Abstract
This paper presents and investigates an improved local descriptor for spatio-temporal features on action recognition. Follow the idea of local spatio-temporal interest points on human action recognition, we develop a memory-efficient algorithm based on integral videos. The contribution of our job is we use the SURF descriptors on cuboids to speed up the computation especially for the integral video and improve the recognition rate. We present recognition results on a variety of dataset such as YouTobe and KTH, compared to previous work, the results showed that our algorithm is more efficient and accurate compared with the previous work.
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Yang, K., Du, JX., Zhai, CM. (2011). Action Recognition via an Improved Local Descriptor for Spatio-temporal Features. In: Huang, DS., Gan, Y., Bevilacqua, V., Figueroa, J.C. (eds) Advanced Intelligent Computing. ICIC 2011. Lecture Notes in Computer Science, vol 6838. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24728-6_31
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DOI: https://doi.org/10.1007/978-3-642-24728-6_31
Publisher Name: Springer, Berlin, Heidelberg
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