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A Parallel Algorithm of PCA-SIFT Based on CUDA

Ping Zhang, Yongqi Sun, Hao Shen, Rui Zhang
Beijing Key Lab of Traffic Data Analysis and Mining, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
Journal of Information & Computational Science, 11:9, 3137-3147, 2014

@article{zhang2014parallel,

   title={A Parallel Algorithm of PCA-SIFT Based on CUDA},

   author={Zhang, Ping and Sun, Yongqi and Shen, Hao and Zhang, Rui},

   year={2014}

}

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PCA-SIFT is an algorithm to extract invariant features from images, it has been widely applied to many application fields including image processing, computer vision and pattern recognition. However, the execution of PCA-SIFT is time-consuming. A parallel algorithm of PCA-SIFT based on Compute Unified Device Architecture (CUDA) is proposed in this paper, in which each step of PCA-SIFT is implemented in parallel as much as possible. The experimental results show that the speedup of parallel algorithm is 3-5 compared to the original PCA-SIFT while maintaining the same descriptors.
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