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Direct three-dimensional head pose estimation from Kinect-type sensors
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.
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
2014 (English)In: Electronics Letters, ISSN 0013-5194, E-ISSN 1350-911X, Vol. 50, no 4, 268-270 p.Article in journal, Letter (Refereed) Published
Abstract [en]

A direct method for recovering three-dimensional (3D) head motion parameters from a sequence of range images acquired by Kinect sensors is presented. Based on the range images, a new version of the optical flow constraint equation is derived, which can be used to directly estimate 3D motion parameters without any need of imposing other constraints. Since all calculations with the new constraint equation are based on the range images, Z(xyt), the existing techniques and experiences developed and accumulated on the topic of motion from optical flow can be directly applied simply by treating the range images as normal intensity images I(xyt). In this reported work, it is demonstrated how to employ the new optical flow constraint equation to recover the 3D motion of a moving head from the sequences of range images, and furthermore, how to use an old trick to handle the case when the optical flow is large. It is shown, in the end, that the performance of the proposed approach is comparable with that of some of the state-of-the-art approaches that use range data to recover 3D motion parameters.

Place, publisher, year, edition, pages
2014. Vol. 50, no 4, 268-270 p.
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:umu:diva-86584DOI: 10.1049/el.2013.2489ISI: 000331405200019OAI: oai:DiVA.org:umu-86584DiVA: diva2:703472
Available from: 2014-03-06 Created: 2014-03-02 Last updated: 2017-12-05Bibliographically approved
In thesis
1. 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, FaridYousefi, ShahrouzLi, Haibo
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