Paper Info
Title
Moving object detection and tracking from video captured by moving camera
Abstract
Proposed method has good performance for a moving camera without additional sensors.Proposed method works well for tracking overlapping objects with scale changes.Proposed method outperforms the-state-of-art methods. 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.
Year
DOI
Venue
2015
10.1016/j.jvcir.2015.03.003
Journal of Visual Communication and Image Representation
Keywords
Field
DocType
object tracking
Computer vision,Object detection,Pattern recognition,Effective method,Camera auto-calibration,Kalman filter,Video tracking,Artificial intelligence,Match moving,Mathematics,Minimum bounding box,Center of gravity
Journal
Volume
Issue
ISSN
30
C
1047-3203
Citations 
PageRank 
References 
22
0.71
18
Authors
5
Name
Order
Citations
PageRank
Wu-Chih Hu124427.01
C. -H. Chen2382.14
Tsong-Yi Chen38415.49
Deng-Yuan Huang4382.35
Zong-Che Wu5220.71