A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Corner-Finding Algorithm for Chain-Coded Curves
IEEE Transactions on Computers
Automated anthropometric data collection using 3D whole body scanners
Expert Systems with Applications: An International Journal
3D body reconstruction from photos based on range scan
Edutainment'06 Proceedings of the First international conference on Technologies for E-Learning and Digital Entertainment
Constructing 3D human model from front and side images
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
Extracting human body features automatically from 2D images provides a fast and easy approach to collect anthropometric data. This paper presents a systematic method to detect feature points on the silhouette of human body from the front and side images. With an efficient shape coding algorithm, the human body contour of the binary images can be represented. By evaluating the difference between the coding sequence, feature points can be identified. Hence, a total of 60 feature points can be extracted automatically. The method has been tested on 30 human subjects and all the feature points can be correctly extracted. In order to evaluate the performance of the automatic body feature extraction system, the feature points obtained from the proposed method were validated by analyzing the location variation of the silhouette curve. The experimental results indicate that the system is very effective and robust. Moreover, the extracted feature points can be subsequently processed for body dimension measurements. Thus, the newly developed system can achieve an automated extraction of body features and to obtain anthropometric data for many applications.