Moving object detection and tracking from video captured by moving camera

被引:62
|
作者
Hu, Wu-Chih [1 ]
Chen, Chao-Ho [2 ]
Chen, Tsong-Yi [2 ]
Huang, Deng-Yuan [3 ]
Wu, Zong-Che [4 ]
机构
[1] Natl Penghu Univ Sci & Technol, Dept Comp Sci & Informat Engn, Penghu, Taiwan
[2] Natl Kaohsiung Univ Appl Sci, Dept Elect Engn, Kaohsiung 807, Taiwan
[3] Dayeh Univ, Dept Elect Engn, Dacun, Taiwan
[4] Whetron Elect Co Ltd, Taipei, Taiwan
关键词
Object detection; Moving camera; Object tracking; Feature classification; Image difference; Object motion; Motion history; Ego-motion compensation; MOTION ESTIMATION; RANDOM-FIELD; SEGMENTATION;
D O I
10.1016/j.jvcir.2015.03.003
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents an effective method for the detection and tracking of multiple moving objects from a video sequence captured by a moving camera without additional sensors. Moving object detection is relatively difficult for video captured by a moving camera, since camera motion and object motion are mixed. In the proposed method, the feature points in the frames are found and then classified as belonging to foreground or background features. Next, moving object regions are obtained using an integration scheme based on foreground feature points and foreground regions, which are obtained using an image difference scheme. Then, a compensation scheme based on the motion history of the continuous motion contours obtained from three consecutive frames is applied to increase the regions of moving objects. Moving objects are detected using a refinement scheme and a minimum bounding box. Finally, moving object tracking is achieved using a Kalman filter based on the center of gravity of a moving object region in the minimum bounding box. Experimental results show that the proposed method has good performance. (C) 2015 Elsevier Inc. All rights reserved.
引用
收藏
页码:164 / 180
页数:17
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