An Efficient Foreground Object Detection Method Using a Color Cluster-Based Background Modeling Algorithm

2016 ◽  
Author(s):  
Wen-Kai Tsai ◽  
Ming-Hwa Sheu
Keyword(s):  
Object Detection ◽  
Detection Method ◽  
Background Modeling ◽  
Foreground Object ◽  
Modeling Algorithm

Object detection based on randomized background modeling algorithm

2015 ◽  
Vol 36 (6) ◽  
pp. 880-887 ◽  
Author(s):  
Yang Heng ◽  
Wang Chao ◽  
Jiang Wen-tao ◽  
Liu Pei-zhen ◽  
Sun Xiao-wei ◽  
...  
Keyword(s):  
Object Detection ◽  
Background Modeling ◽  
Modeling Algorithm

Moving Object Detection for Video Based on Image Blocking and Improved Particle Filter

2013 ◽  
Vol 333-335 ◽  
pp. 1043-1046
Author(s):  
Li Xin Liu ◽  
Xiao Xue Zhang ◽  
Li Li Meng ◽  
Ming Zhang
Keyword(s):  
Object Detection ◽  
Particle Filter ◽  
Detection Method ◽  
Temporal Correlation ◽  
Moving Object Detection ◽  
Moving Object ◽  
Foreground Object ◽  
Qualitative And Quantitative Analysis ◽  
Qualitative And Quantitative ◽  
Low Dimensional

In this paper, a moving object detection method based on image blocking and improved Particle Filter is proposed. Firstly, each frame in a video is partitioned into blocks and a low-dimensional descriptor is extracted for each block; Secondly, each block is sequentially passed through two classifiers, improved Particle Filter and temporal correlation check. Finally, foreground object is detected by integrating the classification results of all blocks. We use two-stage classifier to effectively minimize the number of false positive in the detected foreground object. Experiments show that the method proposed in this paper is feasible both in qualitative and quantitative analysis so it can be used in moving object detection effectively.

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