Advertisement
Published in:
2011 | OriginalPaper | Chapter
Improved Cue Fusion for Object Tracking Algorithm Based on Particle Filter
Authors : Hui Li, Li Zhang
Published in: Emerging Research in Artificial Intelligence and Computational Intelligence
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
The traditional object tracking with cue fusion is inaccurate under complex background. Especially when some blocks exist, the targets may be lost. To solve this problem, improved cue fusion for object tracking algorithm based on particle filter is proposed. It uses color and motion as the observation information source. Color is the main observation information and motion is the auxiliary information. It weights particles followed by the order of information. Block detection, particle filter and mean-shift are used together to track the interest targets. The experimental results show that in complex scene, when the number of particles of the proposed method is half of the traditional cue fusion, the proposed method can improve effectively the accuracy of target tracking, and track object stably when the shape is changing. So the proposed method is more robust and real-time.