Gradual training of cascaded shape regression for facial landmark localization and pose estimation

Wibowo, Moh Edi & Tjondronegoro, Dian W. (2013) Gradual training of cascaded shape regression for facial landmark localization and pose estimation. In International Conference on Multimedia and Expo 2013, 15 - 19 July 2013, San Jose, CA.

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Facial landmarks play an important role in face recognition. They serve different steps of the recognition such as pose estimation, face alignment, and local feature extraction. Recently, cascaded shape regression has been proposed to accurately locate facial landmarks. A large number of weak regressors are cascaded in a sequence to fit face shapes to the correct landmark locations. In this paper, we propose to improve the method by applying gradual training. With this training, the regressors are not directly aimed to the true locations. The sequence instead is divided into successive parts each of which is aimed to intermediate targets between the initial and the true locations. We also investigate the incorporation of pose information in the cascaded model. The aim is to find out whether the model can be directly used to estimate head pose. Experiments on the Annotated Facial Landmarks in the Wild database have shown that the proposed method is able to improve the localization and give accurate estimates of pose.

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ID Code: 61607
Item Type: Conference Paper
Refereed: Yes
Keywords: facial landmark localization, pose estimation, cascaded shape regression
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)
Divisions: Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 [please consult the author]
Deposited On: 01 Aug 2013 03:48
Last Modified: 30 Jan 2014 07:56

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