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Contour tracking via on-line discriminative active contours

Lv, P and Zhao, Q and Gu, D (2014) Contour tracking via on-line discriminative active contours. In: UNSPECIFIED, ? - ?.

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© 2014 IEEE. This paper presents a novel on-line AdaBoost based discriminative active contour tracking framework (ADACT) using level sets. First we build an on-line AdaBoost based appearance model to track and extract the rough target region, which provides important discriminative clues for our active contour model. Integrating with both edge and discriminative region information, a new active contour model is proposed for obtaining accurate target contour after curve evolution. Experiments on the challenging video sequences demonstrate that the proposed method can achieve more robust deformable target contour tracking under various situations than other competitive contour tracking methods.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: 2014 IEEE International Conference on Image Processing, ICIP 2014
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 23 Jul 2015 10:08
Last Modified: 23 Jan 2019 00:16

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