Detecting Hidden Objects Using Efficient Spatio-Temporal Knowledge Representation

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• 关键词：Surveillance application ; Visual scene analysis ; Automated scene understanding ; Knowledge representation ; Spatio ; temporal visual ontology ; Symbolic reasoning ; Computer vision ; Pattern recognition
• 刊名：Lecture Notes in Computer Science
• 出版年：2017
• 出版时间：2017
• 年：2017
• 卷：10162
• 期：1
• 页码：302-313
• 丛书名：Agents and Artificial Intelligence
• ISBN：978-3-319-53354-4
• 卷排序：10162

文摘

Detecting visible as well as invisible objects of interest in real-world scenes is crucial in new-generation video-surveillance. For this purpose, we design a fully intelligent system incorporating semantic, symbolic, and grounded information. In particular, we conceptualize temporal representations we use together with spatial and visual information in our multi-view tracking system. It uses them for automated reasoning and induction of knowledge about the multiple views of the studied scene, in order to automatically detect salient or hidden objects of interest. Tests on standard datasets demonstrated the efficiency and accuracy of our proposed approach.