Illumination-Invariant Robust Multiview 3D Human Motion Capture

Nadia Robertini, Florian Bernard, Weipeng Xu, Christian Theobalt

Abstract: In this work we address the problem of capturing human body motion under changing lighting conditions in a multiview setup. In order to account for changing lighting conditions we propose to use an intermediate image representation that is invariant to the scene lighting. In our approach this is achieved by solving time-varying segmentation problems that use frame- and view-dependent appearance costs that are able to adjust to the present conditions. Moreover, we use an adaptive combination of our lighting-invariant segmentation with CNN-based joint detectors in order to increase the robustness to segmentation errors. In our experimental validation we demonstrate that our method is able to handle difficult conditions better than existing works.