Yair Hanani

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Action Recognition in videos is an active research field that is fueled by an acute need, spanning several application domains. Still, existing systems fall short of the appli-cations' needs in real-world scenarios, where the quality of the video is less than optimal and the viewpoint is uncontrolled and often not static. In this paper, we extend the Motion(More)
In video understanding, the spatial patterns formed by local space-time interest points hold discriminative information. We encode these spatial regularities using a word2vec neural network, a recently proposed tool in the field of text processing. Then, building upon recent accu-mulator based image representation solutions, input videos are represented in(More)
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