Fast Detection and Modeling of Human-Body Parts from Monocular Video
AMDO '08 Proceedings of the 5th international conference on Articulated Motion and Deformable Objects
3-D camera modeling and its applications in sports broadcast video analysis
MCAM'07 Proceedings of the 2007 international conference on Multimedia content analysis and mining
A distributed multi-agent architecture in simulation based medical training
Transactions on Edutainment III
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With the growing storage capacities of hard-disks and optical discs, large consumer video databases are gradually developing. The large effective storage capacity using compressed video leads to the application of fast storage and retrieval functions, to enable quick user-friendly searching for and access to specific parts of the video data. We explore the feasibility of a near real-time semantic sports video analyzer for an experimental consumer media server. This tool is able to automatically extract and analyze key events in a video sequence. The analyzer employs several visual cues and a model for real-world coordinates, so that key parameters (e.g. speed and position) of a player can be determined with sufficient accuracy. This special data can be stored as metadata, thereby facilitating intelligent searching of events. The tool consists of four processing steps: (1) playing frame detection, (2) court extraction, as well as a 3-D camera model, (3) player segmentation and tracking, and (4) event-based high-level analysis exploiting visual cues extracted in the real-world. Our system has been evaluated in a new distributed AV content analysis system for home entertainment. We show attractive experimental results indicating the system efficiency and classification skills, thereby offering new analysis and search/retrieval tools to the consumer