於行動裝置上利用GPU平行運算實現FAST角點偵測演算法

Implementation of Parallel Computing FAST Algorithm on Mobile GPUs

Chien-Hsing Chou, Peter Liu, Tai-Yi Wu [Paper PDF]

Corner detection is an extremely important technique in image recognition, which is widely employed in various applications for image recognition. With the widespread use of mobile devices, image recognition techniques are frequently applied in such devices. However, the hardware resource of smartphones are lacked and restricted, it is a difficult task to apply the techniques of corner detection smoothly in these devices. To enhance the computational speed, the FAST corner detection algorithm is implemented with parallel computing of GPU in mobile devices. In the experiments, the computational speed of the FAST corner detection algorithm increases 24 times after using GPU parallel computing. Compared with the widely known SURF algorithm, which is computed with mobile CPU only, the proposed technique in this study is 468 times faster than SURF algorithm.

[Program1 Download] This Program is developed on iOS Xcode, and contains "FAST-GPU", "FAST-CPU". (Two Methods)

## Program1 can test only Xcode Simulator and and iPhone3GS and iPhone4.

[Program2 Download]  This Program is developed on iOS Xcode, and contains "FAST-GPU", "FAST-CPU", "SURF-CPU". (Three Methods)

## Program2 can be only tested on the real devices of iPhone3GS and iPhone4 (Can't run the program on Simulator).