JOURNAL ARTICLE

Boosted human head pose estimation using kinect camera

Abstract

Head pose estimation is essential for several computer vision applications. For example, it has been employed in facial expression recognition, head gesture detection, and driver monitoring systems. In this work, we present a boosted method to estimate the head pose using Kinect camera. This estimation is cooperatively performed with the help of RGB and depth images. The human face is located in the RGB image using frontal and profile Viola-Jones (VJ) face detector, where the depth information is used to confine the size and location of the search window. Appearance features, extracted from the detected face patch in the RGB image and its corresponding in the depth image, are passed to Support Vector Machine (SVM) regressors to infer the head pose. Evaluation on two public benchmark databases demonstrates that our proposed approach compares favorably to state-of-the-art approaches.

Keywords:
Artificial intelligence Computer vision Pose RGB color model Computer science Human head Face (sociological concept) Support vector machine Benchmark (surveying) Face detection Head (geology) Pattern recognition (psychology) Facial recognition system Engineering Geography

Metrics

31
Cited By
2.71
FWCI (Field Weighted Citation Impact)
23
Refs
0.93
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Face recognition and analysis
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Face and Expression Recognition
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Video Surveillance and Tracking Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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