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Implementation and Optimization of Image Processing Algorithms on Embedded GPU

2012; Institute of Electronics, Information and Communication Engineers; Volume: E95.D; Issue: 5 Linguagem: Inglês

10.1587/transinf.e95.d.1475

1745-1361

Nitin Singhal, Jin Woo Yoo, Ho Yeol Choi, In Kyu Park,

Video Surveillance and Tracking Methods

In this paper, we analyze the key factors underlying the implementation, evaluation, and optimization of image processing and computer vision algorithms on embedded GPU using OpenGL ES 2.0 shader model. First, we present the characteristics of the embedded GPU and its inherent advantage when compared to embedded CPU. Additionally, we propose techniques to achieve increased performance with optimized shader design. To show the effectiveness of the proposed techniques, we employ cartoon-style non-photorealistic rendering (NPR), speeded-up robust feature (SURF) detection, and stereo matching as our example algorithms. Performance is evaluated in terms of the execution time and speed-up achieved in comparison with the implementation on embedded CPU.