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3D Active Human Motion Estimation for Biomedical Applications
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics. (Digital Media Lab)
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
2012 (English)In: World Congress on Medical Physics and Biomedical Engineering May 26-31, 2012, Beijing, China / [ed] Mian Long, Springer Berlin/Heidelberg, 2012, , 4 p.1014-1017 p.Conference paper, Published paper (Refereed)
Abstract [en]

Movement disorders forbid many people from enjoying their daily lives. As with other diseases, diagnosis and analysis are key issues in treating such disorders. Computer vision-based motion capture systems are helpful tools for accomplishing this task. However Classical motion tracking systems suffer from several limitations. First they are not cost effective. Second these systems cannot detect minute motions accurately. Finally they are spatially limited to the lab environment where the system is installed. In this project, we propose an innovative solution to solve the above-mentioned issues. Mounting the camera on human body, we build a convenient, low cost motion capture system that can be used by the patient while practicing daily-life activities. We refer to this system as active motion capture, which is not confined to the lab environment. Real-time experiments in our lab revealed the robustness and accuracy of the system.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2012. , 4 p.1014-1017 p.
Series
IFMBE Proceedings, ISSN 1680-0737 ; 39
Keyword [en]
Active motion tracking, Human motion analysis, Movement disorder, SIFT
National Category
Biomedical Laboratory Science/Technology
Identifiers
URN: urn:nbn:se:umu:diva-55831DOI: 10.1007/978-3-642-29305-4_266ISBN: 978-364229304-7 (print) (print)ISBN: 978-3-642-29305-4 (print)OAI: oai:DiVA.org:umu-55831DiVA: diva2:530599
Conference
World Congress on Medical Physics and Biomedical Engineering (WC 2012), Beijing, China, 26-31 May 2012
Available from: 2012-06-04 Created: 2012-06-04 Last updated: 2014-05-21Bibliographically 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
2. Bring Your Body into Action: Body Gesture Detection, Tracking, and Analysis for Natural Interaction
Open this publication in new window or tab >>Bring Your Body into Action: Body Gesture Detection, Tracking, and Analysis for Natural Interaction
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Due to the large influx of computers in our daily lives, human-computer interaction has become crucially important. For a long time, focusing on what users need has been critical for designing interaction methods. However, new perspective tends to extend this attitude to encompass how human desires, interests, and ambitions can be met and supported. This implies that the way we interact with computers should be revisited. Centralizing human values rather than user needs is of the utmost importance for providing new interaction techniques. These values drive our decisions and actions, and are essential to what makes us human. This motivated us to introduce new interaction methods that will support human values, particularly human well-being.

The aim of this thesis is to design new interaction methods that will empower human to have a healthy, intuitive, and pleasurable interaction with tomorrow’s digital world. In order to achieve this aim, this research is concerned with developing theories and techniques for exploring interaction methods beyond keyboard and mouse, utilizing human body. Therefore, this thesis addresses a very fundamental problem, human motion analysis.

Technical contributions of this thesis introduce computer vision-based, marker-less systems to estimate and analyze body motion. The main focus of this research work is on head and hand motion analysis due to the fact that they are the most frequently used body parts for interacting with computers. This thesis gives an insight into the technical challenges and provides new perspectives and robust techniques for solving the problem.

Place, publisher, year, edition, pages
Umeå: Umeå Universitet, 2014. 70 p.
Series
Digital Media Lab, ISSN 1652-6295 ; 19
Keyword
Human Well-Being, Bodily Interaction, Natural Interaction, Human Motion Analysis, Active Motion Estimation, Direct Motion Estimation, Head Pose Estimation, Hand Pose Estimation.
National Category
Signal Processing
Research subject
Signal Processing; Computerized Image Analysis
Identifiers
urn:nbn:se:umu:diva-88508 (URN)978-91-7601-067-9 (ISBN)
Public defence
2014-06-04, Naturvetarhuset, N420, Umeå universitet, Umeå, 13:00 (English)
Opponent
Supervisors
Available from: 2014-05-14 Created: 2014-05-08 Last updated: 2014-05-13Bibliographically approved

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Abedan Kondori, FaridLiu, Li

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