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Thermal Face Recognition based on Physiological Information

Citation Author(s):
Shinfeng D. Lin, Kuanyuan Chen, Wensheng Chen
Submitted by:
Shin-Feng Lin
Last updated:
18 September 2019 - 9:04am
Document Type:
Poster
Document Year:
2019
Event:
Presenters:
Shinfeng D. Lin
Paper Code:
2429

Abstract

In this paper, we propose a novel thermal face recognition based on physiological information. The training phase includes preprocessing, feature extraction and classification. In the beginning, the human face can be depicted from the background of thermal image using the Bayesian framework and normalized to uniform size. A grid of 22 thermal points is extracted as a feature vector. These 22 extracted points are used to train Linear Support Vector Machine Classifier (linear SVC). The classifier calculates the support vectors and uses them to find the hyperplane for classification. A feature vector of testing image is inputted to the classifier for face recognition. Our contribution is that the proposed method firstly applies temperature information in face recognition. Experimental results prove the effectiveness of the proposed method.

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ICIP2019 poster_20190925.pdf

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