Team members:
Chen-Ping Yu, Kyle Brocklehurst, Sitapa Rujikietumjorn
Project overview:
In this project, we focused on object tracking using contours. Specifically, we attempt to track objects that may deform substantially. Where this can be useful is for image segmentation and general object tracking. We formulate the contour as a Hidden Markov Model, which was proposed by Huang [1]. In each new frame, we allow the states (locations along the boundary) to adapt to new observations of edge detection and NCC score against a patch centered at their location along the previous frame, while constraining smoothness of neighboring transitions as well. To do this, the forward-backward algorithmis used to find the global optimum set of contour landmark points in the new frame.
Project Report: [pdf]
Reference:
[1] Y. Chen, Y. Rui, and T. S. Huang, “Multicue hmm-ukf for real-time contour tracking,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 28, no. 9, pp. 1525–1529, 2006.
Sample Results and Demo Videos: (Click images for video)
** videos require Xvid MPEG-4 codec, can be downloaded from http://www.xvidmovies.com/codec/
