Sparse representation for face recognition: A review paper
| Autor: | Rimjhim Padam Singh, Jitendra Madarkar, Poonam Sharma |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Computer science
business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Sparse approximation Facial recognition system QA76.75-76.765 Signal Processing Photography Computer software Computer Vision and Pattern Recognition Artificial intelligence Electrical and Electronic Engineering TR1-1050 business Software |
| Zdroj: | IET Image Processing, Vol 15, Iss 9, Pp 1825-1844 (2021) |
| ISSN: | 1751-9667 1751-9659 |
| DOI: | 10.1049/ipr2.12155 |
| Popis: | With the increasing use of surveillance cameras, face recognition is being studied by many researchers for security purposes. Although high accuracy has been achieved for frontal faces, the existing methods have shown poor performance for occluded and corrupt images. Recently, sparse representation based classification (SRC) has shown the state‐of‐the‐art result in face recognition on corrupt and occluded face images. Several researchers have developed extended SRC methods in the last decade. This paper mainly focuses on SRC and its extended methods of face recognition. SRC methods have been compared on the basis of five issues of face recognition such as linear variation, non‐linear variation, undersampled, pose variation, and low resolution. Detailed analysis of SRC methods for issues of face recognition have been discussed based on experimental results and execution time. Finally, the limitation of SRC methods have been listed to help the researchers to extend the work of existing methods to resolve the unsolved issues. |
| Databáze: | OpenAIRE |
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