Results 271 to 280 of about 21,066 (308)

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
openaire   +1 more source

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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Hybrid Resolution Based Video Foreground Detection

Proceedings of the International Conference on Distributed Smart Cameras, 2014
Conventional video foreground segmentation methods model a scene at pixel or block granularity. The granularity is the same for the whole scene, and is selected based on computational budget and accuracy requirements, independent of video content. We propose a hybrid resolution segmentation system, which uses foreground activity distribution as a ...
Amit Kumar Gupta, Getian Ye, Jeroen Vendrig   +2 more
openaire   +1 more source

Lightweight and Robust Shadow Removal for Foreground Detection

2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance, 2012
Background subtraction is a commonly used method to detect moving objects from videos captured by static cameras. However, shadows and reflections significantly affect the output of background subtraction algorithms, and distort the shape of the objects obtained as a result.
Anuja Gawde, Kedar Joshi, Senem Velipasalar   +2 more
openaire   +1 more source

Foreground detection for moving cameras with stochastic approximation

Pattern Recognition Letters, 2015
A non-panoramic method to detect foreground objects for moving cameras is proposed.Probabilistic background models with full covariance matrices are employed.Camera movement tracking and foreground detection are done by two distinct pixel models.A procedure to interpolate the full covariance matrices of the pixel models is proposed.
Francisco Javier López-Rubio, Ezequiel López-Rubio   +1 more
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Foreground detection based on color and texture features

2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 2015
Moving objects detection from a video sequence is a fundamental and critical work in many computer-vision applications. A widely utilized strategy is to implement background subtraction method, aiming to classify moving objects from video sequences based on the background model.
openaire   +1 more source

Foreground detection using spatiotemporal projection kernels

2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012
In this paper, we propose a novel video foreground detection method that exploits the statistics of 3D spacetime patches. 3D space-time patches are characterized by means of the subspace they span. As the complexity of real-time systems prohibits performing this modeling directly on the raw pixel data, we propose a novel framework in which ...
Yair Moshe, Hagit Hel-Or, Yacov Hel-Or
openaire   +1 more source

Saliency Detection Based on Foreground and Background Propagation

2019
In recent years, image saliency detection has become a research hotspot in the field of computer vision. Although significant progress has been witnessed in visual saliency detection, several existing saliency detection methods still cannot highlight the complete salient object when under complex background.
Qing Xing, Suoping Zhang, Mingbing Li, Chaoqun Dang, Zhanhui Qi   +4 more
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Saliency Detection Based on Background and Foreground Modeling

2017
In this paper, a novel saliency detection algorithm is proposed to fuse both the background and foreground information while detecting salient objects in complex scenes. Firstly, we extract background seeds as well as their spatial information from image borders to construct a background-based saliency map.
Zhengbing Wang, Guili Xu, Yuehua Cheng, Zhengsheng Wang   +3 more
openaire   +1 more source

A novel framework for background subtraction and foreground detection

Pattern Recognition, 2018
Abstract In this paper, we propose a novel image background subtraction framework based on KDE. Firstly a new data structure called Mino Vector (MV) is designed for each pixel; we define dynamic nature (DN) for pixels of a scene and rank them in terms of DN for getting quantized results named dynamic rank (DR).
Guian Zhang, Zhiyong Yuan, Qianqian Tong 0001, Mianlun Zheng, Jianhui Zhao 0001   +4 more
openaire   +1 more source