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Face Detection by Aggregating Visible Components

  • Jiali DuanEmail author
  • Shengcai Liao
  • Xiaoyuan Guo
  • Stan Z. Li
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10117)

Abstract

Pose variations and occlusions are two major challenges for unconstrained face detection. Many approaches have been proposed to handle pose variations and occlusions in face detection, however, few of them addresses the two challenges in a model explicitly and simultaneously. In this paper, we propose a novel face detection method called Aggregating Visible Components (AVC), which addresses pose variations and occlusions simultaneously in a single framework with low complexity. The main contributions of this paper are: (1) By aggregating visible components which have inherent advantages in occasions of occlusions, the proposed method achieves state-of-the-art performance using only hand-crafted feature; (2) Mapped from meanshape through component-invariant mapping, the proposed component detector is more robust to pose-variations (3) A local to global aggregation strategy that involves region competition helps alleviate false alarms while enhancing localization accuracy.

Keywords

False Alarm Face Detection Weak Classifier Facial Component Face Detection Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgement

This work was supported by the National Key Research and Development Plan (Grant No. 2016YFC0801002), the Chinese National Natural Science Foundation Projects #61672521, #61473291, #61572501, #61502491, #61572536, NVIDIA GPU donation program and AuthenMetric R&D Funds.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Jiali Duan
    • 1
    Email author
  • Shengcai Liao
    • 2
  • Xiaoyuan Guo
    • 3
  • Stan Z. Li
    • 2
  1. 1.School of Electronic, Electrical and Communication EngineeringUniversity of Chinese Academy of SciencesBeijingChina
  2. 2.Center for Biometrics and Security Research and National Laboratory of Pattern Recognition, Institute of AutomationChinese Academy of SciencesBeijingChina
  3. 3.School of Engineering ScienceUniversity of Chinese Academy of SciencesBeijingChina

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