Real-time pedestrian detection using support vector machines
- Authors
- Kang, SH; Byun, H; Lee, SW
- Issue Date
- 5월-2003
- Publisher
- WORLD SCIENTIFIC PUBL CO PTE LTD
- Keywords
- pedestrian detection; support vector machines; stereo vision
- Citation
- INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, v.17, no.3, pp.405 - 416
- Indexed
- SCIE
SCOPUS
- Journal Title
- INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE
- Volume
- 17
- Number
- 3
- Start Page
- 405
- End Page
- 416
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/124358
- DOI
- 10.1142/S0218001403002435
- ISSN
- 0218-0014
- Abstract
- In this paper, we present a real-time pedestrian detection method in outdoor environments. It is necessary for pedestrian detection to implement obstacle and face detection which are major parts of a walking guidance system for the visually impaired. It detects foreground objects on the ground, discriminates pedestrians from other noninterest objects, and extracts candidate regions for face detection and recognition. For effective real-time pedestrian detection, we have developed a method using stereo-based segmentation and the SVM (Support Vector Machines), which works well particularly in binary classification problem (e.g. object detection). We used vertical edge features extracted from arms, legs and torso. In our experiments, test results on a large number of outdoor scenes demonstrated the effectiveness of the proposed pedestrian detection method.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - Graduate School > Department of Artificial Intelligence > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.