Unsupervised Pose Estimation via Inverse Graphics

Abstract

We introduce a method for pose estimation from sensor array data utilizing an inverse graphics approach. We propose a general unsupervised method based on manipulating a 3D model to discover the joint-space parameters that produce an observed image or sensor reading. Using our novel architecture, we discuss the design of a model for performing human pose estimation on data obtained from a mattress pressure sensor.