We examine high accuracy stereo estimation for binocular sequences that where obtained from a mobile platform. The ultimate goal is to improve the range of stereo systems without altering the setup. Based on a well-known variational optical flow model, we introduce a novel stereo model that features a second-order regularization, which both allows sub-pixel accurate solutions and piecewise planar disparity maps. The model incorporates a robust fidelity term to account for adverse illumination conditions that frequently arise in real-world scenes. Using several sequences that were taken from a mobile platform we show the robustness and accuracy of the proposed model.
Pushing the limits of stereo using variational stereo estimation
2012 IEEE Intelligent Vehicles Symposium ; 401-407
2012-06-01
2015663 byte
Conference paper
Electronic Resource
English
Pushing the Limits of Stereo Using Variational Stereo Estimation
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