Real-Time Vision Tracking Algorithm
Real-time object tracking is recently becoming very important in many video processing tasks. Applications like video surveillance, robotics, people tracking, etc., need reliable and economically affordable video tracking tools. Most of current available solutions are, however, computationally intensive and sometimes require expensive video hardware. In this paper, we propose a new object tracking algorithm for real-time video that relies in the combination of a similarity measure with an euclidian metric. This approach infers the trajectory of a moving object by applying a very simple optimization method which makes the tracking algorithm robust and easy to implement. Experimental results are provided to demonstrate the performance of the proposed tracking algorithm in complex real-time video sequence scenarios.
KeywordsTracking Algorithm Color Histogram Tracking Window Object Tracking Algorithm Propose Tracking Algorithm
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- 1.Trucco, E.: Introductory techniques for 3D computer vision. Prentice Hall, NJ (1998)Google Scholar
- 2.Birchfield, S.T.: Elliptical Head Tracking Using Intensity Gradients and Color Histograms. In: Proc. Conf. Computer Vision and Pattern Recognition, pp. 232–237 (1998)Google Scholar
- 3.Bradski, G.R.: Computer Vision Face Tracking for Use in a Perceptual User Interface. Intel Technology Journal (1998)Google Scholar
- 4.Comaniciu, D., Ramesh, V., Meer, P.: Real-Time Tracking of Non-Rigid Objects Using Mean Shift. In: Proc. Conf. Computer Vision and Pattern Recognition, vol. 2, pp. 142–149 (2000)Google Scholar
- 6.Chen, H.-T., Liu, T.-L.: Trust-Region Methods for Real-Time Tracking. In: IEEE 8th International Conference on Computer Vision, vol. 2(3) (2001)Google Scholar