Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Example-Based Object Detection in Images by Components
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Pedestrian Detection Using Wavelet Templates
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Integrated Person Tracking Using Stereo, Color, and Pattern Detection
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
W4: Who? When? Where? What? A Real Time System for Detecting and Tracking People
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Hydra: Multiple People Detection and Tracking Using Silhouettes
VS '99 Proceedings of the Second IEEE Workshop on Visual Surveillance
Example Based Learning for View-Based Human Face Detection
Example Based Learning for View-Based Human Face Detection
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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.