IEEE Trans Image Process - Low-resolution face tracker robust to illumination variations.

Tópicos

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Resumo

In many practical video surveillance applications, the faces acquired by outdoor cameras are of low resolution and are affected by uncontrolled illumination. Although significant efforts have been made to facilitate face tracking or illumination normalization in unconstrained videos, the approaches developed may not be effective in video surveillance applications. This is because: 1) a low-resolution face contains limited information, and 2) major changes in illumination on a small region of the face make the tracking ineffective. To overcome this problem, this paper proposes to perform tracking in an illumination-insensitive feature space, called the gradient logarithm field (GLF) feature space. The GLF feature mainly depends on the intrinsic characteristics of a face and is only marginally affected by the lighting source. In addition, the GLF feature is a global feature and does not depend on a specific face model, and thus is effective in tracking low-resolution faces. Experimental results show that the proposed GLF-based tracker works well under significant illumination changes and outperforms many state-of-the-art tracking algorithms.

Resumo Limpo

mani practic video surveil applic face acquir outdoor camera low resolut affect uncontrol illumin although signific effort made facilit face track illumin normal unconstrain video approach develop may effect video surveil applic lowresolut face contain limit inform major chang illumin small region face make track ineffect overcom problem paper propos perform track illuminationinsensit featur space call gradient logarithm field glf featur space glf featur main depend intrins characterist face margin affect light sourc addit glf featur global featur depend specif face model thus effect track lowresolut face experiment result show propos glfbase tracker work well signific illumin chang outperform mani stateoftheart track algorithm

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