A Direct Method for 3D Hand Pose Recovery
2014 (English)In: 22nd International Conference on Pattern Recognition, 2014, 345-350 p.Conference paper (Refereed)
This paper presents a novel approach for performing intuitive 3D gesture-based interaction using depth data acquired by Kinect. Unlike current depth-based systems that focus only on classical gesture recognition problem, we also consider 3D gesture pose estimation for creating immersive gestural interaction. In this paper, we formulate gesture-based interaction system as a combination of two separate problems, gesture recognition and gesture pose estimation. We focus on the second problem and propose a direct method for recovering hand motion parameters. Based on the range images, a new version of optical flow constraint equation is derived, which can be utilized to directly estimate 3D hand motion without any need of imposing other constraints. Our experiments illustrate that the proposed approach performs properly in real-time with high accuracy. As a proof of concept, we demonstrate the system performance in 3D object manipulation. This application is intended to explore the system capabilities in real-time biomedical applications. Eventually, system usability test is conducted to evaluate the learnability, user experience and interaction quality in 3D interaction in comparison to 2D touch-screen interaction.
Place, publisher, year, edition, pages
2014. 345-350 p.
, International Conference on Pattern Recognition, ISSN 1051-4651
Other Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:umu:diva-108475DOI: 10.1109/ICPR.2014.68ISI: 000359818000057ISBN: 978-1-4799-5208-3OAI: oai:DiVA.org:umu-108475DiVA: diva2:853542
22ND International Conference on Pattern Recognition (ICPR, 24–28 August 2014, Stockholm, Sweden