Deformable part-based robust face detection under occlusion by using face decomposition into face components
Darijan Marčetić, Samo Ribarič · 2016
In this paper, we propose modifications of deformable part-based models in order to increase the robustness of face detection under occlusion. The modifications are: i) the tree, representing the deformable part-based model of the frontal face, which is partitioned into 11 subtrees representing face components; ii) the weight of each face component which is obtained based on the results of psychological experiments; iii) the introduction of new scoring functions and thresholds; and iv) a new procedure for robust face detection based on the valuation of scoring functions and thresholds. The experiment was performed only for frontal face images, and thus this work is used only as a proof of concept. Based on the encouraging experimental results, we conclude that the proposed method is suitable for extension to detect faces with different poses under occlusions.