Paper Info
Title
Multiple-Person Tracking System For Content Analysis
Abstract
This paper presents a framework to track multiple persons in real-time. First, a method with real-time and adaptable capability is proposed to extract face-like regions based on skin, motion and silhouette features. Then, an adaptable skin model is used for each detected face to overcome the changes of the observed environment. After that, a two-stage face verification algorithm is proposed to quickly eliminate false faces based on face geometries and the SVM (Support Vector Machine) approach. In order to overcome the effect of lighting changes, during verification, a method of color constancy compensation is proposed. Then, a robust tracking scheme is applied to identify multiple persons based on a face-status table. With the table, the proposed system has powerful capabilities to track different persons at different statuses, which is quite important in face-related applications. Experimental results show that the proposed method is more robust and powerful than other traditional methods, which utilize only color, motion information, and the correlation technique.
Year
DOI
Venue
2001
10.1142/S0218001402001800
INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE
Keywords
Field
DocType
face detection, face tracking, video surveillance, support vector machine, color constancy compensation
Color constancy,Facial recognition system,Computer vision,Content analysis,Pattern recognition,Silhouette,Support vector machine,Tracking system,Artificial intelligence,Face detection,Facial motion capture,Mathematics
Conference
Volume
Issue
ISSN
16
4
0218-0014
Citations 
PageRank 
References 
4
0.61
5
Authors
2
Name
Order
Citations
PageRank
Jun-Wei Hsieh175167.88
Yea-shuan Huang247979.42