ISBN: 978-981-11-0008-6 DOI: 10.18178/wcse.2016.06.133
A Specific Face Positioning Segmentation Research Based on Complex Background
Abstract— Facial gesture, light, expression, and other factors affect the formation of a complex background,
under this wireless visual sensor network identification encountered unprecedented challenges. Traditional
visual identification is required at node distribution is relatively complex environment, the uncontrollable
factors transforming into a controllable, stable characteristic factors during the identification, thus leading to
long recognition time, low efficiency. In this paper, the use of face recognition based on LBP wireless visual
sensor network identity adaptive recognition method to get strong classifier cascade of underlying feature
extraction, through the final Harr face cascade classifier human face testing, and the face region feature
vector PCA dimension reduction, access to low-dimensional feature vector, the number of drop maintain,
establish the simulation experiments, the feature matching facial feature library to complete the identification.
Simulation results show that the proposed algorithm has high accuracy, effectively improve the recognition
Index Terms— wireless sensor, dimensionality reduction, feature matching, adaptive recognition.
College of Engineering Technology, Yang-En University, CHINA
Chen Duan-Sheng, Wang Jing
College of Computer Science and Technolgy, Huaqiao University, CHINA
Cite: Wang Jiang-Tao, Chen Duan-Sheng, Wang Jing, "A Specific Face Positioning Segmentation Research Based on Complex Background," Proceedings of 2016 6th International Workshop on Computer Science and Engineering, pp. 743-748, Tokyo, 17-19 June, 2016.