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Proceedings Paper

A multi-view face recognition system based on cascade face detector and improved Dlib
Author(s): Hongjun Zhou; Pei Chen; Wei Shen
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Paper Abstract

In this research, we present a framework for multi-view face detect and recognition system based on cascade face detector and improved Dlib. This method is aimed to solve the problems of low efficiency and low accuracy in multi-view face recognition, to build a multi-view face recognition system, and to discover a suitable monitoring scheme. For face detection, the cascade face detector is used to extracted the Haar-like feature from the training samples, and Haar-like feature is used to train a cascade classifier by combining Adaboost algorithm. Next, for face recognition, we proposed an improved distance model based on Dlib to improve the accuracy of multiview face recognition. Furthermore, we applied this proposed method into recognizing face images taken from different viewing directions, including horizontal view, overlooks view, and looking-up view, and researched a suitable monitoring scheme. This method works well for multi-view face recognition, and it is also simulated and tested, showing satisfactory experimental results.

Paper Details

Date Published: 8 March 2018
PDF: 6 pages
Proc. SPIE 10609, MIPPR 2017: Pattern Recognition and Computer Vision, 1060908 (8 March 2018); doi: 10.1117/12.2282829
Show Author Affiliations
Hongjun Zhou, Sun Yat-Sen Univ. (China)
Pei Chen, Sun Yat-Sen Univ. (China)
Wei Shen, Sun Yat-Sen Univ. (China)

Published in SPIE Proceedings Vol. 10609:
MIPPR 2017: Pattern Recognition and Computer Vision
Zhiguo Cao; Yuehuang Wang; Chao Cai, Editor(s)

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