Scene flow estimation by growing correspondence seeds

A simple seed growing algorithm for estimating scene flow in a stereo setup is presented. Two calibrated and synchronized cameras observe a scene and output a sequence of image pairs. The algorithm simultaneously computes a disparity map between the image pairs and optical flow maps between consecut...

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Bibliographic Details
Main Authors: Cech, J., Sanchez-Riera, J., Horaud, R.
Format: Conference Proceeding
Language:English
Subjects:
Adaptive optics
Cameras
Correlation
Image color analysis
Noise
Optical imaging
Three dimensional displays
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Description
Summary:A simple seed growing algorithm for estimating scene flow in a stereo setup is presented. Two calibrated and synchronized cameras observe a scene and output a sequence of image pairs. The algorithm simultaneously computes a disparity map between the image pairs and optical flow maps between consecutive images. This, together with calibration data, is an equivalent representation of the 3D scene flow, i.e. a 3D velocity vector is associated with each reconstructed point. The proposed method starts from correspondence seeds and propagates these correspondences to their neighborhood. It is accurate for complex scenes with large motions and produces temporally-coherent stereo disparity and optical flow results. The algorithm is fast due to inherent search space reduction. An explicit comparison with recent methods of spatiotemporal stereo and variational optical and scene flow is provided.
ISSN:1063-6919
DOI:10.1109/CVPR.2011.5995442