Image Training, Corner and FAST Features based Algorithm for Face Tracking in Low Resolution Different Background Challenging Video Sequences

• Published in: International journal of image, graphics and signal processing Vol. 10; no. 8; pp. 39 - 53
• Main Authors: S, Ranganatha, Gowramma, Y P
• Format: Journal Article
• Language: English
• Published: Hong Kong Modern Education and Computer Science Press 08.08.2018
• Subjects: Algorithms; Face recognition; Feature extraction; Image detection; Occlusion; Tracking; Video compression
• ISSN: 2074-9074; 2074-9082; 2074-9082
• DOI: 10.5815/ijigsp.2018.08.05

We are proposing a novel algorithm for tracking human face(s) in different background video sequences. We have trained both face and non-face images which help in face(s) detection process. At first, FAST features and corner points are extracted from the detected face(s). Further, mid points are calculated from corner points. FAST features, corner points and mid points are combined together. Using the combined points, point tracker tracks face(s) in the frames of the video sequence. Standard metrics were adopted for measuring the performance of the proposed algorithm. Low resolution video sequences with challenges such as partial occlusion, changes in expression, variations in illumination and pose took part while testing the proposed algorithm. Test results clearly indicate the robustness of the proposed algorithm on all different background challenging video sequences.