![](/images/graphics-bg.png)
A Research on Fast Face Feature Points Detection on Smart Mobile Devices
Joint Authors
Zhang, Xingming
Li, Xiaohe
Wang, Haoxiang
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-02-25
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
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.
American Psychological Association (APA)
Li, Xiaohe& Zhang, Xingming& Wang, Haoxiang. 2018. A Research on Fast Face Feature Points Detection on Smart Mobile Devices. Wireless Communications and Mobile Computing،Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1216427
Modern Language Association (MLA)
Li, Xiaohe…[et al.]. A Research on Fast Face Feature Points Detection on Smart Mobile Devices. Wireless Communications and Mobile Computing No. 2018 (2018), pp.1-8.
https://search.emarefa.net/detail/BIM-1216427
American Medical Association (AMA)
Li, Xiaohe& Zhang, Xingming& Wang, Haoxiang. A Research on Fast Face Feature Points Detection on Smart Mobile Devices. Wireless Communications and Mobile Computing. 2018. Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1216427
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1216427