Click Here for
Track Your Paper

International Journal of New Technology and Research

Impact Factor 3.953

(An ISO 9001:2008 Certified Online Journal)
India | Germany | France | Japan

Face Recognition from Invariant Illumination Based on Textural Analysis and Machine Learning Approach

( Volume 4 Issue 3,March 2018 ) OPEN ACCESS

Mr. M. Prabu, Yash Srivastava, Arnav Shankar, Aditya Kumar Singh, Hillol Chatterjee


Matching people across multiple camera views known as person re-identification, is a challenging problem due to the change in visual appearance caused by varying lighting conditions. The perceived color of the subject appears to be different with respect to illumination. In this paper, we propose a data driven approach for learning color patterns from pixels sampled from images across two camera views. The intuition behind this work is that, even though pixel values of same color would be different across views, they should be encoded with the same values. We model color feature generation as a learning problem by jointly learning a linear transformation and a dictionary to encode pixel values. Dominant Rotated Local Binary Pattern (DRLBP) have been proposed yields better performance. This paper proposes a novel method of classifying the human face using Convolutional Neural Network.

Paper Statistics:

Total View : 154 | Downloads : 145 | Page No: 150-153 |

Cite this Article:
Click here to get all Styles of Citation using DOI of the article.