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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Video Analytics for Business Intelligence
verfasst von : Asaad Hakeem, Himaanshu Gupta, Atul Kanaujia, Tae Eun Choe, Kiran Gunda, Andrew Scanlon, Li Yu, Zhong Zhang, Peter Venetianer, Zeeshan Rasheed, Niels Haering
Erschienen in: Video Analytics for Business Intelligence
Verlag: Springer Berlin Heidelberg
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This chapter focuses on various algorithms and techniques in video analytics that can be applied to the business intelligence domain. The goal is to provide the reader with an overview of the state of the art approaches in the field of video analytics, and also describe the various applications where these technologies can be applied. We describe existing algorithms for extraction and processing of target and scene information, multi-sensor cross camera analysis, inferencing of simple, complex and abnormal video events, data mining, image search and retrieval, intuitive UIs for efficient customer experience, and text summarization of visual data. We have also presented the evaluation results of each of these technology components using in-house and other publicly available datasets.