Extracting Motion Features for Visual Human Activity Representation
This paper presents a technique to characterize human actions in visual surveillance scenarios in order to describe, in a qualitative way, basic human movements in general imaging conditions. The representation proposed is based on focus of attention concepts, as part of an active tracking process to describe target movements. The introduced representation, named “focus of attention” representation, FOA, is based on motion information. A segmentation method is also presented to group the FOA in uniform temporal segments. The segmentation will allow providing a higher level description of human actions, by means of further classifying each segment in different types of basic movements.
KeywordsReceptive Field Optical Flow Video Shot Human Activity Recognition Segmented Target
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- 1.BenAbdelkader, C., Cutler, R., Davis, L.: Motion-based recognition of people in EigenGait space. In: V Int. Conf. on Automatic Face Gesture Recognition (2002)Google Scholar
- 2.Bobick, A.F., Davis, J.W.: The recognition of human movement using temporal templates. IEEE. Trans. on PAMI 23(3), 257–267 (2001)Google Scholar
- 3.Bodor, R., Jackson, B., Papanikoloupolos, N.: Vision-based human tracking and activity recognition. In: XI Mediterranean Conf. on Control and Automation (2003)Google Scholar
- 7.Davis, J.W., Tyagi, A.: A reliable-inference framework for recognition of human actions. In: IEEE Conf. on Advance Video and Signal Based Surveillance, pp. 169–176 (2003)Google Scholar
- 8.Essa, I.A., Pentland, A.P.: Coding, analysis, interpretation and recognition of facial expressions. IEEE Trans. on PAMI 19(7), 757–763 (1997)Google Scholar
- 9.Masoud, O., Papanikolopoulos, N.: Recognizing human activities. In: IEEE Conf. on Advanced Video and Signal Surveillance (2003)Google Scholar
- 10.Rui, Y., Anandan, P.: Segmenting visual actions based on spatio-temporal motion patterns. In: IEEE Int. Conf. on Computer Vision and Pattern Recognition (2000)Google Scholar
- 11.CAVIAR Project IST 2001 37540, http://homepages.inf.ed.ac.uk/rbf/CAVIAR/