmd.com/read/28541898/con-text-text-detection-for-fine-grained-object-classification
#7
Sezer Karaoglu, Ran Tao, Jan C van Gemert, Theo Gevers
This work focuses on fine-grained object classification using recognized scene text in natural images. While the state-of-the-art relies on visual cues only, this paper is the first work which proposes to combine textual and visual cues. Another novelty is the textual cue extraction. Unlike the state-of-the-art text detection methods, we focus more on the background instead of text regions. Once text regions are detected, they are further processed by two methods to perform text recognition i.e. ABBYY commercial OCR engine and a state-of-the-art character recognition algorithm...
May 24, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28534775/learning-rotation-invariant-local-binary-descriptor
#8
Yueqi Duan, Jiwen Lu, Jianjiang Feng, Jie Zhou
In this paper, we propose a rotation-invariant local binary descriptor (RI-LBD) learning method for visual recognition. Compared with hand-crafted local binary descriptors such as LBP and its variants which require strong prior knowledge, local binary feature learning methods are more efficient and dataadaptive. Unlike existing learning-based local binary descriptors such as compact binary face descriptor (CBFD) and simultaneous local binary feature learning and encoding (SLBFLE) which are susceptible to rotations, our RI-LBD first categorizes each local patch into a rotational binary pattern (RBP), and then jointly learns the orientation for each pattern and the projection matrix to obtain rotation-invariant local binary descriptors...
May 16, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28534732/evaluation-of-adaptive-noise-management-technologies-for-school-age-children-with-hearing-loss
#9
Jace Wolfe, Mila Duke, Erin Schafer, Christine Jones, Lori Rakita
BACKGROUND: Children with hearing loss experience significant difficulty understanding speech in noisy and reverberant situations. Adaptive noise management technologies, such as fully adaptive directional microphones and digital noise reduction, have the potential to improve communication in noise for children with hearing aids. However, there are no published studies evaluating the potential benefits children receive from the use of adaptive noise management technologies in simulated real-world environments as well as in daily situations...
May 2017: Journal of the American Academy of Audiology
https://www.readbyqxmd.com/read/28532349/capabilities-and-limitations-of-peripheral-vision
#10
Ruth Rosenholtz
This review discusses several pervasive myths about peripheral vision, as well as what is actually true: Peripheral vision underlies a broad range of visual tasks, in spite of its significant loss of information. New understanding of peripheral vision, including likely mechanisms, has deep implications for our understanding of vision. From peripheral recognition to visual search, from change blindness to getting the gist of a scene, a lossy but relatively fixed peripheral encoding may determine the difficulty of many tasks...
October 14, 2016: Annual Review of Vision Science
https://www.readbyqxmd.com/read/28531101/phrog-a-multimodal-feature-for-place-recognition
#11
Fabien Bonardi, Samia Ainouz, Rémi Boutteau, Yohan Dupuis, Xavier Savatier, Pascal Vasseur
Long-term place recognition in outdoor environments remains a challenge due to high appearance changes in the environment. The problem becomes even more difficult when the matching between two scenes has to be made with information coming from different visual sources, particularly with different spectral ranges. For instance, an infrared camera is helpful for night vision in combination with a visible camera. In this paper, we emphasize our work on testing usual feature point extractors under both constraints: repeatability across spectral ranges and long-term appearance...
May 20, 2017: Sensors
https://www.readbyqxmd.com/read/28523466/recognition-induced-forgetting-does-not-occur-for-temporally-grouped-objects-unless-they-are-semantically-related
#12
Ashleigh M Maxcey, Hannah Glenn, Elisabeth Stansberry
Recent evidence has shown that practice recognizing certain objects hurts memories of objects from the same category, a phenomenon called recognition-induced forgetting. In all previous studies of this effect, the objects have been related by semantic category (e.g., instances of vases). However, the relationship between objects in many real-world visual situations stresses temporal grouping rather than semantic relations (e.g., a weapon and getaway car at a crime scene), and temporal grouping is thought to cluster items in models of long-term memory...
May 18, 2017: Psychonomic Bulletin & Review
https://www.readbyqxmd.com/read/28503145/a-neural-dynamic-architecture-for-concurrent-estimation-of-object-pose-and-identity
#13
Oliver Lomp, Christian Faubel, Gregor Schöner
Handling objects or interacting with a human user about objects on a shared tabletop requires that objects be identified after learning from a small number of views and that object pose be estimated. We present a neurally inspired architecture that learns object instances by storing features extracted from a single view of each object. Input features are color and edge histograms from a localized area that is updated during processing. The system finds the best-matching view for the object in a novel input image while concurrently estimating the object's pose, aligning the learned view with current input...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28500002/cross-label-suppression-a-discriminative-and-fast-dictionary-learning-with-group-regularization
#14
Xiudong Wang, Yuantao Gu
This paper addresses image classification through learning a compact and discriminative dictionary efficiently. Given a structured dictionary with each atom (columns in the dictionary matrix) related to some label, we propose crosslabel suppression constraint to enlarge the difference among representations for different classes. Meanwhile, we introduce group regularization to enforce representations to preserve label properties of original samples, meaning the representations for the same class are encouraged to be similar...
May 10, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28481270/smartphone-based-escalator-recognition-for-the-visually-impaired
#15
Daiki Nakamura, Hotaka Takizawa, Mayumi Aoyagi, Nobuo Ezaki, Shinji Mizuno
It is difficult for visually impaired individuals to recognize escalators in everyday environments. If the individuals ride on escalators in the wrong direction, they will stumble on the steps. This paper proposes a novel method to assist visually impaired individuals in finding available escalators by the use of smartphone cameras. Escalators are recognized by analyzing optical flows in video frames captured by the cameras, and auditory feedback is provided to the individuals. The proposed method was implemented on an Android smartphone and applied to actual escalator scenes...
May 6, 2017: Sensors
https://www.readbyqxmd.com/read/28463270/tracking-background-oriented-schlieren-for-observing-shock-oscillations-of-transonic-flying-objects
#16
Tomohiro Sueishi, Masato Ishii, Masatoshi Ishikawa
A detailed understanding of the in-flight behavior of high-speed flying objects is useful in the forensic investigation of crime scenes. In particular, for transonic flying objects with associated unsteady shock waves, long-duration and high-resolution measurements are desirable but difficult with conventional optical visualization methods. In this study, we propose a tracking background-oriented schlieren (BOS) method that uses a mirror-based high-speed optical axis controller and a striped retroreflective background...
May 1, 2017: Applied Optics
https://www.readbyqxmd.com/read/28458481/comparing-object-recognition-from-binary-and-bipolar-edge-images-for-visual-prostheses
#17
Jae-Hyun Jung, Tian Pu, Eli Peli
Visual prostheses require an effective representation method due to the limited display condition which has only 2 or 3 levels of grayscale in low resolution. Edges derived from abrupt luminance changes in images carry essential information for object recognition. Typical binary (black and white) edge images have been used to represent features to convey essential information. However, in scenes with a complex cluttered background, the recognition rate of the binary edge images by human observers is limited and additional information is required...
November 2016: Journal of Electronic Imaging
https://www.readbyqxmd.com/read/28437797/central-and-peripheral-vision-for-scene-recognition-a-neurocomputational-modeling-exploration
#18
Panqu Wang, Garrison W Cottrell
What are the roles of central and peripheral vision in human scene recognition? Larson and Loschky (2009) showed that peripheral vision contributes more than central vision in obtaining maximum scene recognition accuracy. However, central vision is more efficient for scene recognition than peripheral, based on the amount of visual area needed for accurate recognition. In this study, we model and explain the results of Larson and Loschky (2009) using a neurocomputational modeling approach. We show that the advantage of peripheral vision in scene recognition, as well as the efficiency advantage for central vision, can be replicated using state-of-the-art deep neural network models...
April 1, 2017: Journal of Vision
https://www.readbyqxmd.com/read/28437623/selective-scene-perception-deficits-in-a-case-of-topographical-disorientation
#19
Jessica Robin, Matthew X Lowe, Sara Pishdadian, Josée Rivest, Jonathan S Cant, Morris Moscovitch
Topographical disorientation (TD) is a neuropsychological condition characterized by an inability to find one's way, even in familiar environments. One common contributing cause of TD is landmark agnosia, a visual recognition impairment specific to scenes and landmarks. Although many cases of TD with landmark agnosia have been documented, little is known about the perceptual mechanisms which lead to selective deficits in recognizing scenes. In the present study, we test LH, a man who exhibits TD and landmark agnosia, on measures of scene perception that require selectively attending to either the configural or surface properties of a scene...
April 2, 2017: Cortex; a Journal Devoted to the Study of the Nervous System and Behavior
https://www.readbyqxmd.com/read/28436874/track-everything-limiting-prior-knowledge-in-online-multi-object-recognition
#20
Sebastien C Wong, Victor Stamatescu, Adam Gatt, David Kearney, Ivan Lee, Mark D McDonnell
This paper addresses the problem of online tracking and classification of multiple objects in an image sequence. Our proposed solution is to first track all objects in the scene without relying on object-specific prior knowledge, which in other systems can take the form of hand-crafted features or user-based track initialization. We then classify the tracked objects with a fastlearning image classifier that is based on a shallow convolutional neural network architecture and demonstrate that object recognition improves when this is combined with object state information from the tracking algorithm...
April 24, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
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