A multicore accelerated implementation for statistical analysis of facial expressions in video
Sümeyye Bayrakdar, İbrahim Yücedağ, Devrim Akgün · 2016
Recently, the analysis of facial expressions has become one of the important research areas in computer vision and image processing. Analysing facial expressions quickly and accurately play a critical role in many software systems for various applications. In this study, a new algorithm is proposed for the acceleration of video-based facial expression analysis that is performed using cubic Bézier curves. Performance evaluation of the expression analysis accelerated with parallel threads on multi-core computers has been presented. The experiments have been conducted with eNTERFACE'05 emotion video database. Experimental results were obtained using quad-core processor with Hyper Threading technology. According to experimental results, quad core processor using two threads produced about 1.8 fold speed-up and four threads produced about 2.9 fold speed-up while eight threads produced about 3.5 fold speed-up has been obtained.