Face recognition: challenges, achievements and future directions
Face recognition has received significant attention because of its numerous applications in access control, law enforcement, security, surveillance, Internet communication and computer entertainment. Although significant progress has been made, the state‐of‐the‐art face recognition systems yield sat...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-08-01
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| Series: | IET Computer Vision |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/iet-cvi.2014.0084 |
| _version_ | 1797684877758300160 |
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| author | M. Hassaballah Saleh Aly |
| author_facet | M. Hassaballah Saleh Aly |
| author_sort | M. Hassaballah |
| collection | DOAJ |
| description | Face recognition has received significant attention because of its numerous applications in access control, law enforcement, security, surveillance, Internet communication and computer entertainment. Although significant progress has been made, the state‐of‐the‐art face recognition systems yield satisfactory performance only under controlled scenarios and they degrade significantly when confronted with real‐world scenarios. The real‐world scenarios have unconstrained conditions such as illumination and pose variations, occlusion and expressions. Thus, there remain plenty of challenges and opportunities ahead. Latterly, some researchers have begun to examine face recognition under unconstrained conditions. Instead of providing a detailed experimental evaluation, which has been already presented in the referenced works, this study serves more as a guide for readers. Thus, the goal of this study is to discuss the significant challenges involved in the adaptation of existing face recognition algorithms to build successful systems that can be employed in the real world. Then, it discusses what has been achieved so far, focusing specifically on the most successful algorithms, and overviews the successes and failures of these algorithms to the subject. It also proposes several possible future directions for face recognition. Thus, it will be a good starting point for research projects on face recognition as useful techniques can be isolated and past errors can be avoided. |
| first_indexed | 2024-03-12T00:37:06Z |
| format | Article |
| id | doaj.art-5f046300bd8b47e3969b0aced2d69b4f |
| institution | Directory Open Access Journal |
| issn | 1751-9632 1751-9640 |
| language | English |
| last_indexed | 2024-03-12T00:37:06Z |
| publishDate | 2015-08-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Computer Vision |
| spelling | doaj.art-5f046300bd8b47e3969b0aced2d69b4f2023-09-15T09:33:34ZengWileyIET Computer Vision1751-96321751-96402015-08-019461462610.1049/iet-cvi.2014.0084Face recognition: challenges, achievements and future directionsM. Hassaballah0Saleh Aly1Department of MathematicsFaculty of ScienceSouth Valley UniversityQena83523EgyptDepartment of Electrical EngineeringFaculty of EngineeringAswan UniversityAswanEgyptFace recognition has received significant attention because of its numerous applications in access control, law enforcement, security, surveillance, Internet communication and computer entertainment. Although significant progress has been made, the state‐of‐the‐art face recognition systems yield satisfactory performance only under controlled scenarios and they degrade significantly when confronted with real‐world scenarios. The real‐world scenarios have unconstrained conditions such as illumination and pose variations, occlusion and expressions. Thus, there remain plenty of challenges and opportunities ahead. Latterly, some researchers have begun to examine face recognition under unconstrained conditions. Instead of providing a detailed experimental evaluation, which has been already presented in the referenced works, this study serves more as a guide for readers. Thus, the goal of this study is to discuss the significant challenges involved in the adaptation of existing face recognition algorithms to build successful systems that can be employed in the real world. Then, it discusses what has been achieved so far, focusing specifically on the most successful algorithms, and overviews the successes and failures of these algorithms to the subject. It also proposes several possible future directions for face recognition. Thus, it will be a good starting point for research projects on face recognition as useful techniques can be isolated and past errors can be avoided.https://doi.org/10.1049/iet-cvi.2014.0084face recognition systemsunconstrained conditionsreal-world scenarios |
| spellingShingle | M. Hassaballah Saleh Aly Face recognition: challenges, achievements and future directions IET Computer Vision face recognition systems unconstrained conditions real-world scenarios |
| title | Face recognition: challenges, achievements and future directions |
| title_full | Face recognition: challenges, achievements and future directions |
| title_fullStr | Face recognition: challenges, achievements and future directions |
| title_full_unstemmed | Face recognition: challenges, achievements and future directions |
| title_short | Face recognition: challenges, achievements and future directions |
| title_sort | face recognition challenges achievements and future directions |
| topic | face recognition systems unconstrained conditions real-world scenarios |
| url | https://doi.org/10.1049/iet-cvi.2014.0084 |
| work_keys_str_mv | AT mhassaballah facerecognitionchallengesachievementsandfuturedirections AT salehaly facerecognitionchallengesachievementsandfuturedirections |