RGB-D action recognition using linear coding

In this paper, we investigate action recognition using an inexpensive RGB-D sensor (Microsoft Kinect). First, a depth spatial-temporal descriptor is developed to extract the interested local regions in depth image. Such descriptors are very robust to the illumination and background clutter. Then the intensity spatial-temporal descriptor and the depth spatial-temporal descriptor are combined and feeded into a linear coding framework to get an effective feature vector, which can be used for action classification. Finally, extensive experiments are conducted on a publicly available RGB-D action recognition dataset and the proposed method shows promising results.