| Title: |
Features based face detection tracking and recognition in video surveillance. |
| Authors: |
Reeja, Y. Mary; Preethi, B. C.; Absa, S.; Sujitha, S. Maria Seraphin |
| Source: |
AIP Conference Proceedings; 2025, Vol. 3137 Issue 1, p1-10, 10p |
| Subject Terms: |
Artificial intelligence; Principal components analysis; Video surveillance; Biometric identification; Image intensifiers |
| Abstract: |
Face is the most common biometric used for identification. So in advanced technology by using machine intelligence it is necessary to identify face from all other objects. Face detection and tracking has been an important research area as it is used in many applications. It is the most initial step in face analysis, face localization and image enhancement. This paper focuses on applying face detection, tracking and recognition in surveillance systems. This will be helpful in monitoring customer arrival in shopping mall, hospital and in high security areas. The input image may be still or dynamic image. Face detection determines the presence and location of a face in an image by distinguishing the face from all other patterns present in the scene. Face tracking helps to identify moving faces in video frame. Face detection and tracking are performed using features based adaboost algorithm. Face recognition helps to find the correct match from the trained images. This is done by improved principal component analysis. The feature based methods used in this paper helps to detect face in the presence of varying light conditions, obstacles, gender, age, etc. By using these combined methods accuracy and detection rate will be improved. [ABSTRACT FROM AUTHOR] |
| : |
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| Database: |
Complementary Index |