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Camera-based gesture tracking for 3D interaction behind mobile devices
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.
2012 (English)In: International journal of pattern recognition and artificial intelligence, ISSN 0218-0014, Vol. 26, no 8, 1260008- p.Article in journal (Refereed) Published
Abstract [en]

Number of mobile devices such as Smartphones or Tablet PCs has been dramatically increased over the recent years. New mobile devices are equipped with integrated cameras and large displays that make the interaction with the device easier and more efficient. Although most of the previous works on interaction between humans and mobile devices are based on 2D touch-screen displays, camera-based interaction opens a new way to manipulate in 3D space behind the device in the camera's field of view. In this paper, our gestural interaction relies on particular patterns from local orientation of the image called rotational symmetries. This approach is based on finding the most suitable pattern from a large set of rotational symmetries of diffrerent orders that ensures a reliable detector for fingertips and user's gesture. Consequently, gesture detection and tracking can be used as an efficient tool for 3D manipulation in various virtual/augmented reality applications.

Place, publisher, year, edition, pages
2012. Vol. 26, no 8, 1260008- p.
Keyword [en]
3D mobile interaction, rotational symmetries, gesture detection, tracking, mobile applications
National Category
Human Computer Interaction
Identifiers
URN: urn:nbn:se:umu:diva-67979DOI: 10.1142/S0218001412600087ISI: 000315523100006OAI: oai:DiVA.org:umu-67979DiVA: diva2:615231
Available from: 2013-04-09 Created: 2013-04-09 Last updated: 2017-12-06Bibliographically 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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