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This e-book provides the cutting-edge in face detection and research. It outlines new learn instructions, together with particularly psychology-based facial dynamics attractiveness, aimed toward a variety of purposes reminiscent of habit research, deception detection, and analysis of varied mental issues. subject matters of curiosity contain face and facial landmark detection, face popularity, facial features and emotion research, facial dynamics research, face type, identity, and clustering, and gaze path and head pose estimation, in addition to functions of face analysis.
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Additional info for Advances in Face Detection and Facial Image Analysis
However, building the full illumination cone is tedious, and the low dimensional approximation of the illumination cone is applied in practice. From the view of signal processing, the reflection equation can be considered as the rotational convolution of incident lighting with the albedo of the surface . lCm/Š angle, which is the angle between the polar axis and the z-axis with range 0 Ä Â Ä Ä 180ı /. Pm 180ı , and is the azimuth angle with the range 180ı Ä l is the associated Legendre function, and the two indices meet the conditions l 0 and l m l.
Math. Problems Eng. (2013), Article ID 694321, pp. 1155/2013/694321 15. J. Shotton, A. Fitzgibbon, M. Cook, T. Sharp, M. Finocchio, R. Moore, A. Kipman, A. Blake, Real-time human pose recognition in parts from single depth images. CVPR 2, 3 (2011) 16. R. Mattheij, E. Postma, Y. Van den Hurk, P. Spronck, Depth-based detection using Haarlike features, in Proceedings of the BNAIC 2012 Conference (Maastricht University, The Netherlands, 2012), pp. 162–169 17. M. Anisetti, V. Bellandi, E. Damiani, L.
Anisetti, Fast and robust face detection, in Multimedia Techniques for Device and Ambient Intelligence, Chapter 3 (Springer, US, 2009). ISBN: 978-0-387-88776-0 10. J. Li, Y. Zhang, Learning surf cascade for fast and accurate object detection, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (IEEE, 2013) Hoboken, NJ 07030 USA 11. M. Mathias, et al. Face detection without bells and whistles, in Computer Vision–ECCV 2014 (Springer International Publishing, 2014), Zurich, Switzerland, pp.