Local feature coding for action recognition using RGB-D camera

Authors:
Mingyi Yuan;Huaping Liu;Fuchun Sun
Affiliations:
Department of Computer Science and Technology, Tsinghua University, P.R. China,State Key Laboratory of Intelligent Technology and Systems, Beijing, P.R. China;Department of Computer Science and Technology, Tsinghua University, P.R. China,State Key Laboratory of Intelligent Technology and Systems, Beijing, P.R. China;Department of Computer Science and Technology, Tsinghua University, P.R. China,State Key Laboratory of Intelligent Technology and Systems, Beijing, P.R. China
Venue:
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part I
Year:
2013

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Abstract

In this paper, we perform activity recognition using an inexpensive RGBD sensor (Microsoft Kinect). The main contribution of this paper is that the conventional STIPs feature are extracted from not only the RGB image, but also the depth image. To the best knowledge of the authors, there is no work on extracting STIPs feature from the depth image. In addition, the extracted feature are combined under the framework of locality-constrained linear coding framework and the resulting algorithm achieves better results than state-of-the-art on public dataset.