Paper Info
Title
Pedestrian Detection Using Derived Third-Order Symmetry Of Legs A Novel Method Of Motion-Based Information Extraction From Video Image-Sequences
Abstract
The paper focuses on motion-based information extraction from video image sequences. A novel method is introduced which can reliably detect walking human figures contained in such images. The method works with spatio-temporal input information to detect and classify the patterns typical of human movement. Our algorithm consists of easy-to-optimise operations, which in practical applications is an important factor. The paper presents a new information-extraction and temporal-tracking method based on a simplified version of the symmetry which is characteristic for the legs of a walking person. These spatio-temporal traces are labelled by kernel Fisher discriminant analysis. With this use of temporal tracking and non-linear classification we have achieved pedestrian detection from real-life images with a correct classification rate of 96.5%.
Year
DOI
Venue
2004
10.1007/1-4020-4179-9_106
COMPUTER VISION AND GRAPHICS (ICCVG 2004)
Keywords
DocType
Volume
simplified symmetry, pedestrian detection, tracking, surveillance, kernel Fisher discriminant analysis
Conference
32
Citations 
PageRank 
References 
0
0.34
5
Authors
3
Name
Order
Citations
PageRank
László Havasi1165.34
Zoltán Szlávik211621.40
Tamás Szirányi315226.92