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Acceleration of object tracking in high‐speed videogrammetry using a parallel OpenMP and SIMD strategy
Author(s) -
Tong Xiaohua,
Zheng Shouzhu,
Gao Sa,
Liu Sicong,
Chen Peng,
Guo Chengcheng,
Liu Shijie,
Xie Huan,
Jin Yanmin,
Ye Zhen,
Xu Xiong,
Wei Chao,
Hu Lintao
Publication year - 2019
Publication title -
the photogrammetric record
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.638
H-Index - 51
eISSN - 1477-9730
pISSN - 0031-868X
DOI - 10.1111/phor.12279
Subject(s) - simd , laptop , computer science , workstation , acceleration , process (computing) , parallel computing , speedup , tracking (education) , object (grammar) , parallel processing , computational science , computer graphics (images) , artificial intelligence , operating system , psychology , pedagogy , physics , classical mechanics
High‐speed cameras are able to effectively and efficiently obtain the location of moving objects over time in many practical applications. In order to meet the requirement for fast computing and processing in the object‐tracking process, this paper adopts parallel computing to process multiple video‐image sequences by using open multi‐processing (Open MP ) and single‐instruction multiple data ( SIMD ) simultaneously, combined with a coarse‐to‐fine matching method. Experimental results showed that the proposed method: (1) has a high accuracy compared with other methods; (2) demonstrates a higher computational efficiency than other methods; and (3) has an efficiency running on a laptop equivalent to other methods running on a computer workstation.