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3D Head Pose Estimation Using the Kinect
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
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2011 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Head pose estimation plays an essential role for bridging the information gap between humans and computers. Conventional head pose estimation methods are mostly done in images captured by cameras. However accurate and robust pose estimation is often problematic. In this paper we present an algorithm for recovering the six degrees of freedom (DOF) of motion of a head from a sequence of range images taken by the Microsoft Kinectfor Xbox 360. The proposed algorithm utilizes a least-squares minimization of the difference between themeasured rate of change of depth at a point and the rate predicted by the depth rate constraint equation. We segment the human head from its surroundings and background, and then we estimate the head motion. Our system has the capability to recover the six DOF of the head motion of multiple people in one image. Theproposed system is evaluated in our lab and presents superior results.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2011. 1-4 p.
National Category
Medical Engineering
Identifiers
URN: urn:nbn:se:umu:diva-52815DOI: 10.1109/WCSP.2011.6096866ISBN: 978-1-4577-1008-7 (print)OAI: oai:DiVA.org:umu-52815DiVA: diva2:507238
Conference
IEEE International Conference on Wireless Communications and Signal Processing (WCSP2011), 9-11 nov, TBD, Nanjing, China
Available from: 2012-03-02 Created: 2012-03-02 Last updated: 2012-06-04Bibliographically approved
In thesis
1. Human Motion Analysis for Creating Immersive Experiences
Open this publication in new window or tab >>Human Motion Analysis for Creating Immersive Experiences
2012 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

From an early age, people display the ability to quickly and effortlessly interpret the orientation and movement of human body parts, thereby allowing one to infer the intentions of others who are nearby and to comprehend an important nonverbal form of communication. The ease with which one accomplishes this task belies the difficulty of a problem that has challenged computational systems for decades, human motion analysis.

Technological developments over years have resulted into many systems for measuring body segment positions and angles between segments. In these systems human body is typically considered as a system of rigid links connected by joints. The motion is estimated by the use of measurements from mechanical, optical, magnetic, or inertial trackers. Among all kinds of sensors, optical sensing encompasses a large and varying collection of technologies.

In a computer vision context, human motion analysis is a topic that studies methods and applications in which two or more consecutive images from an image sequences, e.g. captured by a video camera, are processed to produce information based on the apparent human body motion in the images.

Many different disciplines employ motion analysis systems to capture movement and posture of human body for applications such as medical diagnostics, virtual reality, human-computer interaction etc.

This thesis gives an insight into the state of the art human motion analysissystems, and provides new methods for capturing human motion.

Place, publisher, year, edition, pages
Umeå: Umeå University, 2012. 71 p.
Series
Digital Media Lab, ISSN 1652-6295 ; 15
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:umu:diva-55832 (URN)978-91-7459-416-4 (ISBN)
Presentation
2012-04-13, room A305, Department of Applied Physics and Electronics, Umeå University, Umeå, 10:00 (English)
Supervisors
Available from: 2012-06-04 Created: 2012-06-04 Last updated: 2012-06-04Bibliographically approved

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Abedan Kondori, FaridYousefi, ShahrouzLi, HaiboSonning, Samuel

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