Real-Time Human Action Recognition Based on Depth Motion Maps

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Note: the depth sequences of each action from MSR-Action3D dataset are stored as a matrix of size 240 x 320 x number_of_frames in MATLAB.

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Authors C. Chen, K. Liu, and N. Kehtarnavaz
Journal/Conference Name Journal of Real-Time Image Processing
Paper Category
Paper Abstract This paper presents a human action recognition method by using depth motion maps. Each depth frame in a depth video sequence is projected onto three orthogonal Cartesian planes. Under each projection view, the absolute difference between two consecutive projected maps is accumulated through an entire depth video sequence forming a depth motion map. An l2-regularized collaborative representation classifier with a distance-weighted Tikhonov matrix is then employed for action recognition. The developed method is shown to be computationally efficient allowing it to run in real-time. The recognition results applied to the Microsoft Research Action3D dataset indicate superior performance of our method over the existing methods.
Date of publication 2013
Code Programming Language MATLAB

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