Towards Automatic Human Body Model Fitting to a 3D Scan

This paper presents a method to automatically recover a realistic and accurate body shape of a
person wearing clothing from a 3D scan. Indeed, in many practical situations, people are scanned
wearing clothing. The underlying body shape is thus partially or completely occluded. Yet, it is very
desirable to recover the shape of a covered body as it provides non-invasive means of measuring and
analysing it. This is particularly convenient for patients in medical applications, customers in a retail
shop, as well as in security applications where suspicious objects under clothing are to be detected.
To recover the body shape from the 3D scan of a person in any pose, a human body model is usually
fitted to the scan. Current methods rely on the manual placement of markers on the body to identify
anatomical locations and guide the pose fitting. The markers are either physically placed on the body
before scanning or placed in software as a postprocessing step. Some other methods detect key
points on the scan using 3D feature descriptors to automate the placement of markers. They usually
require a large database of 3D scans. We propose to automatically estimate the body pose of a
person from a 3D mesh acquired by standard 3D body scanners, with or without texture. To fit a
human model to the scan, we use joint locations as anchors. These are detected from multiple 2D
views using a conventional body joint detector working on images. In contrast to existing approaches,
the proposed method is fully automatic, and takes advantage of the robustness of state-of-art 2D joint
detectors. The proposed approach is validated on scans of people in different poses wearing
garments of various thicknesses and on scans of one person in multiple poses with known ground
truth wearing close-fitting clothing.