Videos taken by hand-held camera easily contain both motion and jitter, which can result in a large number of false detections of moving object detection and achieve poor performance. In this paper, we propose a moving object detection algorithm adapted to videos from hand-held camera. The proposed algorithm uses the optical flow method to perform motion estimation and motion compensation on the videos. So the interferences caused by hand-held camera can be reduced. Then we establish background model to detect the moving object. The proposed algorithm is verified with videos from hand-held camera and compared with several state-of-the-art algorithms. Experimental results demonstrate that the proposed algorithm is effective for moving object detection in videos from hand-held camera.

Date Published: 9 August 2018
PDF: 6 pages
Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 1080611 (9 August 2018);

Published in SPIE Proceedings Vol. 10806:
Tenth International Conference on Digital Image Processing (ICDIP 2018)
Xudong Jiang; Jenq-Neng Hwang, Editor(s)