Abstract
We present here an approach for video image segmentation where spatial segmentation is based on rough sets and granular computing and temporal segmentation is done by consecutive frame subtraction. Then the intersection of the temporal segmentation and spatial segmentation for the same frame is analyzed in RGB feature space. The estimated statistics of the intersecting regions is used for the object reconstruction and tracking.
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Uma Shankar, B., Chakraborty, D. (2011). Spatiotemporal Approach for Tracking Using Rough Entropy and Frame Subtraction. In: Kuznetsov, S.O., Mandal, D.P., Kundu, M.K., Pal, S.K. (eds) Pattern Recognition and Machine Intelligence. PReMI 2011. Lecture Notes in Computer Science, vol 6744. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21786-9_33
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DOI: https://doi.org/10.1007/978-3-642-21786-9_33
Publisher Name: Springer, Berlin, Heidelberg
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