Abstract
To enable the precise detection of persons walking or running on the ground using unmanned Micro Aerial Vehicles (MAVs), we present the evaluation of the MCT algorithm based on intensity as well as gradient images for optical flow, focusing on accuracy as well as low computational complexity to enable the real-time implementation in light-weight embedded systems. Therefore, we give a detailed analysis of this algorithm on four optical flow datasets from the Middlebury database and show the algorithm’s performance when compared to other optical flow algorithms. Furthermore, different approaches for sub-pixel refinement and occlusion detection are discussed.
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Puxbaum, P., Ambrosch, K. (2010). Gradient-Based Modified Census Transform for Optical Flow. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2010. Lecture Notes in Computer Science, vol 6453. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17289-2_42
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DOI: https://doi.org/10.1007/978-3-642-17289-2_42
Publisher Name: Springer, Berlin, Heidelberg
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