Title: Research on facial feature-based gender intelligent recognition based on the Adaboost algorithm
Authors: Jing Wang
Addresses: Department of Energy and Intelligence Engineering, Henan University of Animal Husbandry and Economy, Zhengzhou 450011, China
Abstract: In order to overcome the problem of poor facial recognition intelligence and weak gender judgment, a new method based on Adaboost algorithm for facial feature-based gender intelligence recognition is proposed in this paper. In this method, the three-dimensional special point detection, weak perspective projection, spatial region segmentation and other methods are employed to construct the facial feature information sampling model. The Adaboost algorithm is used to analyse the matching between facial features and gender, on which facial-feature gender intelligent recognition is performed according to the distribution of the eyes, nose and mouth of the face image, and the edge contour detection model of the face image is constructed. The experimental results show that the method has the advantages of good intelligence, high recognition precision and short time cost in face-based gender recognition.
Keywords: Adaboost algorithm; facial features; intelligent identification; gender.
International Journal of Biometrics, 2021 Vol.13 No.1, pp.40 - 50
Received: 10 Dec 2019
Accepted: 26 Mar 2020
Published online: 05 Jan 2021 *