Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation with Applications to Tracking and Navigation
Estimation with Applications to Tracking and Navigation
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Implicit Probabilistic Models of Human Motion for Synthesis and Tracking
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Behavioral Priors for Detection and Tracking of Pedestrians in Video Sequences
International Journal of Computer Vision
Stereo Processing by Semiglobal Matching and Mutual Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
Monocular Pedestrian Detection: Survey and Experiments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Recognition of Human Activities: A Survey
IEEE Transactions on Circuits and Systems for Video Technology
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Future vehicle systems for active pedestrian safety will not only require a high recognition performance, but also an accurate analysis of the developing traffic situation. In this paper, we present a system for pedestrian action classification (walking vs. stopping) and path prediction at short, sub-second time intervals. Apart from the use of positional cues, obtained by a pedestrian detector, we extract motion features from dense optical flow. These augmented features are used in a probabilistic trajectory matching and filtering framework. The vehicle-based system was tested in various traffic scenes. We compare its performance to that of a state-of-the-art IMM Kalman filter (IMM-KF), and for the action classification task, to that of human observers, as well. Results show that human performance is best, followed by that of the proposed system, which outperforms the IMM-KF and the simpler system variants.