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UGC-JU face database and its benchmarking using linear regression classifier

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Abstract

In this paper, a new face database has been presented which will be freely available to academicians and research community for research purposes. The face database consists of both visual and thermal face images of 84 persons with varying poses, expressions and occlusions (39 different variations for each type, visual or thermal). A new thermal face image recognition technique based on Gappy Principal Component Analysis and Linear Regression Classifier has also been presented here. The recognition performance of this technique on the thermal face images of this database is found to be 98.61 %, which can be considered as the initial benchmark recognition performance this database.

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Acknowledgments

Authors are thankful to a project entitled “Development of 3D Face Recognition Techniques Based on Range Images,” funded by Deity, Govt. of India and “DST-PURSE Programme” at Department of Computer Science and Engineering, Jadavpur University, India for providing necessary infrastructure to conduct experiments relating to this work. Ayan Seal is grateful to Department of Science & Technology (DST), Govt. of India for providing him Junior Research Fellowship-Professional (JRF-Professional) under DST-INSPIRE Fellowship programme [No: IF110591].

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Authors and Affiliations

  1. DST INSPIRE Fellow, Department of Computer Science and Engineering, Jadavpur University, Kolkata, India

    Ayan Seal

  2. Department of Computer Science and Engineering, Jadavpur University, Kolkata, India

    Debotosh Bhattacharjee, Mita Nasipuri & Dipak Kr. Basu

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  1. Ayan Seal
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  2. Debotosh Bhattacharjee
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  3. Mita Nasipuri
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  4. Dipak Kr. Basu
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Correspondence to Ayan Seal.

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Seal, A., Bhattacharjee, D., Nasipuri, M. et al. UGC-JU face database and its benchmarking using linear regression classifier. Multimed Tools Appl 74, 2913–2937 (2015). https://doi.org/10.1007/s11042-013-1754-8

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