Titlebook: Video Search and Mining; Dan Schonfeld,Caifeng Shan,Liang Wang Book 2010 Springer-Verlag Berlin Heidelberg 2010 Video Retrieval.calculus.c

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Three Dimensional Information Extraction and Applications to Video Analysis tasks. The use of 3D information in video analysis is scarce in the literature due to the inherent difficulties of such a system. When the only input to the system is a video stream with no previous knowledge of the scene or camera (a typical scenario in video analysis), computing an accurate 3D re

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Statistical Analysis on Manifolds and Its Applications to Video Analysiss and web-based user interfaces. A common requirement among these very different applications is the ability to learn statistical models of appearance and motion from a collection of videos, and then use them for recognizing actions or persons in a new video. These applications in video analysis req

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Semantic Video Content Analysisecting abnormalities. The practical applications of such a system could include airport tarmac monitoring, or monitoring of activities in secure installations, to name a few. The difficulty of the problem is compounded by several factors: detection of primitive actions in spite of changes in illumin

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Visual Concept Learning from Weakly Labeled Web Videosirplane”), locations (“desert”), or activities (“interview”). The task poses a difficult challenge as the amount of accurately labeled data available for supervised training is limited and coverage of concept classes is poor. In order to overcome these problems, we describe the use of videos found o

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Face Recognition and Retrieval in Videovironments remains challenging for most practical applications. In contrast to traditional still-image based approaches, recently the research focus has shifted towards videobased approaches. Video data provides rich and redundant information, which can be exploited to resolve the inherent ambiguiti

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