Application of cooperative co-evolution in pedestrian detection systems

Authors:
Xianbin Cao;Hong Qiao;Fei-Yue Wang;Xinzheng Zhang
Affiliations:
Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China;Institute of Automation, Chinese Academy of Sciences, Beijing, China;Institute of Automation, Chinese Academy of Sciences, Beijing, China;Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China
Venue:
ISI'05 Proceedings of the 2005 IEEE international conference on Intelligence and Security Informatics
Year:
2005

Citing 2
Cited 0

Comparing Images Using the Hausdorff Distance

IEEE Transactions on Pattern Analysis and Machine Intelligence
Pedestrian Detection from a Moving Vehicle

ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II

Quantified Score

Hi-index	0.00

Visualization

Abstract

In general, a shape-based[1] pedestrian detection system includes the following two steps: (a) finding out and tracking a possible pedestrian figure, and (b) determining if the candidate pedestrian figure is really a pedestrian figure by checking if it matches with any of the pedestrian templates. Since there are a large number of templates, it is necessary to build up a search tree for the Match process [2,3]. Each node in the tree is one feature of the corresponding templates that can be used for classification and where each branch is one pedestrian template. Usually, the search tree is not adjustable during the matching process.