NDLI: Face recogntion in open world environment

Content Provider	IEEE Xplore Digital Library
Author	Jieqiong Qiu Ya Zhang Jun Sun
Copyright Year	2013
Description	Author affiliation: Shanghai Key Lab. of Multimedia Process. & Transmissions, Shanghai Jiao Tong Univ., Shanghai, China (Jieqiong Qiu; Ya Zhang; Jun Sun)
Abstract	Face recognition in open world environment is a very challenging task due to variant appearances of the target persons and a large scale of unregistered probe faces. In this paper we combine two parallel classifiers, one based on the Local Binary Pattern (LBP) feature and the other based on the Gabor features, to build a specific face recognizer for each target person. Faces used for training are borderline patterns obtained through a morphing procedure combing target faces and random non-target ones. Grid-search is applied to find an optimal morphing-degree-pair. By using an AND operator to integrate the prediction of the two complementary parallel classifiers, many false positives are eliminated in the final results. The proposed algorithm is compared with the Robust Sparse Coding method, using selected celebrities as the target persons and the images from FERET as the non-target faces. Experimental results suggest that the proposed approach is better at tolerating the distortion of the target person's appearance and has a lower false alarm rate.
Starting Page	1
Ending Page	6
File Size	1156924
Page Count	6
File Format	PDF
e-ISBN	9781479902903
DOI	10.1109/VCIP.2013.6706423
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-11-17
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Open world face recognition Local Binary Pattern Target recognition Parallel sub-classifiers Face recognition Feature extraction Classification algorithms Face Gabor wavelets Face morphing Radio access networks
Content Type	Text
Resource Type	Article

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