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A CNN Model for Head Pose Recognition using Wholes and Regions
2019
2019 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2019)
Head pose recognition and monitoring is key to many real-world applications, since it is a vital indicator for human attention and behavior. Currently, head pose is often computed by localizing landmarks on a targeted face and solving 2D to 3D correspondence problem with a mean head model. Recent research has shown that this is a brittle approach since it relies entirely on the accuracy of landmark detection, the extraneous head model and an ad-hoc alignment step. Recent work has also shown
doi:10.1109/fg.2019.8756536
dblp:conf/fgr/BeheraGWRQ19
fatcat:wxvp27qczndc5ad2edjj5dd7jm