Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10360051 | Journal of Visual Communication and Image Representation | 2014 | 14 Pages |
Abstract
Human body detection and pose estimation is useful for a wide variety of applications and environments. Therefore a human body detection and pose estimation system must be adaptable and customizable. This paper presents such a system that extracts skeletons from RGB-D sensor data. The system adapts on-line to difficult unstructured scenes taken from a moving camera (since it does not require background subtraction) and benefits from using both color and depth data. It is customizable by virtue of requiring less training data, having a clearly described training method, and a customizable human kinematic model. Results show successful application to data from a moving camera in cluttered indoor environments. This system is open-source, encouraging reuse, comparison, and future research.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Koen Buys, Cedric Cagniart, Anatoly Baksheev, Tinne De Laet, Joris De Schutter, Caroline Pantofaru,