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http://dx.doi.org/10.3745/KTCCS.2017.6.4.169

Development of a Visitor Recognition System Using Open APIs for Face Recognition  

Ok, Kisu (KETI 에너지IT)
Kwon, Dongwoo (계명대학교 컴퓨터공학과)
Kim, Hyeonwoo (계명대학교 컴퓨터공학과)
An, Donghyeok (계명대학교 컴퓨터공학부)
Ju, Hongtaek (계명대학교 컴퓨터공학부)
Publication Information
KIPS Transactions on Computer and Communication Systems / v.6, no.4, 2017 , pp. 169-178 More about this Journal
Abstract
Recently, as the interest rate and necessity for security is growing, the demands for a visitor recognition system are being increased. In order to recognize a visitor in visitor recognition systems, the various biometric methods are used. In this paper, we propose a visitor recognition system based on face recognition. The visitor recognition system improves the face recognition performance by integrating several open APIs as a single algorithm and by performing the ensemble of the recognition results. For the performance evaluation, we collected the face data for about five months and measured the performance of the visitor recognition system. As the results of the performance measurement, the visitor recognition system shows a higher face recognition rate than using a single face recognition API, meeting the requirements on performance.
Keywords
Open API Integration; Face Recognition; Visitor Recognition System;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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1 C. Pagano, E. Granger, R. Sabourin, A. Rattani, G. L. Marcialis, and F. Roli, "Efficient adaptive face recognition systems based on capture conditions," in Proceedings of Computational Intelligence in Biometrics and Identity Management, pp.60-67, 2014.
2 L. Wen, G. Guo, and X. Li, "A study on the influence of body weight changes on face recognition," in Proceedings of IEEE International Joint Conference on Biometrics, pp. 1-6, 2014.
3 T. Kim, H. Park, S. H. Hong, and Y. Chung, "Integrated system of face recognition and sound localization for a smart door phone," IEEE Transactions on Consumer Electronics, Vol.59, No.3, pp.598-603, 2013.   DOI
4 M. A. H. Lucas, L. A. Luis, E. B. M. Maria, R. Mariano, T. Juliana, and G. Sergio, "Smart doorbell: An ICT solution to enhance inclusion of disabled people," in Proceedings of ITU Kaleidoscope Trust in the Information Society, pp.1-7, 2015.
5 K. H. Kwon and H. B. Lee, "Gate Management System by Face Recognition using Smart Phone," The Korea Society of Computer and Information, Vol.16, No.11, pp.9-15, 2011.
6 G. D. Thomas, "Ensemble Methods in Machine Learning," Multiple Classifier Systems, Vol.1857, pp.1-5, 2000.
7 K. H. Tin, "Random decision forests," in Proceedings of Document Analysis and Recognition, pp.278-282. 1995.
8 G. Ratsch, T. Onoda, and K. R. Muller, "Soft margins for AdaBoost," Machine Learning, Vol.42, No.3, pp.287-320, 2001.   DOI
9 H. M. Tang, M. R. Lyu, and I. King, "Face recognition committee machine," in Proceedings of International Conference on Multimedia and Expo, Vol.3, pp.425-428, 2003.
10 R. Jafri and H. R. Arabnia, "A survey of face recognition techniques," Information Processing Systems, Vol.5, No.2, pp.41-68, 2009.   DOI
11 Inttelix, Inttelix [Internet], http://www.inttelix.com.
12 TCIT, TCIT [Internet], http://www.tcit-us.com.
13 Digiface, Digiface [Internet], http://www.digiface.com.br.
14 FIRSTEC, FIRSTEC [Internet], http://www.firsteccom.co.kr.
15 VS-KOREA, Smart-Face [Internet], http://www.vs-korea.com.
16 Lambda Labs, Lambda Labs [Internet], https://lambdal.com /face-recognition-api.
17 Betaface, Betaface API [Internet], https://betafaceapi.com.
18 Kairos, Kairos [Internet], https://www.kairos.com.
19 Face++, Face++ [Internet], https://www.faceplusplus.com.
20 S. Z. Li and A. K. Jain, Handbook of face recognition, 2nd ed. Springer, 2011.