基于可变形部件模型的驾驶员人脸检测

Translated title of the contribution: Driver Face Detection Based on Deformable Part-Based Model

Meng Zhao, He Zhang, Mao Yong Cao, Pei Rui Bai, Yang Wang, Ming Tao Pei

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

To solve the problem of detecting driver faces from cabs images taken by traffic cameras,a driver face detection method was proposed based on deformable part-based model,overcoming the condition influence such as dim light,occlusion and low resolution in cabs.Firstly,extracting aggregate channel features (local binary pattern and histogram of oriented gradient),the candidate faces were obtained.Then,considering the relative settled position between the license plate and driver face,the driver face and plate were taken as two deformable parts of a face-plate couple based on the concept of deformable part-based model,and the ubiety of two parts was used to determine the position of the candidate face.Experimental results show that the proposed method can improve the detection accuracy and overall performance,effectively filter out the false face alarm,and the recall rate is less affected.

Translated title of the contributionDriver Face Detection Based on Deformable Part-Based Model
Original languageChinese (Traditional)
Pages (from-to)393-397
Number of pages5
JournalBeijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume38
Issue number4
DOIs
Publication statusPublished - 1 Apr 2018

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