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Real 3D Interaction Behind Mobile Phones for Augmented Environments
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.
2011 (English)In: 2011 IEEE International Conference on Multimedia and Expo (ICME), IEEE conference proceedings, 2011, 1-6 p.Conference paper, Published paper (Refereed)
Abstract [en]

Number of mobile devices such as mobile phones or PDAs has been dramatically increased over the recent years. New mobile devices are equipped with integrated cameras and large displays which make the interaction with 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. This paper suggests the use of particular patterns from local orientation of the image called Rotational Symmetries to detect and localize human gesture. Relative rotation and translation of human gesture between consecutive frames are estimated by means of extracting stable features. Consequently, this information can be used to facilitate the 3D manipulation of virtual objects in various applications in mobile devices.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2011. 1-6 p.
Series
IEEE International Conference on Multimedia and Expo, ISSN 1945-7871
Keyword [en]
Mobile interaction, rotational symmetries, SIFT, 3D manipulation
National Category
Interaction Technologies
Identifiers
URN: urn:nbn:se:umu:diva-52816DOI: 10.1109/ICME.2011.6012155ISI: 000304354700154ISBN: 978-1-61284-349-0 (print)OAI: oai:DiVA.org:umu-52816DiVA: diva2:507239
Conference
Multimedia and Expo (ICME), 2011 IEEE International Conference on, Barcelona, Spain, July 11-15, 2011
Available from: 2012-03-02 Created: 2012-03-02 Last updated: 2017-01-16Bibliographically 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, FaridYousefi, ShahrouzLi, Haibo
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