基于GPU并行加速的2DPCA人脸识别算法

Face recognition technology is based on identifying by using human face features. Nowadays, it has become an indispensible part of our society. Principle Component Analysis (PCA) algorithm is one of the major face recognition technologies. With thousands of human faces to recognize and pixels to read, the matrix computing becomes huge, which makes PCA algorithm cost long time and undoubtedly unfit for serial running. To overcome the shortcoming, the paper combines a Two-Dimensional PCA (2DPCA) algorithm, which based on two-dimensional processing, and discovers a new parallel speedup 2DPCA algorithm using GPU computing which can still run on a single computer. Through the experiments by testing ORL human faces, a conclusion is brought out that the new algorithm is more than 10,000 times faster than the original PCA algorithm, while still using one single computer and can keep the recognition rate.