Action recognition on motion capture data using a dynemes and forward differences representation

作者：Kapsouras Ioannis^*; Nikolaidis Nikos

来源：Journal of Visual Communication and Image Representation, 2014, 25(6): 1432-1445.

DOI：10.1016/j.jvcir.2014.04.007

• Action recognition
• Action representation
• Angular K-means
• Skeleton animation
• Motion capture data
• Dynemes
• Forward differences
• Bag of words

In this paper we introduce a novel method for action/movement recognition in motion capture data. The joints orientation angles and the forward differences of these angles in different temporal scales are used to represent a motion capture sequence. Initially K-means is applied on training data to discover the most representative patterns on orientation angles and their forward differences. A novel K-means variant that takes into account the periodic nature of angular data is applied on the former. Each frame is then assigned to one or more of these patterns and histograms that describe the frequency of occurrence of these patterns for each movement are constructed. Nearest neighbour and SVM classification are used for action recognition on the test data. The effectiveness and robustness of this method is shown through extensive experimental results on four standard databases of motion capture data and various experimental setups.

• 出版日期2014-8