A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pedestrian Detection Using Wavelet Templates
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Model Based Extraction of Articulated Objects in Image Sequences for Gait Analysis
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 3 - Volume 3
Detecting Pedestrians Using Patterns of Motion and Appearance
International Journal of Computer Vision
Stochastic Pedestrian Tracking Based on 6-Stick Skeleton Model
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
A Quantitative Evaluation of Video-based 3D Person Tracking
ICCCN '05 Proceedings of the 14th International Conference on Computer Communications and Networks
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
Stereo- and neural network-based pedestrian detection
IEEE Transactions on Intelligent Transportation Systems
Walking pedestrian recognition
IEEE Transactions on Intelligent Transportation Systems
Development of night-vision system
IEEE Transactions on Intelligent Transportation Systems
Pedestrian detection and tracking with night vision
IEEE Transactions on Intelligent Transportation Systems
A survey on visual surveillance of object motion and behaviors
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Fast occluded object tracking by a robust appearance filter
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Nowadays, pedestrian recognition based on image processing is widely tackled. Generally, pedestrian recognition is constructed by combining detection and tracking of pedestrians. However, accuracy of pedestrian recognition degrades since non-pedestrian objects are tracked once they are falsely detected as pedestrians. To overcome this problem, a novel pedestrian recognition by combining detection based on boosting and skeleton-based stochastic tracking with false positive detection is proposed. In the proposed scheme, false positives are detected based on the variance of predicted skeleton in a tracking phase. The experimental results by applying the proposed scheme to a sequence provided by PETS show that false positives can be detected by the proposed scheme based on the variance.