A Novel Semantic Video Classification Model

Wei Ren, M. Singh, S. Singh
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Abstract

In this paper, we propose a novel spatio-temporal video retrieval model to extract spatio-temporal attributes for semantic video category classification using high-level reasoning of video objects and scenes. We also explore the semantic logical inference learning of video attributes based on interpreting camera movements and object spatial constraints, as well the views on temporal continuity of video. We have used Minerva international video benchmark for the analysis of our algorithm.
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一种新的语义视频分类模型
在本文中,我们提出了一种新的时空视频检索模型,利用视频对象和场景的高级推理来提取语义视频类别分类的时空属性。我们还探讨了基于摄像机运动和物体空间约束的视频属性的语义逻辑推理学习,以及对视频时间连续性的看法。我们使用Minerva国际视频基准来分析我们的算法。
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