Abstract

In this work, we address the problem of 3D pose estima-tion of multiple humans from multiple views. This is a morechallenging problem than single human 3D pose estimationdue to the much larger state space, partial occlusions aswell as across view ambiguities when not knowing the identity of the humans in advance. To address these problems,we first create a reduced state space by triangulation ofcorresponding body joints obtained from part detectors inpairs of camera views. In order to resolve the ambiguitiesof wrong and mixed body parts of multiple humans after tri-angulation and also those coming from false positive bodypart detections, we introduce a novel 3D pictorial structures(3DPS) model. Our model infers 3D human body configurations from our reduced state space. The 3DPS model isgeneric and applicable to both single and multiple human pose estimation. In order to compare to the state-of-the art, we first eval-uate our method on single human 3D pose estimation onHumanEva-I [22] and KTH Multiview Football Dataset II [8] datasets. Then, we introduce and evaluate our method on two datasets for multiple human 3D pose estimation.