An on-line visual human tracking algorithm using SURF-based dynamic object model
Description
The interest point based tracking methods suffer from the limitation of unavailability of sufficient number of matching key points for the target in all frames of a running video. In this paper, a dynamic model is proposed for describing the object model which is used for tracking a human in a non-stationary video. This dynamic model takes into account the change in the pose as well as the motion of the human. A simple autoregression based predictor is used for dealing with the case of full occlusion. Simulation results are provided to show the efficacy of the algorithm.
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| ID Code: | 204238 | ||
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| Item Type: | Chapter in Book, Report or Conference volume (Conference contribution) | ||
| Series Name: | 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings | ||
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| Measurements or Duration: | 5 pages | ||
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| Keywords: | Auto-regression prediction, Human Tracking, SURF | ||
| DOI: | 10.1109/ICIP.2013.6738798 | ||
| ISBN: | 9781479923427 | ||
| Pure ID: | 68086493 | ||
| Copyright Owner: | 2013 IEEE | ||
| Copyright Statement: | This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au | ||
| Deposited On: | 11 Sep 2020 03:43 | ||
| Last Modified: | 02 Mar 2024 03:01 |
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