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This paper presents a method which able to integrate audio and visual information for human action scene analysis. The approach is top-down for determining and extracting action scenes in video by analyzing both audio and video data. We proposed a framework for recognizing actions by measuring image and action-based information from video with the following characteristics: feature extraction is done...
In this paper we have designed a neural network based movie genres classifier. The Movie classifier characterizes the movie clips into different movie genres. The characterization is based on low level audio-visual features. We have extracted the computable audio-visual features from the movie clips which are inspired by the techniques and film grammars used by many filmmakers to endow specific characteristics...
This paper presents a method which able to integrate audio and visual information for action scene analysis in any movie. The approach is top-down for determining and extract action scenes in video by analyzing both audio and video data. In this paper, we directly modelled the hierarchy and shared structures of human behaviours, and we present a framework of the hidden Markov model based application...
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