Moving object detecting using gradient information, three-frame-differencing and connectivity testing

Authors:
Shuguang Zhao;Jun Zhao;Yuan Wang;Xinlin Fu
Affiliations:
College of Information Sciences and Technology, Donghua University, Shanghai, P.R. China;School of Electronic Engineering, Xidian University, Xi'an, P.R. China;School of Electronic Engineering, Xidian University, Xi'an, P.R. China;School of Electronic Engineering, Xidian University, Xi'an, P.R. China
Venue:
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
Year:
2006

Citing 5
Cited 0

Performance of optical flow techniques

International Journal of Computer Vision
Contour extraction of moving objects in complex outdoor scenes

International Journal of Computer Vision
Automatic moving object and background separation

Signal Processing - Video segmentation for content-based processing manipulation
W4: Real-Time Surveillance of People and Their Activities

IEEE Transactions on Pattern Analysis and Machine Intelligence
Moving Target Classification and Tracking from Real-time Video

WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)

Quantified Score

Hi-index	0.00

Visualization

Abstract

The motivation and the current status of moving object detecting research were reviewed firstly, and a novel method was proposed and verified in this paper. The method works mainly by using gradient information, three-frame-differencing and connectivity-testing-based noise reduction. The results of theoretical analyses and computer simulation show that the method has some advantages over its competitors, e.g., a wider application range, a less computation complexity and a faster processing speed. Thus, it is able to work rather robust in a noisy environment.