Rapid Finger Motion Tracking on Low-Power Mobile Environments for Large Screen Interaction

Entertainment Computing – ICEC 2017 - Lecture Notes in Computer Science ◽

10.1007/978-3-319-66715-7_64 ◽

2017 ◽

pp. 465-468

Author(s):

Yeongnam Chae ◽

Daniel Crane

Keyword(s):

Low Power ◽

Motion Tracking ◽

Mobile Environments ◽

Large Screen ◽

Finger Motion

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Selectivity, cycling stability and temperature dependence of touchless finger motion tracking devices based on 1D photonic crystals

10.1117/12.2227431 ◽

2016 ◽

Author(s):

Katalin Szendrei ◽

Pirmin Ganter ◽

Bettina V. Lotsch

Keyword(s):

Photonic Crystals ◽

Temperature Dependence ◽

Motion Tracking ◽

Cycling Stability ◽

Finger Motion ◽

Tracking Devices

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A Low Power Architecture for HASM Motion Tracking

The Journal of VLSI Signal Processing Systems for Signal Image and Video Technology ◽

10.1023/b:vlsi.0000017006.75431.c7 ◽

2004 ◽

Vol 37 (1) ◽

pp. 111-127 ◽

Cited By ~ 1

Author(s):

Wael Badawy ◽

Magdy Bayoumi

Keyword(s):

Low Power ◽

Motion Tracking ◽

Power Architecture

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Algorithm-based low-power VLSI architecture for 2D mesh video-object motion tracking

IEEE Transactions on Circuits and Systems for Video Technology ◽

10.1109/76.999201 ◽

2002 ◽

Vol 12 (4) ◽

pp. 227-237 ◽

Cited By ~ 20

Author(s):

W. Badawy ◽

M. Bayoumi

Keyword(s):

Low Power ◽

Motion Tracking ◽

Vlsi Architecture ◽

Object Motion ◽

Video Object

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A Low-Power Data Driving Method With Enhanced Charge Sharing Technique for Large-Screen LCD TVs

Journal of Display Technology ◽

10.1109/jdt.2015.2392757 ◽

2015 ◽

Vol 11 (4) ◽

pp. 346-352 ◽

Cited By ~ 4

Author(s):

Dong-Un Kim ◽

Jong-Seok Kim ◽

Byong-Deok Choi

Keyword(s):

Low Power ◽

Charge Sharing ◽

Large Screen

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A low power VLSI architecture for mesh-based video motion tracking

IEEE Transactions on Circuits and Systems II Analog and Digital Signal Processing ◽

10.1109/tcsii.2002.805248 ◽

2002 ◽

Vol 49 (7) ◽

pp. 488-504 ◽

Cited By ~ 14

Author(s):

W. Badawy ◽

M.A. Bayoumi

Keyword(s):

Low Power ◽

Motion Tracking ◽

Vlsi Architecture

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Development of a wireless low-power multi-sensor network for motion tracking applications

2013 IEEE International Conference on Body Sensor Networks ◽

10.1109/bsn.2013.6575466 ◽

2013 ◽

Cited By ~ 17

Author(s):

Daniele Comotti ◽

Michele Ermidoro ◽

Michael Galizzi ◽

Andrea Vitali

Keyword(s):

Low Power ◽

Sensor Network ◽

Motion Tracking

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Touchless Optical Finger Motion Tracking Based on 2D Nanosheets with Giant Moisture Responsiveness

Advanced Materials ◽

10.1002/adma.201503463 ◽

2015 ◽

Vol 27 (41) ◽

pp. 6341-6348 ◽

Cited By ~ 52

Author(s):

Katalin Szendrei ◽

Pirmin Ganter ◽

Olalla Sànchez-Sobrado ◽

Roland Eger ◽

Alexander Kuhn ◽

...

Keyword(s):

Motion Tracking ◽

Finger Motion ◽

2D Nanosheets

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Low power VLSI architecture for 2D-mesh video object motion tracking

Proceedings IEEE Computer Society Workshop on VLSI 2000. System Design for a System-on-Chip Era ◽

10.1109/iwv.2000.844532 ◽

2002 ◽

Cited By ~ 2

Author(s):

W. Badawy ◽

M. Bayoumi

Keyword(s):

Low Power ◽

Motion Tracking ◽

Vlsi Architecture ◽

Object Motion ◽

Video Object

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KEY DESIGN PARAMETERS AND SENSOR-FUSION FOR LOW-POWER WEARABLE UWB-BASED MOTION TRACKING AND GAIT ANALYSIS SYSTEMS

Progress In Electromagnetics Research Letters ◽

10.2528/pierl11120303 ◽

2012 ◽

Vol 29 ◽

pp. 115-126 ◽

Cited By ~ 6

Author(s):

Mohamad Abou El-Nasr ◽

Heba A. Shaban ◽

R. Michael Buehrer

Keyword(s):

Low Power ◽

Gait Analysis ◽

Sensor Fusion ◽

Motion Tracking ◽

Design Parameters

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Inertial Sensor Based Solution for Finger Motion Tracking

Computers ◽

10.3390/computers9020040 ◽

2020 ◽

Vol 9 (2) ◽

pp. 40

Author(s):

Stepan Lemak ◽

Viktor Chertopolokhov ◽

Ivan Uvarov ◽

Anna Kruchinina ◽

Margarita Belousova ◽

...

Keyword(s):

Motion Tracking ◽

Inertial Sensor ◽

Complete Information ◽

Recognition Algorithm ◽

Inertial Motion ◽

Hand Motion ◽

Virtual Reconstruction ◽

Finger Tracking ◽

Finger Motion ◽

Finger Model

Hand motion tracking plays an important role in virtual reality systems for immersion and interaction purposes. This paper discusses the problem of finger tracking and proposes the application of the extension of the Madgwick filter and a simple switching (motion recognition) algorithm as a comparison. The proposed algorithms utilize the three-link finger model and provide complete information about the position and orientation of the metacarpus. The numerical experiment shows that this approach is feasible and overcomes some of the major limitations of inertial motion tracking. The paper’s proposed solution was created in order to track a user’s pointing and grasping movements during the interaction with the virtual reconstruction of the cultural heritage of historical cities.

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