Abstract
We present an approach for motion estimation from videos captured by depth-sensing cameras. Our method uses the technique of graph matching to find groups of pixels that move to the same direction in subsequent frames. In order to choose the best matching for each patch, we minimize a cost function that accounts for distances on RGB and XYZ spaces. Our application runs at real-time rates for low resolution images and has shown to be a convenient framework to deal with input data generated by the new depth-sensing devices. The results show clearly the advantage obtained in the use of RGB-D images over RGB images.
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da Silva Pires, D., Cesar-Jr, R.M., Velho, L. (2013). Motion Estimation from RGB-D Images Using Graph Homomorphism. In: Ruiz-Shulcloper, J., Sanniti di Baja, G. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2013. Lecture Notes in Computer Science, vol 8259. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41827-3_61
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DOI: https://doi.org/10.1007/978-3-642-41827-3_61
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