Multi-view action recognition using bag-of-words and various fusion schemes
نویسندگان
چکیده
In this paper, we summarize how the action recognition can be improved when multiple views are available. The novelty is that we explore various combination schemes within the robust and simple bag-of-words (BoW) framework, from early fusion of features to late fusion of multiple classifiers. In new experiments on the publicly available IXMAS dataset, we learn that action recognition can be improved significantly already by only adding one viewpoint. We demonstrate that the state-of-the-art on this dataset can be improved by 5% – achieving 96.4% accuracy – when multiple views are combined.
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