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A platform for research: civil engineering, architecture and urbanism
Fusing optical flow and stereo disparity for object tracking
This paper proposes a novel approach to object detection and tracking using video sensors. Two different methods are employed to retrieve depth information from images: stereopsis and depth from motion. The obtained data streams are fused yielding increased reliability and accuracy. A set of image points is tracked over time using an extended Kalman filter. The proposed algorithm clusters points of similar dynamics by analysis of the filter residuals. Experimental results are provided for synthetic as well as for natural image sequences.
Fusing optical flow and stereo disparity for object tracking
This paper proposes a novel approach to object detection and tracking using video sensors. Two different methods are employed to retrieve depth information from images: stereopsis and depth from motion. The obtained data streams are fused yielding increased reliability and accuracy. A set of image points is tracked over time using an extended Kalman filter. The proposed algorithm clusters points of similar dynamics by analysis of the filter residuals. Experimental results are provided for synthetic as well as for natural image sequences.
Fusing optical flow and stereo disparity for object tracking
Dang, T. (author) / Hoffmann, C. (author) / Stiller, C. (author)
2002-01-01
477249 byte
Conference paper
Electronic Resource
English
FUSING OPTICAL FLOW AND STEREO DISPARITY FOR OBJECT TRACKING
| British Library Conference Proceedings | 2002
Obstacles Detection from Disparity Properties in a Particular Stereo Vision System Configuration
| British Library Conference Proceedings | 2003