In this paper, we present a real-time pedestrian detection system in outdoor environments. It is necessary for pedestrian detection to implement obstacle and face detection which are major parts of a walking guidance system. It can discriminate pedestrian from obstacles, and extract candidate regions for face detection and recognition. For pedestrian detection, we have used stereo-based segmentation and SVM (Support Vector Machines), which has superior classification performance in binary classification case (e. g. object detection). We have used vertical edges, which can extracted from arms, legs, and the body of pedestrians, as features for training and detection. The experiments on a large number of street scenes demonstrate the effectiveness of the proposed for pedestrian detection system.
|Title of host publication||Pattern Recognition with Support Vector Machines - First International Workshop, SVM 2002 Niagara Falls, Canada, August 10, 2002 Proceedings|
|Editors||Seong-Whan Lee, Alessandro Verri|
|Number of pages||10|
|Publication status||Published - 2002|
|Event||1st International Workshop on Pattern Recognition with Support Vector Machines, SVM 2002 - Niagara Falls, Canada|
Duration: 2002 Aug 10 → 2002 Aug 10
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Other||1st International Workshop on Pattern Recognition with Support Vector Machines, SVM 2002|
|Period||02/8/10 → 02/8/10|
Bibliographical notePublisher Copyright:
© Springer-Verlag Berlin Heidelberg 2002.
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)