Hog active appearance models

Antonakos, Epameinondas, Alabort-i-Medina, Joan, Tzimiropoulos, Georgios and Zafeiriou, Stefanos (2014) Hog active appearance models. In: IEEE International Conference on Image Processing, 2014 (ICIP 2014), 27-30 October 2014, Paris, France.

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We propose the combination of dense Histogram of Oriented Gradients (HOG) features with Active Appearance Models (AAMs). We employ the efficient Inverse Compositional optimization technique and show results for the task of face fitting. By taking advantage of the descriptive characteristics of HOG features, we build robust and accurate AAMs that generalize well to unseen faces with illumination, identity, pose and occlusion variations. Our experiments on challenging in-the-wild databases show that HOG AAMs significantly outperfrom current state-of-the-art results of discriminative methods trained on larger databases.

Item Type: Conference or Workshop Item (Paper)
RIS ID: https://nottingham-repository.worktribe.com/output/997888
Additional Information: © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Published in: IEEE International Conference on Image Processing, 2014 (ICIP 2014), IEEE, 2014, ISBN 9781479957521. doi: 10.1109/ICIP.2014.7025044
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Depositing User: Tzimiropoulos, Yorgos
Date Deposited: 29 Jan 2016 13:27
Last Modified: 04 May 2020 20:16
URI: https://eprints.nottingham.ac.uk/id/eprint/31435

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