Multi-View Constrained Local Models for Large Head Angle Facial Tracking

Georgia Rajamanoharan, Timothy F. Cootes; The IEEE International Conference on Computer Vision (ICCV) Workshops, 2015, pp. 18-25

Abstract


We propose Multi-View Constrained Local Models - a simple but effective technique for improving facial point detection under large head angles, such as in a car driving setting. Our approach combines a global shape model with separate sets of response maps targeted at different head angles, indexed on the shape model parameters. We explore shape-space division strategies and show that, as well as outperforming the traditional method, our approach also provides a marked speed-up which demonstrates the suitability of this technique for real-time face tracking.

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[bibtex]
@InProceedings{Rajamanoharan_2015_ICCV_Workshops,
author = {Rajamanoharan, Georgia and Cootes, Timothy F.},
title = {Multi-View Constrained Local Models for Large Head Angle Facial Tracking},
booktitle = {The IEEE International Conference on Computer Vision (ICCV) Workshops},
month = {December},
year = {2015}
}