关键词: 大规模人脸识别, 识别速度, 内存占用, 离散余弦变换, 图像压缩, 区域收缩

Abstract: To increase face recognition speed and reduce RAM occupancy on a large-scale database, a high-efficient face recognition method was proposed. By introducing the technique of Discrete Cosine Transform (DC) image data compression into the face feature database compression, the database was compressed in multi-level compression ratio to generate few compressed sub-databases. Then, according to the order from high-to-low compression ratio, the rough face recognition was implemented on these sub-databases one by one. In the meantime, the recognition scope was narrowed down progressively according to previous recognition results. Finally, the accurate face recognition was carried out on the original uncompressed database in a very small range. Compared to traditional method, the experimental results show that the recognition time is reduced to 29.2%, RAM occupancy is reduced to 10.2%, and hard disk resource consumption is increased by only 11%, and the recognition rate is not significantly reduced.

Key words: large scale face recognition, recognition speed, RAM occupancy, Discrete Cosine Transform (DCT), image compression, region constriction