Title: Research on facial expression recognition of video stream based on OpenCV
Authors: Feng Gao; Daizhong Luo; Xinqiang Ma
Addresses: School of Artificial Intelligence, Chongqing University of Arts and Sciences, Chongqing 402160, China; Lyceum of the Philippines University – Batangas Campus, Batangas City, Philippines ' School of Artificial Intelligence, Chongqing University of Arts and Sciences, Chongqing 402160, China ' School of Artificial Intelligence, Chongqing University of Arts and Sciences, Chongqing 402160, China
Abstract: In order to overcome the poor performance of expression similarity measurement in traditional video stream facial expression recognition methods, an OpenCV based facial expression recognition method is proposed. In this method, the video stream face detection image is obtained by the window detection of various features in each position for the video stream image through the cascade classifier, and the image preprocessing is implemented. Based on OpenCV, the most important eyes and mouth in the facial expression are modeled, the eye feature model and mouth feature model are constructed, and the facial expression recognition of the video stream is realised through the constructed model. The experimental results show that the performance of expression similarity measurement is better, and the recognition rate of different expressions is more than 90%.
Keywords: OpenCV; video stream; face; facial expression recognition.
International Journal of Biometrics, 2021 Vol.13 No.1, pp.114 - 129
Received: 01 Feb 2020
Accepted: 09 Apr 2020
Published online: 05 Jan 2021 *