Results 211 to 220 of about 115,245 (245)

Hierarchical Foreground Detection in Dynamic Background

2011
Foreground detection in dynamic background is one of challenging problems in many vision-based applications. In this paper, we propose a hierarchical foreground detection algorithm in the HSL color space. With the proposed algorithm, the experimental precision in five testing sequences reached to 56.46%, which was the best among compared four methods.
Guoliang Lu, Mineichi Kudo, Jun Toyama
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Robust Foreground Detection In Video Using Pixel Layers

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008
A framework for robust foreground detection that works under difficult conditions such as dynamic background and moderately moving camera is presented in this paper. The proposed method includes two main components: coarse scene representation as the union of pixel layers, and foreground detection in video by propagating these layers using a maximum ...
Kedar A, Patwardhan, Guillermo, Sapiro, Vassilios, Morellas   +2 more
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Robust foreground detection using block-based RPCA

Optik, 2015
Abstract Robust foreground detection is difficult in real-life applications due to complex factors such as illumination change and background interference. A robust foreground detection approach using block-based RPCA is proposed in this paper. The input matrix is segmented into different blocks according to the initial segmentation.
Biao Yang, Ling Zou
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Foreground Gated Network for Surveillance Object Detection

2018 IEEE Fourth International Conference on Multimedia Big Data (BigMM), 2018
Object detection in surveillance videos is challenging due to the requirement of real-time detection of small objects in presence of motion blurs and over-exposures at night. False positives caused by above challenges on background areas are more critical in surveillance videos compared to general object detection.
Zhihang Fu, Chang Zhou, Hongwei Yong, Rongxin Jiang, Xiang Tian, Yaowu Chen, Xian-Sheng Hua   +6 more
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Foreground detection using background subtraction with histogram

2013 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), 2013
In the background subtraction method one of the core issue is; how to setup the threshold value precisely at run time, which can ultimately overcome several bugs of this approach in the foreground detection. In the proposed algorithm the key feature of any foreground detection algorithm; motion is used however getting the threshold value from the ...
Muhammad Nawaz, John Cosmas, Awais Adnan, Muhammad Inam Ul Haq, Eman Alazawi   +4 more
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STATISTICAL BACKGROUND MODELING FOR FOREGROUND DETECTION: A SURVEY

2009
Background modeling is often used in the context of moving objects detection from static cameras. Numerous methods have been developed over the recent years and the most used are the statistical ones. The purpose of this chapter is to provide a recent survey of these different statistical methods. For this, we have classified them in term of generation
Bouwmans, Thierry, El Baf, Fida, Vachon, Bertrand   +2 more
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Stationary foreground detection for video-surveillance based on foreground and motion history images

2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance, 2013
Stationary foreground detection is a common stage in many video-surveillance applications. In this paper, we propose an approach for stationary foreground detection in video based on the spatio-temporal variation of foreground and motion data. Foreground data are obtained by Background Subtraction to detect regions of interest.
Diego Ortego, Juan C. SanMiguel
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The improvement of VIBE foreground detection algorithm

MIPPR 2017: Automatic Target Recognition and Navigation, 2018
VIBE algorithm is one of the effective methods that based on dynamic model, which can deal with the detection of moving objects in the slowly changing background. The traditional VIBE uses a fixed threshold to realize target cutting ,that would result in a poor detection when the target enters a background area whose pixel value is not much different ...
Xiaomao Liu, Jinwen Tian, Jun Zhang, ahong xu, Daimeng Zhang   +4 more
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Pruning phantom detections from multiview foreground intersection

2012 19th IEEE International Conference on Image Processing, 2012
Homography mapping and fusion of foreground regions from multiple camera views is an effective technique for moving object detection. However, the intersections of non-corresponding foreground regions frequently cause phantom detections. In this paper, an algorithm using colour template matching is proposed to identify such phantoms from the multiview ...
Jie Ren, Ming Xu, Jeremy S Smith
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Features for stochastic approximation based foreground detection

Computer Vision and Image Understanding, 2015
Abstract Foreground detection algorithms have sometimes relied on rather ad hoc procedures, even when probabilistic mixture models are defined. Moreover, the fact that the input features have different variances and that they are not independent from each other is often neglected, which hampers performance.
Francisco Javier López-Rubio, Ezequiel López-Rubio   +1 more
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