Recognising action as clouds of space-time interest points

• Published in: 2009 IEEE Conference on Computer Vision and Pattern Recognition pp. 1948 - 1955
• Main Authors: Bregonzio, Matteo, Shaogang Gong, Tao Xiang
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2009
• Subjects: Cameras; Clouds; Clustering algorithms; Computational efficiency; Computer science; Data mining; Noise shaping; Power engineering and energy; Robustness; Shape

Much of recent action recognition research is based on space-time interest points extracted from video using a Bag of Words (BOW) representation. It mainly relies on the discriminative power of individual local space-time descriptors, whilst ignoring potentially valuable information about the global...