Multimodal Semantic Analysis of Public Transport Movements
نویسندگان
چکیده
We present a system for multimodal, semantic analysis of person movements that incorporates data from surveillance cameras, weather sensors, and third-party information providers. The interactive demonstration will show the automated creation of a survey of passenger transfer behavior at a public transport hub. Such information is vital for public transportation planning and the presented approach increases the cost-effectiveness and data accuracy as compared to traditional methods.
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تاریخ انتشار 2009