keyword
MENU ▼
Read by QxMD icon Read
search

scene recognition

keyword
https://www.readbyqxmd.com/read/28531101/phrog-a-multimodal-feature-for-place-recognition
#1
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
#2
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
#3
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
#4
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
#5
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
#6
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
#7
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
#8
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
#9
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
#10
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
https://www.readbyqxmd.com/read/28436864/tracking-based-multi-orientation-scene-text-detection-a-unified-framework-with-dynamic-programming
#11
Chun Yang, Xu-Cheng Yin, Wei-Yi Pei, Shu Tian, Ze-Yu Zuo, Chao Zhu, Junchi Yan
There are a variety of grand challenges for multiorientation text detection in scene videos, where the typical issues include skew distortion, low contrast and arbitrary motion. Most conventional video text detection methods using individual frames have limited performance. In this paper, we propose a novel tracking based multi-orientation scene text detection method using multiple frames within a unified framework via dynamic programming. First, a multi-information fusion based multiorientation text detection method in each frame is proposed to extensively locate possible character candidates and extract text regions with multiple channels and scales...
April 18, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28422661/correlated-topic-vector-for-scene-classification
#12
Pengxu Wei, Fei Qin, Fang Wan, Yi Zhu, Jianbin Jiao, Qixiang Ye
Scene images usually involve semantic correlations, particularly when considering large-scale image datasets. This paper proposes a novel generative image representation, Correlated Topic Vector, to model such semantic correlations. Oriented from the correlated topic model, Correlated Topic Vector intends to naturally utilize the correlations among topics which are seldom considered in the conventional feature encoding, e.g., Fisher Vector, but do exist in scene images. It is expected that the involvement of correlations can increase the discriminative capability of the learned generative model and consequently improve the recognition accuracy...
April 13, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28422537/morbidity-and-mortality-associated-with-prehospital-lift-assist-calls
#13
Lauren Leggatt, Kristine Van Aarsen, Melanie Columbus, Adam Dukelow, Michael Lewell, Matthew Davis, Shelley McLeod
INTRODUCTION: When an individual requires assistance with mobilization, emergency medical services (EMS) may be called. If a patient does not receive treatment on scene and is not transported to hospital, these are referred to as "Lift Assist" (LA) calls. It is possible this need for assistance represents a subtle onset of a disease process or decline in function. Without recognition or treatment, the patient may be at risk for recurrent falls, repeat EMS visits or worsening illness. OBJECTIVE: To examine the 14-day morbidity and mortality associated with LA calls and determine factors that are associated with increased risk of these outcomes...
April 19, 2017: Prehospital Emergency Care
https://www.readbyqxmd.com/read/28420155/new-compact-3-dimensional-shape-descriptor-for-a-depth-camera-in-indoor-environments
#14
Hyukdoo Choi, Euntai Kim
This study questions why existing local shape descriptors have high dimensionalities (up to hundreds) despite simplicity of local shapes. We derived an answer from a historical context and provided an alternative solution by proposing a new compact descriptor. Although existing descriptors can express complicated shapes and depth sensors have been improved, complex shapes are rarely observed in an ordinary environment and a depth sensor only captures a single side of a surface with noise. Therefore, we designed a new descriptor based on principal curvatures, which is compact but practically useful...
April 16, 2017: Sensors
https://www.readbyqxmd.com/read/28413566/a-hierarchical-predictive-coding-model-of-object-recognition-in-natural-images
#15
M W Spratling
Predictive coding has been proposed as a model of the hierarchical perceptual inference process performed in the cortex. However, results demonstrating that predictive coding is capable of performing the complex inference required to recognise objects in natural images have not previously been presented. This article proposes a hierarchical neural network based on predictive coding for performing visual object recognition. This network is applied to the tasks of categorising hand-written digits, identifying faces, and locating cars in images of street scenes...
2017: Cognitive Computation
https://www.readbyqxmd.com/read/28410105/dynamic-textures-modeling-via-joint-video-dictionary-learning
#16
Xian Wei, Yuanxiang Li, Hao Shen, Fang Chen, Martin Kleinsteuber, Zhongfeng Wang
Video representation is an important and challenging task in the computer vision community. In this paper, we consider the problem of modeling and classifying video sequences of dynamic scenes which could be modeled in a dynamic textures (DT) framework. At first, we assume that image frames of a moving scene can be modeled as a Markov random process. We propose a sparse coding framework, named joint video dictionary learning (JVDL), to model a video adaptively. By treating the sparse coefficients of image frames over a learned dictionary as the underlying "states", we learn an efficient and robust linear transition matrix between two adjacent frames of sparse events in time series...
April 6, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28382195/superordinate-level-processing-has-priority-over-basic-level-processing-in-scene-gist-recognition
#17
Qi Sun, Yanju Ren, Yang Zheng, Mingxia Sun, Yuanjie Zheng
By combining a perceptual discrimination task and a visuospatial working memory task, the present study examined the effects of visuospatial working memory load on the hierarchical processing of scene gist. In the perceptual discrimination task, two scene images from the same (manmade-manmade pairing or natural-natural pairing) or different superordinate level categories (manmade-natural pairing) were presented simultaneously, and participants were asked to judge whether these two images belonged to the same basic-level category (e...
November 2016: I-Perception
https://www.readbyqxmd.com/read/28377161/category-selectivity-in-human-visual-cortex-beyond-visual-object-recognition
#18
Marius V Peelen, Paul E Downing
Human ventral temporal cortex shows a categorical organization, with regions responding selectively to faces, bodies, tools, scenes, words, and other categories. Why is this? Traditional accounts explain category selectivity as arising within a hierarchical system dedicated to visual object recognition. For example, it has been proposed that category selectivity reflects the clustering of category-associated visual feature representations, or that it reflects category-specific computational algorithms needed to achieve view invariance...
April 1, 2017: Neuropsychologia
https://www.readbyqxmd.com/read/28375371/three-dimensional-profilometric-reconstruction-using-flexible-sensing-integral-imaging-and-occlusion-removal
#19
Xin Shen, Adam Markman, Bahram Javidi
We present a method for three-dimensional (3D) profilometric reconstruction using flexible sensing integral imaging with object recognition and automatic occlusion removal. Two-dimensional images, known as elemental images (EIs), of a scene containing an object behind occlusion are captured by flexible sensing integral imaging using a moving camera randomly placed on a non-planar surface with unknown camera position and orientation. After 3D image acquisition, the unknown camera poses are estimated using the EIs and 3D reconstruction is performed based on flexible sensing integral imaging...
March 20, 2017: Applied Optics
https://www.readbyqxmd.com/read/28368817/single-view-3d-scene-reconstruction-and-parsing-by-attribute-grammar
#20
Xiaobai Liu, Yibiao Zhao, Song-Chun Zhu
In this paper, we present an attribute grammar for solving two coupled tasks: i) parsing an 2D image into semantic regions; and ii) recovering the 3D scene structures of all regions. The proposed grammar consists of a set of production rules, each describing a kind of spatial relation between planar surfaces in 3D scenes. These production rules are used to decompose an input image into a hierarchical parse graph representation where each graph node indicates a planar surface or a composite surface. Different from other stochastic image grammars, the proposed grammar augments each graph node with a set of attribute variables to depict scene-level global geometry, e...
March 29, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
keyword
keyword
102340
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"