Paper Info
Title
A 3D Feature-Based Binocular Tracking Algorithm*Our work is supported by the National Natural Science Founds of China (No. 60271033) and SVS 04 of OMRON Corporation, Japan.
Abstract
This paper presents a 3D feature-based binocular tracking algorithm for tracking crowded people indoors. The algorithm consists of a two stage 3D feature points grouping method and a robust 3D feature-based tracking method. The two stage 3D feature points grouping method can use kernel-based ISODATA method to detect people accurately even though the part or almost full occlusion occurs among people in surveillance area. The robust 3D feature-based Tracking method combines interacting multiple model (IMM) method with a cascade multiple feature data association method. The robust 3D feature-based tracking method not only manages the generation and disappearance of a trajectory, but also can deal with the interaction of people and track people maneuvering. Experimental results demonstrate the robustness and efficiency of the proposed framework. It is real-time and not sensitive to the variable frame to frame interval time. It also can deal with the occlusion of people and do well in those cases that people rotate and wriggle.
Year
DOI
Venue
2006
10.1093/ietisy/e89-d.7.2142
IEICE - Transactions on Information and Systems
Keywords
DocType
Volume
association method,national natural science founds,feature-based binocular tracking algorithm,full occlusion,track people maneuvering,feature point,omron corporation,crowded people,multiple model,isodata method,feature-based tracking method,cascade multiple feature data
Journal
E89-D
Issue
ISSN
Citations 
7
1745-1361
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Guang Tian121.42
Feihu Qi234727.19
Masatoshi Kimachi372.59
Y. Wu41178139.36
Takashi Iketani521.08