Estimating Anthropometry and Pose from a Single Uncalibrated Image

Abstract

In this paper, we present a four-step technique for simultaneously estimating a human's anthropometric measurements (up to a scale parameter) and pose from a single uncalibrated image. The user initially selects a set of image points that constitute the projection of selected landmarks. Using this information, along with a priori statistical information about the human body, a set of plausible segment length estimates is produced. In the third step, a set of plausible poses is inferred using a geometric method based on joint limit constraints. In the fourth step, pose and anthropometric measurements are obtained by minimizing an appropriate cost function subject to the associated constraints. The novelty of our approach is the use of anthropometric statistics to constrain the estimation process that allows the simultaneous estimation of both anthropometry and pose. We demonstrate the accuracy, advantages, and limitations of our method for various classes of both synthetic and real input data.