Intelligent vehicle systems need to distinguish which objects are moving and which are static. A static concrete wall lying in the path of a vehicle should be treated differently than a truck moving in front of the vehicle. This paper proposes a new algorithm that addresses this problem, by providing dense dynamic depth information, while coping with real-time constraints. The algorithm models disparity and disparity rate pixel-wise for an entire image. This model is integrated over time and tracked by means of many pixel-wise Kalman filters. This provides better depth estimation results over time, and also provides speed information at each pixel without using optical flow. This simple approach leads to good experimental results for real stereo sequences, by showing an improvement over previous methods.
Integrating disparity images by incorporating disparity rate
Integration der Disparity-Images durch Einbeziehung der Disparitätsrate
2008
14 Seiten, 11 Quellen
Aufsatz (Konferenz)
Englisch
Motion Estimation from Disparity Images
British Library Conference Proceedings | 2001
|Motion estimation from disparity images
IEEE | 2001
|Enhanced disparity estimation in stereo images
British Library Online Contents | 2015
|Shape-indifferent stereo disparity based on disparity gradient estimation
British Library Online Contents | 2017
|Real-time joint disparity and disparity flow estimation on programmable graphics hardware
British Library Online Contents | 2009
|