By J. Matteson

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IEEE Trans. Pattern Anal. Mach. Intell. 24, 509–522 (2002) 14. : Learning motion categories using both semantic and structural information. In: IEEE Conference on Computer Vision and Pattern Recognition (2007) 15. : A biologically inspired system for action recognition. In: IEEE International Conference of Computer Vision (2007) 16. : Learning realistic human actions from movies. In: IEEE Conference on Computer Vision and Pattern Recognition (2008) 17. : Recognizing human actions: a local svm approach.

Efficient object retrieval from videos. In: The 12th European Signal Processing Conference, Vienna, Austria, September 2004 5. : Object retrieval with large vocabularies and fast spatial matching. In: IEEE Conference on Computer Vision and Pattern Recognition, June 2007, pp. 1–8 (2007) 6. : Scale & affine invariant interest point detectors. Int. J. Comput. Vis. 60, 63–86 (2004) 7. : The recognition of human movement using temporal templates. IEEE Trans. Pattern Anal. Mach. Intell. 23(3), 257–267 (2001) 8.

In each meeting, four participants were grouped together, and were asked to design a remote control device over a series of sessions. Each person was assigned a role such as “Project Manager”, “Marketing Expert”, or “Industrial Designer”. A microphone array and four cameras were set in the center of the room. Side and rear cameras were also mounted to capture different angles of the meeting room and its participants, as shown in Fig. 2. Each camera captures the visual activity of a single seated participant, who is assigned a seat at the start of each meeting session.

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