A Research on Fast Face Feature Points Detection on Smart Mobile Devices. (25th February 2018)

• Record Type: Journal Article
• Authors: Li, Xiaohe; Zhang, Xingming; Wang, Haoxiang
• Other Names: Ning Zhaolong Academic Editor.
• Is Part Of: Wireless communications and mobile computing. Volume 2018(2018)
• Publication Date: 2018-02-25
• Subjects: Wireless communication systems -- Periodicals; Mobile communication systems -- Periodicals; 621.38205
• DOI: 10.1155/2018/9729014
• Languages: English
• ISSNs: 1530-8669

Abstract

Abstract : We explore how to leverage the performance of face feature points detection on mobile terminals from 3 aspects. First, we optimize the models used in SDM algorithms via PCA and Spectrum Clustering. Second, we propose an evaluation criterion using Linear Discriminative Analysis to choose the best local feature descriptions which plays a critical role in feature points detection. Third, we take advantage of multicore architecture of mobile terminal and parallelize the optimized SDM algorithm to improve the efficiency further. The experiment observations show that our final accomplished GPC-SDM (improved Supervised Descent Method using spectrum clustering, PCA, and GPU acceleration) suppresses the memory usage, which is beneficial and efficient to meet the real-time requirements.