Abstract
Face recognition has received tremendous support in the discipline of computer, which is used for automatic attendance from CCTV (closed circuit television) cameras, monitoring criminal activity, and person tracking systems, etc. Tracking through video surveillances includes pre-processing, feature extraction, face detection and face recognition. Many problems are there when detecting faces during process of face recognition through surveillance camera like low quality camera, illumination problem, variation in face angle, occlusion problem, variation in facial expression, etc. some of these are still required more attention which is illumination and occlusion. When human faces are covered with some objects like face mask, sunglasses, beard, scarf and many other than face recognition accuracy have been drastically decreased. As many researchers have worked on tracking individuals from Surveillance camera, which found that still occlusion along with illumination is major problem when CCTV camera recognizes the face from the live feed as specially faces with the face mask. There are numerous algorithms and classifiers that can identify and comprehend faces of person from the front as well as with certain changes in an orientation of the face, but not many researches are utilized for unconstrained and occluded with illumination video-based face Recognition. So, this research review concentrates on various diverse algorithm for face recognition with occlusion and illumination from the surveillance camera and its parameter like execution time as well as recognition accuracy.
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Desai, H.S., Gonsai, A.M. (2022). Comparative Study on Video Based Face Recognition Methods. In: Rathore, V.S., Sharma, S.C., Tavares, J.M.R., Moreira, C., Surendiran, B. (eds) Rising Threats in Expert Applications and Solutions. Lecture Notes in Networks and Systems, vol 434. Springer, Singapore. https://doi.org/10.1007/978-981-19-1122-4_30
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