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International Journal of Image, Graphics and Signal Processing(IJIGSP)

ISSN: 2074-9074 (Print), ISSN: 2074-9082 (Online)

Published By: MECS Press

IJIGSP Vol.14, No.4, Aug. 2022

Eigen and HOG Features based Algorithm for Human Face Tracking in Different Background Challenging Video Sequences

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Author(s)

Ranganatha S, Y P Gowramma

Index Terms

Tracking human face(s), Different background, Video sequences, Eigen features, Corner points, HOG features, Point tracker, Challenging datasets, and Standard metrics.

Abstract

We are proposing a unique novel algorithm for tracking human face(s) in different background video sequences. In the beginning, Eigen features and corner points are extracted from the detected face(s). HOG (Histograms of Oriented Gradients) features are isolated from corner points. Eigen and HOG features are combined together. Using these combined features, point tracker keeps track of the face(s) in the frames of the video sequence. Proposed algorithm is being tested on challenging datasets video sequences with technical challenges such as partial occlusion (e.g. moustache, beard, spectacles, helmet, headscarf etc.), changes in expression, variations in illumination and pose; and measured for performance using standard metrics such as accuracy, precision, recall and specificity. Experimental results clearly indicate the robustness of the proposed algorithm on all different background challenging video sequences.

Cite This Paper

Ranganatha S, Y P Gowramma, "Eigen and HOG Features based Algorithm for Human Face Tracking in Different Background Challenging Video Sequences", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.14, No.4, pp. 70-83, 2022. DOI:10.5815/ijigsp.2022.04.06

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