Phase-based optical flow algorithms are characterized by high precision and robustness, but also by high computational requirements. Using the CUDA platform, we have implemented a phase-based algorithm that maps exceptionally well on the GPUpsilas architecture. This optical flow algorithm revolves around a reliability measure that evaluates the consistency of phase information over time. By exploiting efficient filtering operations, the high internal bandwidth of the GPU, and the texture units, we obtain dense and reliable optical flow estimates in realtime at high resolutions (640 times 512 pixels and beyond). Even though the algorithm is local and does not involve iterative regularization, highly accurate results are obtained on synthetic and complex real-world sequences.
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Pauwels et al. (2008) studied this question.
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