Person Independent Head Pose Estimation by Non-Linear Regression and Manifold Embedding
نویسندگان
چکیده
This paper describes an approach to head pose estimation in passport type images with an emphasis on high accuracy for near-frontal poses as well as person independence. Two different algorithms are proposed and compared. A Histogram of Oriented Gradients (HOG) descriptor is used for non-linear regression and a Biased Manifold Embedding (BME) approach is extended to cope with multiple poseangles. In addition, we present an approach for the creation of an artificial training database. The effectiveness of the algorithms is shown on the artificial database as well as on a publicly available dataset where the HOG based approach performs best.
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