Human Action Recognition Based On Multiview
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Abstract
This paper presents the different approaches and datasets for recognition of human actions under view changes. Visual analysis of human action is currently one of the most active research topics. This strong interest is driven by a wide spectrum of promising applications in many areas such as virtual reality, smart surveillance, perceptual interface, etc. Human action analysis concerns the detection, tracking and recognition of people, and more generally, the understanding of human behaviors, from image sequences involving humans. We consider the task of labeling videos containing human motion with action classes. The interest in the topic is motivated by the promise of many applications, both offline and online. In this paper, we specifically addressed multi-view front and top independent video analysis, with human action recognition for training and detection of different actions.
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Keywords: human action recognition; datasets; detection; tracking; human behaviors;
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