scholarly journals Expectations and Proposals for the Next Generation Robots. Tracking Vision: A real-time motion tracking system.

1998 ◽  
Vol 16 (1) ◽  
pp. 52-53
Author(s):  
TAKASHI UCHIYAMA
Keyword(s):  
Real Time ◽  
Motion Tracking ◽  
Tracking System ◽  
Next Generation ◽  
Time Motion ◽  
Motion Tracking System

Real-time orthognathic surgical simulation using a mandibular motion tracking system

2007 ◽  
Vol 12 (2) ◽  
pp. 91-104 ◽  
Author(s):  
Kenji Fushima ◽  
Masaru Kobayashi ◽  
Hiroaki Konishi ◽  
Kennichi Minagichi ◽  
Takeshi Fukuchi
Keyword(s):  
Real Time ◽  
Motion Tracking ◽  
Surgical Simulation ◽  
Tracking System ◽  
Motion Tracking System

Real-time orthognathic surgical simulation using a mandibular motion tracking system

2007 ◽  
Vol 12 (2) ◽  
pp. 91-104
Author(s):  
Kenji Fushima ◽  
Masaru Kobayashi ◽  
Hiroaki Konishi ◽  
Kennichi Minagichi ◽  
Takeshi Fukuchi
Keyword(s):  
Real Time ◽  
Motion Tracking ◽  
Surgical Simulation ◽  
Tracking System ◽  
Motion Tracking System

scholarly journals An IoT-Based Motion Tracking System for Next-Generation Foot-Related Sports Training and Talent Selection

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Shanshan Lu ◽  
Xiao Zhang ◽  
Jiangqing Wang ◽  
Yufan Wang ◽  
Mengjiao Fan ◽  
...  
Keyword(s):  
Motion Tracking ◽  
Microelectromechanical Systems ◽  
Intelligent System ◽  
Tracking System ◽  
Selection Function ◽  
Next Generation ◽  
Sports Training ◽  
Analysis Model ◽  
Talent Selection ◽  
Motion Tracking System

Motion tracking in different fields (medical, military, film, etc.) based on microelectromechanical systems (MEMS) sensing technology has been attracted by world's leading researchers and engineers in recent years; however, there is still a lack of research covering the sports field. In this study, we propose a new AIoT (AI + IoT) paradigm for next-generation foot-driven sports (soccer, football, takraw, etc.) training and talent selection. The system built is cost-effective and easy-to-use and requires much fewer computational resources than traditional video-based analysis on monitoring motions of players during training. The system built includes a customized wireless wearable sensing device (WWSDs), a mobile application, and a data processing interface-based cloud with an ankle attitude angle analysis model. Eleven right-foot male participators wore the WWSD on their ankle while each performed 20 instances of different actions in a formal soccer field. The experimental outcome demonstrates the proposed motion tracking system based on AIoT and MEMS sensing technologies capable of recognizing different motions and assessing the players’ skills. The talent selection function can partition the elite and amateur players at an accuracy of 93%. This intelligent system can be an emerging technology based on wearable sensors and attain the experience-driven to data-driven transition in the field of sports training and talent selection and can be easily extended to analyze other foot-related sports motions (e.g., taekwondo, tumble, and gymnastics) and skill levels.

Real-time awake animal motion tracking system for SPECT imaging

2008 ◽  
Author(s):  
J. S. Goddard ◽  
J. S. Baba ◽  
S. J. Lee ◽  
A. G. Weisenberger ◽  
A. Stolin ◽  
...  
Keyword(s):  
Real Time ◽  
Motion Tracking ◽  
Tracking System ◽  
Spect Imaging ◽  
Time Awake ◽  
Motion Tracking System ◽  
Awake Animal

Use of a real-time three-dimensional motion tracking system for measurement of intrafractional motion of the thoracic wall in dogs

2013 ◽  
Vol 74 (1) ◽  
pp. 11-16 ◽  
Author(s):  
Monique N. Mayer ◽  
Joel L. Lanovaz ◽  
Michael J. Smith ◽  
Narinder Sidhu ◽  
Cheryl L. Waldner
Keyword(s):  
Real Time ◽  
Motion Tracking ◽  
Tracking System ◽  
Three Dimensional ◽  
Thoracic Wall ◽  
Intrafractional Motion ◽  
Motion Tracking System

UNSUPERVISED MARKERLESS 3-DOF MOTION TRACKING IN REAL TIME USING A SINGLE LOW-BUDGET CAMERA

2012 ◽  
Vol 22 (05) ◽  
pp. 1250019 ◽  
Author(s):  
LUIS QUESADA ◽  
ALEJANDRO J. LEÓN
Keyword(s):  
Real Time ◽  
Degrees Of Freedom ◽  
Motion Tracking ◽  
Tracking System ◽  
Three Dimensional ◽  
Target Object ◽  
Commercial Applications ◽  
Amount Of Knowledge ◽  
Partially Occluded ◽  
Motion Tracking System

Motion tracking is a critical task in many computer vision applications. Existing motion tracking techniques require either a great amount of knowledge on the target object or specific hardware. These requirements discourage the wide spread of commercial applications based on motion tracking. In this paper, we present a novel three degrees of freedom motion tracking system that needs no knowledge on the target object and that only requires a single low-budget camera that can be found installed in most computers and smartphones. Our system estimates, in real time, the three-dimensional position of a nonmodeled unmarked object that may be nonrigid, nonconvex, partially occluded, self-occluded, or motion blurred, given that it is opaque, evenly colored, enough contrasting with the background in each frame, and that it does not rotate. Our system is also able to determine the most relevant object to track in the screen. Our proposal does not impose additional constraints, therefore it allows a market-wide implementation of applications that require the estimation of the three position degrees of freedom of an object.

A Human Half-Top Kinematic Motion Tracking System Based on Disparity Information of Stereo Camera

2012 ◽  
Vol 605-607 ◽  
pp. 1391-1394
Author(s):  
Youngouk Kim ◽  
Sewoong Jun
Keyword(s):  
Real Time ◽  
Motion Tracking ◽  
Tracking System ◽  
Main Idea ◽  
Human Model ◽  
Disparity Map ◽  
Real Time System ◽  
Stereo Camera ◽  
Articulated Objects ◽  
Motion Tracking System

This paper presents a new real-time system to acquire motion information of human articulated objects such as arm and head. The system does not need any marker or device to wear on human body and adopted stereo camera to obtain robust system against for illumination and complex background without position initialization of articulated objects. We present a solution to estimate self-occluded body objects when human model behaves normal action towards the camera. The main idea of the solution is to apply a component labeling techniques on sliced disparity map, and found the arm position when the arm is located in front of basis distance of body and we could also found arm location when the arm is located on the basis distance with Morphological methods. From this approach, we can obtain the full body shape considering self-occlusion. It is simple and fast in comparison with other methods which satisfy real-time performance and accuracy of object tracking at the same time.

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