• Journal of Biomedical Engineering Research
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• v.28 no.6
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• pp.744-749
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• 2007

Kinematic and kinetic analysis has been performed for Soft Golf swings utilizing realistic three dimensional computer simulations based on three dimensional motion tracking data. Soft Golf is a newly developed recreational sport in South Korea aimed to become a safe and easy-to-learn sport for all ages. The advantage of Soft Golf stems from lighter weight of the club and much larger area of the sweet spot. This paper tries to look into kinematic and kinetic aspects of soft golf swings compared to regular golf swing and find the advantages of lighter Soft Golf clubs. For this purpose, swing motions of older aged participants were captured and kinematic analysis was performed for various kinematic parameters such as club head velocity, joint angular velocity, and joint range of motions as a pilot study. Kinetic analysis was performed by applying kinematic data to computer simulation models constructed from anthropometric database and the measurements from the participants. The simulations were solved using multi-body dynamics solver. Firstly, the kinematic parameters such as joint angles were obtained by solving inverse dynamics problem based on motion tracking data. Secondly, the kinetic parameters such as joint torques were obtained by solving control dynamics problem of making joint torque to follow pre-defined joint angle data. The results showed that mechanical loadings to major joints were reduced with lighter Soft Golf club.

• Journal of Advanced Navigation Technology
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• v.2 no.2
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• pp.107-115
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• 1998

In this paper, we propose a robust moving object tracking(MOT) method based on motion energy and prediction. MOT consists of two steps: moving object extraction step(MOES) and moving object tracking step(MOTS). For MOES, we use improved motion energy method. For MOTS, we predict the next location of moving object based on distance and direction information among previous instances, so that we can reduce the search space for correspondence. We apply the method to both synthetic and real world sequences and find that the method works well even in the presence of occlusion and disocclusion.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.97-104
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• 2012

Natural User Interface(NUI) technologies introduce new trends in using devices such as computer and any other electronic devices. In this paper, an augmented reality on a mobile device is implemented by using face detection, recognition and motion tracking. The face detection is obtained by using Viola-Jones algorithm from the images of the front camera. The Eigenface algorithm is employed for face recognition and face motion tracking. The augmented reality is implemented by overlapping the rear camera image and GPS, accelerator sensors' data with the 3D graphic object which is correspond with the recognized face. The algorithms and methods are limited by the mobile device specification such as processing ability and main memory capacity.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.9
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• pp.957-963
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• 2014

This paper proposes a predictive control for an efficient human following robot using Kinect sensor. Especially, this research is focused on detecting of foot-end-point and foot-vector instead of human body which can be occluded easily by the obstacles. Recognition of the foot-end-point by the Kinect sensor is reliable since the two feet images can be utilized, which increases the detection possibility of the human motion. Depth image features and a decision tree have been utilized to estimate the foot end-point precisely. A tracking point average algorithm is also adopted in this research to estimate the location of foot accurately. Using the continuous locations of foot, the human motion trajectory is estimated to guide the mobile robot along a smooth path to the human. It is verified through the experiments that detecting foot-end-point is more reliable and efficient than detecting the human body. Finally, the tracking performance of the mobile robot is demonstrated with a human motion along an 'L' shape course.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.1
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• pp.15-23
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• 2020

In this paper, we propose a new method to detect traffic accidents in video from vehicle-mounted cameras (vehicle black box). We use the distance between vehicles to determine whether an accident has occurred. To calculate the position of each vehicle, we use object detection and tracking method. By the way, in a crowded road environment, it is so difficult to decide an accident has occurred because of parked vehicles at the edge of the road. It is not easy to discriminate against accidents from non-accidents because a moving vehicle and a stopped vehicle are mixed on a regular downtown road. In this paper, we try to increase the accuracy of the vehicle accident detection by using not only the motion of the surrounding vehicle but also ego-motion as the input of the Recurrent Neural Network (RNN). We improved the accuracy of accident detection compared to the previous method.

• Journal of Korean Physical Therapy Science
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• v.30 no.4
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• pp.1-8
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• 2023

Background: This study evaluates the usability of the Motion-Tracking Gait Assistive Walker (MTGAW) designed for elderly individuals and those with disabilities, identifying areas for improvement through interviews with physical and occupational therapists. Design: A survey study involves the usability test for MTGAW. Methods: Usability evaluations were conducted with 37 physical therapists and occupational therapists. The process included explanation, product usage, satisfaction surveys, and interviews. A satisfaction survey covering 19 items across safety, maneuverability, usability, and management areas was administered. Individual interviews identified areas for improvement. Results: Overall, high satisfaction was reported across the four areas, but interviews highlighted the need for improvements, such as addressing discomfort due to slow speed and enhancing safety measures to prevent rear-end falls. Adjusting the walker's height and width to suit the user's physique was also suggested. Conclusion: MTGAW enhances walking support and hand movement freedom but needs refinement in speed control, fall prevention, and customization based on the user physique. Future efforts should focus on developing an improved MTGAW, considering recommendations from physical therapy experts, and conducting studies to analyze its clinical effectiveness for commercialization.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.2
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• pp.18-24
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• 2006

This paper proposes a LuGre Model-Based Neural Network (MBNN) friction compensation algorithm for a linear motor stage. For matching the friction phenomena in both the motion-start region and the motion-reverse region, the LuGre dynamic model is employed into the proposed compensation algorithm. After training of the model-based neural network is completed, the estimated friction for compensation is obtained. From the obtained result we find that the new structure gains advantage over the non-friction compensation system on the performance of the compensator in both regions. The proposed compensator is evaluated and compared experimentally with an uncompensated system on a microcomputer controlled linear motor tracking system in the final section of the paper. The experimental results show the improvement on the maximum velocity error and the root mean square tracking error in the motion-start region ranges from 34% to 53% and from 53% to 75% respectively, and in the motion-reverse region from 48% to 65% and from 79% to 90% respectively.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.26 no.1
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• pp.20-29
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• 2017

Motion synchronization between developed real and virtual robots for object recognition and target tracking is introduced. ASUS's XTION PRO Live is implemented as a sensor and configured to recognize walls and obstacles, and perceive objects. In order to create virtual reality, Unity 3D is adopted to be associated with the real robot, and the virtual object is controlled by using an input device. A Bluetooth serial communication module is used for wireless communication between the PC and the real robot. The motion information of a virtual object controlled by the user is sent to the robot. Then, the robot moves in the same way as the virtual object according to the motion information. Through motion synchronization, two scenarios, which map the real space and current object information with virtual objects and space, were demonstrated, yielding good agreement between the two spaces.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.291-294
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• 2004

Semantic video object extraction is important for tracking meaningful objects in video and object-based video coding. We propose a fast semiautomatic video object extraction algorithm which combines a watershed segmentation schemes and chamfer distance transform. Initial object boundaries in the first frame are defined by a human before the tracking, and fast video object tracking can be achieved by tracking only motion-detected regions in a video frame. Experimental results shows that the boundaries of tracking video object arc close to real video object boundaries and the proposed algorithm is promising in terms of speed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1287-1300
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• 2018

Target-tracking algorithm based on ad hoc camera sensor networks (ACSNs) utilizes the distributed observation capability of nodes to achieve accurate target tracking. A compressed sensing-based multiple-target tracking algorithm (CSMTTA) for ACSNs is proposed in this work based on the study of camera node observation projection model and compressed sensing model. The proposed algorithm includes reconfiguration of observed signals and evaluation of target locations. It reconfigures observed signals by solving the convex optimization of L1-norm least and forecasts node group to evaluate a target location by the motion features of the target. Simulation results show that CSMTTA can recover the subtracted observation information accurately under the condition of sparse sampling to a high target-tracking accuracy and accomplish the distributed tracking task of multiple mobile targets.