Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/43217
Title: Object-Oriented Scale-Adaptive Filtering for human detection from stereo images
Authors: Li, L.
Ge, S.S. 
Sim, T. 
Koh, Y.
Hunag, X.
Issue Date: 2004
Source: Li, L.,Ge, S.S.,Sim, T.,Koh, Y.,Hunag, X. (2004). Object-Oriented Scale-Adaptive Filtering for human detection from stereo images. 2004 IEEE Conference on Cybernetics and Intelligent Systems : 135-140. ScholarBank@NUS Repository.
Abstract: In this paper, an effective and efficient methodology to extract visual evidence of suitable scale for object detection, Object-Orient Scale-Adaptive Filtering (OOSAF), is proposed. With OOSAF, object extraction from stereo images is formulated as the design of scale-adaptive filters. Based on OOSAF, two methods for human detection from stereo images are developed. One is to detect human objects with close distances to the camera for intelligent human-machine interaction, and the other is to detect human heads in distant crowds for security surveillance. Experiments show that, with OOSAF, efficient solutions for human detection from stereo images could be achieved with high detection rates and low false alarm rates.
Source Title: 2004 IEEE Conference on Cybernetics and Intelligent Systems
URI: http://scholarbank.nus.edu.sg/handle/10635/43217
ISBN: 0780386442
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

64
checked on Dec 16, 2017

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.