Object Detection and Recognition in Active Video

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Object detection and recognition localize visual objects and recognize their corresponding classes, identities, and activities in images and videos. This task is the foundation of understanding the image and video content, thus it is one of the central topics in Computer Vision and Multimedia. In general, digital video taken by humans is purposive -- aiming for the Object(s) of Interest (OOI). Typical examples include filming, professional video cameramen covering sporting events, or an amateur shooting at a tourist scene (e.g., buildings, sculptures/statues, and activities of the crowd/people). Efforts are made to locate the OOI, examine it closely by close-ups or multiple views, and follow it if it is moving. We call the video thus produced Active Video. It is characterized by the presence of salient OOI, richer context yielded by the purposive camera movements, and it is more object-centered than in non-active videos.******The short-term objectives of the proposed research program are to seek new answers to the important problem of visual object detection and recognition in Active Video. In particular, the program will research and develop: (a) Algorithms to explore saliency and attention models in Active Video; (b) Features and descriptors that can better capture the Active Context; and (c) Boosted classifiers that are more discriminative, robust, and efficient. Research projects in several application areas will be conducted including, for example, 3D Active Video and Faces in Active Video. The long-term objective of my research is to advance the knowledge in visual object-based image and video processing and analysis. It is largely motivated by cues from the intelligent human vision system.******The anticipated impact of this research is two-fold: (a) It will generate new algorithms and solutions for better visual object detection and recognition which are urgently needed by the digital video and multimedia research community and industries. (b) It will directly contribute to the discovery of knowledge in this area in the form of academic publications in top conferences and journals, and to the training of Highly Qualified Personnel (HQP) for Canada.**