Projects > Modeling Spatial Relationships in Human and Object Interactions for Human Activity Understanding in Video Surveillance |
Modeling Spatial Relationships in Human and Object Interactions for Human Activity Understanding in Video SurveillanceProject Team: Prof. YUEN, Pong Chi |
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Project description |
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Human action recognition plays an important role in video and image understanding and analysis. It can be applied to Intelligent Video Surveillance systems to analyze surveillance data automatically. With the rapid growth in the use of CCTV cameras for video surveillance, the amount of surveillance data to be processed increases significantly. Such a huge demand in automation makes human action recognition became more and more important in our society. While human activity understanding has been an active research area in the past decades, most of the existing approaches focus on analyzing the movement of the human subject being tracked. On the other hand, less attention has been paid on extracting context in human-object interactions to provide addition information for analysis. This project will focus on developing a new representation model in this challenging research topic. In particular, we will develop a view-insensitive spatial relation based model to represent human-object interactions. Preliminary results show that the prototype of our new representation is robust in different situations. By using our method, the accuracy of video and image understanding and analysis can be improved. |
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(http://poeticoncorpus.kyb.mpg.de/). |
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Funded projects |
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Relevant publications |
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For further information on this project, please contact Prof. YUEN, Pong Chi. |