Individual anthropometric measures are important for different applications, such as health care, ergonomics, clothing industry, etc. This data can be extracted automatically from 3D body scans. In this project we develop a body scanner, which outperforms competing approaches in terms of precision, robustness and manageability as well as an additional analysis component. The required hardware for capturing data is reduced to a single camera (Occipital Structure) und a single mobile device (Apple iPad). This project is conducted in cooperation with the „Video Analytics" department of Siemens Austria.
A visual body scanner reconstructs a closed 3D model of a person from different camera views. These views are captured with a camera either with a turning person in front of the camera or a moving camera around the person. Working with a depth camera, current filtering and global non-rigid registration algorithms are applied to transform the captured data into a consistent human body model. Such systems were already developed and published in the past; amongst others also in our department (KinectAvatar). However, these systems have still some limitation concerning precision, level of detail and robustness, so that a practical use is hindered.
The goal of the project is to reduce these limitations by the joint usage of color and depth information and to extend the system with an analyze component for the automatic extraction of anthropometric measures. Ziel dieses Projektes ist es, diese Einschränkungen durch gemeinsame Verwendung von Farb- und Tiefeninformationen zu beseitigen und das System durch Ergänzung einer Analysekomponente zur Extraktion anthropometrischer Maße zu einem kostengünstigen, mobilen, ohne technische Kenntnisse handhabbaren Body Analyzer zu erweitern.
