A real time micro-expression detection system with LBP-TOP on a many-core processor

Citation

Soh, Xin Rong and Baskaran, Vishnu Monn and Buhari, Adamu Muhammad and Phan, Raphael (2017) A real time micro-expression detection system with LBP-TOP on a many-core processor. In: 2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 12-15 Dec. 2017, Kuala Lumpur, Malaysia.

[img] Text
66.pdf - Published Version
Restricted to Repository staff only

Download (1MB)

Abstract

The implementation of a micro-expression detection system introduces challenges to sustain a real time recognition result. In order to surmount these problems, this paper examines the algorithm of a serial Local Binary Pattern from Three Orthogonal Planes (LBP-TOP) in order to identify the performance limitations for real time system. Videos from SMIC and CASMEII were up sampled to higher resolutions (280×340, 560×680 and 1120×1360) to cater the need of real life implementation. Then, a parallel multicore-based LBP-TOP algorithm is studied as a benchmark. Experimental results show that the parallel LBP-TOP algorithm exhibits 7× and 8× speedup against serial LBP-TOP for SMIC and CASMEII database respectively for the highest tested video resolution utilising 24- logical processor multi-core architecture. To further reduce the computational time, this paper also proposes a many-core parallel LBP-TOP algorithm using Compute Unified Device Architecture (CUDA). In addition, a method is designed to calculate the threads and blocks required to launch the kernel when processing videos from different resolutions. The proposed algorithm increases the performance speedup to 117× and 130× against the serial algorithm for the highest tested resolution videos

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Parallel
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK452-454.4 Electric apparatus and materials. Electric circuits. Electric networks
Divisions: Faculty of Engineering (FOE)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 26 Apr 2021 14:40
Last Modified: 26 Apr 2021 14:40
URII: http://shdl.mmu.edu.my/id/eprint/7655

Downloads

Downloads per month over past year

View ItemEdit (login required)