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https://www.readbyqxmd.com/read/28708559/texture-characterization-using-shape-co-occurrence-patterns
#1
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
#2
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
#3
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
#4
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
#5
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
#6
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
#7
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
#8
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
#9
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
#10
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
#11
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...
June 1, 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
#12
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...
June 1, 2017: Psychological Science
https://www.readbyqxmd.com/read/28644809/structured-kernel-dictionary-learning-with-correlation-constraint-for-object-recognition
#13
Zhengjue Wang, Yinghua Wang, Hongwei Liu, Hao Zhang
In this paper, we propose a new discriminative non-linear dictionary learning approach, called correlation constrained structured kernel KSVD, for object recognition. The objective function for dictionary learning contains a reconstructive term and a discriminative term. In the reconstructive term, signals are implicitly non-linearly mapped into a space, where a structured kernel dictionary, each sub-dictionary of which lies in the span of the mapped signals from the corresponding class, is established. In the discriminative term, by analyzing the classification mechanism, the correlation constraint is proposed in kernel form, constraining the correlations between different discriminative codes, and restricting the coefficient vectors to be transformed into a feature space, where the features are highly correlated inner-class and nearly independent between-classes...
June 21, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28633321/places-in-the-brain-bridging-layout-and-object-geometry-in-scene-selective-cortex
#14
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
#15
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
#16
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
#17
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
#18
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
#19
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
#20
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
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