Integrated Person Tracking Using Stereo, Color, and Pattern Detection
International Journal of Computer Vision - Special issue on a special section on visual surveillance
A Cooperative Algorithm for Stereo Matching and Occlusion Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
W4S: A real-time system detecting and tracking people in 2 1/2D
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Pedestrian Detection in Crowded Scenes
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
A Dense Stereo Matching Using Two-Pass Dynamic Programming with Generalized Ground Control Points
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Pedestrian detection using stereo and biometric information
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part II
Stereo- and neural network-based pedestrian detection
IEEE Transactions on Intelligent Transportation Systems
Robust pedestrian detection and tracking in crowded scenes
Image and Vision Computing
Mixtures of Classifiers for Recognizing Standing and Running Pedestrians
ICCVG 2008 Proceedings of the International Conference on Computer Vision and Graphics: Revised Papers
Multi-cue-based crowd segmentation in stereo vision
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
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A method for pedestrian detection from challenging real world outdoor scenes is presented in this paper. This technique is able to extract multiple pedestrians, of varying orientations and appearances, from a scene even when faced with large and multiple occlusions. The technique is also robust to changing background lighting conditions and effects, such as shadows. The technique applies an enhanced method from which reliable disparity information can be obtained even from untextured homogeneous areas within a scene. This is used in conjunction with ground plane estimation and biometric information,to obtain reliable pedestrian regions. These regions are robust to erroneous areas of disparity data and also to severe pedestrian occlusion, which often occurs in unconstrained scenarios.