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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...
This work discusses the application of an Artificial Intelligence technique called data extraction and a process-based ontology in constructing experimental qualitative models for video retrieval and detection. We present a framework architecture that uses multimodality features as the knowledge representation scheme to model the behaviors of a number of human actions in the video scenes. The main...
Content-based video retrieval system is fairly recent and it is currently necessary to examine where it would just replace existing systems, where it can really bring some improvement and where it will open new possibilities. The users want to query the content instead of the raw video data. In this paper, we surveyed the art of video retrieval and proposed a basic framework for video retrieval based...
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