Research Article
The Realization of Face Recognition Algorithm Based on Compressed Sensing (Short Paper)
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@INPROCEEDINGS{10.1007/978-3-030-12981-1_40, author={Huimin Zhang and Yan Sun and Haiwei Sun and Xin Yuan}, title={The Realization of Face Recognition Algorithm Based on Compressed Sensing (Short Paper)}, proceedings={Collaborative Computing: Networking, Applications and Worksharing. 14th EAI International Conference, CollaborateCom 2018, Shanghai, China, December 1-3, 2018, Proceedings}, proceedings_a={COLLABORATECOM}, year={2019}, month={2}, keywords={Compressed sensing Face recognition Feature extraction Sparse representation classification Image reconstruction}, doi={10.1007/978-3-030-12981-1_40} }- Huimin Zhang
Yan Sun
Haiwei Sun
Xin Yuan
Year: 2019
The Realization of Face Recognition Algorithm Based on Compressed Sensing (Short Paper)
COLLABORATECOM
Springer
DOI: 10.1007/978-3-030-12981-1_40
Abstract
Once the sparse representation-based classifier (SRC) was raised, it achieved a more outstanding performance than typical classification algorithm. Normally, SRC algorithm adopts -norm minimization method to solve the sparse vector, and its computation complexity increases correspondingly. In this paper, we put forward a compressed sensing reconstruction algorithm based on residuals. This algorithm utilizes the local sparsity within figures as well as the non-local similarity among figure blocks to boost the performance of the reconstruction algorithm while remaining a median computation complexity. It achieves a superior recognition rate in the experiments of Yale facial database.
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