Springer, 2011. —261 p. In recent years, steady progress has been made towards better models for video event categorisation and recognition, e.g., from modelling events with bag of spatial temporal features to discovering event context, from detecting events using a single camera to inferring events through a distributed camera network, and from low-level event feature extraction and description to high-level semantic event classification and recognition. Nowadays, text based video retrieval is widely used by commercial search engines. However, it is still very difficult to retrieve or categorise a specific video segment based on their content in a real multimedia system or in surveillance applications. To advance the progress further, we must adapt recent or existing approaches to find new solutions for intelligent video understanding. This book aims to present state-of-the-art research advances of video event understanding technologies. It will provide researchers and practitioners a rich resource for future research directions and successful practice. It could also serve as a reference tool and handbook for researchers in a number of applications including visual surveillance, human-computer interaction, and video search and indexing etc. Its potential audience will be composed of active researchers and practitioners as well as graduate students working on video analysis in various disciplines such as computer vision, pattern recognition, information security, artificial intelligence, etc.
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