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Implicit color segmentation features for pedestrian and object detection

P Ott, M Everingham
2009 2009 IEEE 12th International Conference on Computer Vision  
We propose a novel feature extraction scheme which computes implicit 'soft segmentations' of image regions into foreground/background.  ...  The method yields stronger object/background edges than grayscale gradient alone, suppresses textural and shading variations, and captures local coherence of object appearance.  ...  Financial support for this work was provided by EPSRC project HAML and an RCUK Academic Fellowship.  ... 
doi:10.1109/iccv.2009.5459238 dblp:conf/iccv/OttE09 fatcat:5c5ahlkqk5bxnihbxij6ntsz2i

Foreground Object Detection and Separation Based on Region Contrast

2017 Iraqi Journal of Science  
Comparisons with general foreground detectors such as background subtraction techniques our approach are able to detect important target for case the target is moving or not and can separate foreground  ...  Foreground objects detection is very important for several approaches like object recognition, surveillance, image annotation, and image retrieval, etc.  ...  An approach for detect and segment (separate) foreground object has been proposed depending on region contrast.  ... 
doi:10.24996/ijs.2017.58.4a.18 fatcat:fnnaesj2ajc7zfqt352xlbzisu

Research on Salient Object Detection using Deep Learning and Segmentation Methods

2019 International journal of recent technology and engineering  
Detecting and segmenting salient objects in natural scenes, often referred to as salient object detection has attracted a lot of interest in computer vision and recently various heuristic computational  ...  The aim of this review work is to study about the details of methods in salient object detection.  ...  Saliency detection is carried out in a two-stage scheme to extract background regions and foreground salient objects efficiently.  ... 
doi:10.35940/ijrte.b1046.0982s1119 fatcat:6ofq53vb7zhx7boq4ndpraphs4

Unsupervised Single Moving Object Detection Based on Coarse-to-Fine Segmentation

2016 KSII Transactions on Internet and Information Systems  
Given the sparsely labelled trajectory points, we adopt a coarse-to-fine strategy to detect and segment the foreground from the background.  ...  Abstract An efficient and effective unsupervised single moving object detection framework is presented in this paper.  ...  Introduction Moving object detection aims to detect and segment moving objects from the scene.  ... 
doi:10.3837/tiis.2016.06.012 fatcat:46icxv222zb4th4d2zi5wtdxku

Live Video Montage with a Rotating Camera

Zilong Dong, Lei Jiang, Guofeng Zhang, Qing Wang, Hujun Bao
2009 Computer graphics forum (Print)  
for many real world online applications.  ...  the dynamic foreground.  ...  Xiaofei He for his enormous help in revising this paper, and the anonymous reviewers for their valuable comments. This work is supported by the 973 program of China (  ... 
doi:10.1111/j.1467-8659.2009.01551.x fatcat:5diy6xqdvvfrdameu52edt7pfy

Detecting moving objects from dynamic background with shadow removal

Shih-Chieh Wang, Te-Feng Su, Shang-Hong Lai
2011 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
In this paper, we propose an adaptive Local-Patch Gaussian Mixture Model (LPGMM) as the dynamic background model for detecting moving objects from video with dynamic background.  ...  subtraction is commonly used to detect foreground objects in video surveillance. Traditional background subtraction methods are usually based on the assumption that the background is stationary.  ...  Much effort has been devoted to developing efficient methods of moving object detection using background subtraction.  ... 
doi:10.1109/icassp.2011.5946556 dblp:conf/icassp/WangSL11 fatcat:n46fqtjcyvgufif5hz35iptkmu

Local Compact Binary Count based Nonparametric Background Modeling for Foreground Detection in Dynamic Scenes

Wei He, Yong K-wan Kim, Hak-Lim Ko, Jianhui Wu, Wujing Li, Bing Tu
2019 IEEE Access  
INDEX TERMS Foreground detection, nonparametric background modeling, local compact binary count, dynamic background, video signal processing.  ...  Specifically, we present a novel local compact binary count (LCBC) feature that can capture local binary gray-scale difference information and totally discard the local binary structural information.  ...  INTRODUCTION Background subtraction is generally regarded as an effective technique for detecting foreground objects in video sequences.  ... 
doi:10.1109/access.2019.2927745 fatcat:jutjchnlknce7biqs2bibbvbsq

Real-time Stable Texture Regions Extraction for Motion-Based Object Segmentation

Dubravko Culibrk, Borislav Antic, Vladimir Crnojevic
2009 Procedings of the British Machine Vision Conference 2009  
Although used extensively for object recognition, texture has lately been ignored as a feature used for background modelling and object segmentation.  ...  The paper proposes an approach that can be used to detect regions of texture, stable enough to be modelled using probabilistic models commonly used for foreground segmentation.  ...  For the first data set the proposed features allowed the segmentation to detect more foreground pixels (see Fig. 2 ).  ... 
doi:10.5244/c.23.17 dblp:conf/bmvc/CulibrkAC09 fatcat:pcdvl4gldvgtlin4jiicuwlale

Accurate Localization of 3D Objects from RGB-D Data Using Segmentation Hypotheses

Byung-soo Kim, Shili Xu, Silvio Savarese
2013 2013 IEEE Conference on Computer Vision and Pattern Recognition  
In this paper we focus on the problem of detecting objects in 3D from RGB-D images.  ...  We propose a novel framework that explores the compatibility between segmentation hypotheses of the object in the image and the corresponding 3D map.  ...  We explored the idea of using segmentation hypotheses for the foreground object to guide the process of accurately localizing the object in 3D.  ... 
doi:10.1109/cvpr.2013.409 dblp:conf/cvpr/KimXS13 fatcat:kterdjrwdzef7ingxddujfmy4i

Using Segmentation to Verify Object Hypotheses

Deva Ramanan
2007 2007 IEEE Conference on Computer Vision and Pattern Recognition  
We present an approach for object recognition that combines detection and segmentation within a efficient hypothesize/test framework.  ...  At each hypothesized detection, we compute a local figure-ground segmentation using a window of slightly larger extent than that used by the classifier.  ...  Acknowledgments: Thanks to Navneet Dalal and Derek Hoiem for discussions and code and Xiaofeng Ren for his ViolaJones implementation.  ... 
doi:10.1109/cvpr.2007.383271 dblp:conf/cvpr/Ramanan07 fatcat:o2lja5qmg5cwvlqpvb6t6q4bnq

Arbitrary-Shape Object Localization Using Adaptive Image Grids [chapter]

Chunluan Zhou, Junsong Yuan
2013 Lecture Notes in Computer Science  
In this paper, we propose an efficient bottom-up approach for detecting arbitrary-shape objects using image grids as basic components.  ...  Sliding-window based search is a widely used technique for object localization.  ...  We thank Gangqiang Zhao for the help to proofread the paper.  ... 
doi:10.1007/978-3-642-37331-2_6 fatcat:lqklmz3juvfpvemlh3d24xtm54

Foreground Segmentation from Occlusions Using Structure and Motion Recovery [chapter]

Kai Cordes, Björn Scheuermann, Bodo Rosenhahn, Jörn Ostermann
2013 Communications in Computer and Information Science  
The knowledge of occluded parts of a connected feature track is used to feed an efficient segmentation algorithm which crops the foreground image regions automatically.  ...  For visual effect creation, the foreground segmentation is required for the integration of virtual objects between scene elements.  ...  Occlusion edges are detected [10] and used for the video segmentation of foreground objects.  ... 
doi:10.1007/978-3-642-38241-3_23 fatcat:brhdon4cgvfhzdpanzkw6omuvy

Moving Object Detection under Various Illumination Conditions for PTZ Cameras

E. Kozagal, B. Sarah Sweetlyn Christella
2016 Indian Journal of Science and Technology  
Finally GMM (Gaussian Mixture Model) is used for segmenting the foreground Extraction by the XCS-LBP descriptor with similarity measure.  ...  The fundamental step in video surveillance is the Moving object detection.  ...  Then these features are weighted, normalized and fed for the detection of foreground/background using GMM.  ... 
doi:10.17485/ijst/2016/v9i45/99004 fatcat:ni2ckwo6ubgrhj7uud4rqduatu

A comprehensive review of vehicle detection using computer vision

Aymen Fadhil Abbas, Usman ullah Sheikh, Fahad Taha AL-dhief, Mohd Norzali Haji Mohd
2021 TELKOMNIKA (Telecommunication Computing Electronics and Control)  
The challenges of vehicle detection in urban roads arise because of camera position, background variations, occlusion, multiple foreground objects as well as vehicle pose.  ...  The advantages and disadvantages among the techniques are also highlighted with a conclusion as to the most accurate one for vehicle detection.  ...  and Universiti Teknologi Malaysia (UTM) for their support under the Research University Grant (GUP), grant number 19H61.  ... 
doi:10.12928/telkomnika.v19i3.12880 fatcat:xkjir3yytzfr5a42nmi3j4tzza

Video Surveillance for Effective Object Detection with Alarm Triggering

B. Priyanka, A. Ramya, J. Sri Katheswari
2014 IOSR Journal of Computer Engineering  
This paper presents a novel algorithm for detection and segmentation of foreground objects from a video which contains both stationary and moving background objects and under-goes both gradual and sudden  ...  And the alarm triggers while a new object enters into the frame, the foreground information and background information are identified using the reference frame as background model .  ...  In this paper, we propose a general Bayesian framework which can integrate multiple features to model the background for foreground object detection.  ... 
doi:10.9790/0661-16272125 fatcat:d7uv4xydvbdvxoz3xwgjhqxeda
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