• Proceedings of the KSME Conference
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• 2003.04a
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• pp.479-484
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• 2003

A non-contact 6D motion tracking system is proposed. The system consists of two color cameras, a color image grabber and a host computer, Motions of a floating vessel was measured by the constructed system. The instantaneous forces of the floating vessel are analyzed. The floating vessel was put on the water in a small water container in free conditions. The measured forces are reconstructed by the measurement results. The system can be used to non-contact measurements for 6D dynamic analysis of floating vessels.

• Journal of Korea Multimedia Society
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• v.10 no.6
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• pp.716-725
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• 2007

In this paper we describe a motion tracking algorithm for 3D human animation using stereo vision system. This allows us to extract the motion data of the end effectors of human body by following the movement through segmentation process in HIS or RGB color model, and then blob analysis is used to detect robust shape. When two hands or two foots are crossed at any position and become disjointed, an adaptive algorithm is presented to recognize whether it is left or right one. And the real motion is the 3-D coordinate motion. A mono image data is a data of 2D coordinate. This data doesn't acquire distance from a camera. By stereo vision like human vision, we can acquire a data of 3D motion such as left, right motion from bottom and distance of objects from camera. This requests a depth value including x axis and y axis coordinate in mono image for transforming 3D coordinate. This depth value(z axis) is calculated by disparity of stereo vision by using only end-effectors of images. The position of the inner joints is calculated and 3D character can be visualized using inverse kinematics.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.1574-1579
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• 2004

A simultaneous measurement system that can analyze the flow-structure interactions(FSI) has been constructed and analyses on the flow field and the motion field of a floating cylinder was made. The three-dimensional vector fields around the cylinder are measured by 3D-PTV technique while the motion of the cylinder forced by the flow field is measured simultaneously with a newly developed motion tracking algorithm(bidirectional tracking algorithm). The cylinder is pendant in the working fluid of a water channel and the surface of the working fluid is forced sinusoidal to make the cylinder bounced. The interaction between the flow fields and the cylinder motion is examined quantitatively.

• Journal of Broadcast Engineering
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• v.11 no.4 s.33
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• pp.533-540
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• 2006

In this study we propose to use a facial motion capture technique to track facial motions and expressions effectively by using the stereo vision module, which has two CMOS IMAGE SENSORS. In the proposed tracking algorithm, a center point tracking technique and correlation tracking technique, based on neural networks, were used. Experimental results show that the two tracking techniques using stereo vision motion capture are able to track general face expressions at a 95.6% and 99.6% success rate, for 15 frames and 30 frames, respectively. However, the tracking success rates(82.7%,99.1%) of the center point tracking technique was far higher than those(78.7%,92.7%) of the correlation tracking technique, when lips trembled.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.6
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• pp.605-612
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• 2015

Three dimensional (3D) position determination and motion recognition using a 3D depth sensor camera are applied to a developed penguin-shaped robot, and its validity and closeness are investigated. The robot is equipped with an Asus Xtion Pro Live as a 3D depth camera, and a sound module. Using the skeleton information from the motion recognition data extracted from the camera, the robot is controlled so as to follow the typical three mode-reactions formed by the operator's gestures. In this study, the extraction of skeleton joint information using the 3D depth camera is introduced, and the tracking performance of the operator's motions is explained.

• Journal of Information Display
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• v.6 no.4
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• pp.16-25
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• 2005

In this paper, a new 3D object tracking system using the disparity motion vector (DMV) is presented. In the proposed method, the time-sequential disparity maps are extracted from the sequence of the stereo input image pairs and these disparity maps are used to sequentially estimate the DMV defined as a disparity difference between two consecutive disparity maps Similarly to motion vectors in the conventional video signals, the DMV provides us with motion information of a moving target by showing a relatively large change in the disparity values in the target areas. Accordingly, this DMV helps detect the target area and its location coordinates. Based on these location data of a moving target, the pan/tilt embedded in the stereo camera system can be controlled and consequently achieve real-time stereo tracking of a moving target. From the results of experiments with 9 frames of the stereo image pairs having 256x256 pixels, it is shown that the proposed DMV-based stereo object tracking system can track the moving target with a relatively low error ratio of about 3.05 % on average.

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.657-664
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• 2003

Reliable tracking of moving humans is essential to motion estimation, video surveillance and human-computer interface. This paper presents a new approach to human motion tracking that combines appearance-based and model-based techniques. Monocular color video is processed at both pixel level and object level. At the pixel level, a Gaussian mixture model is used to train and classily individual pixel colors. At the object level, a 3D human body model projected on a 2D image plane is used to fit the image data. Our method does not use inverse kinematics due to the singularity problem. While many others use stochastic sampling for model-based motion tracking, our method is purely dependent on nonlinear programming. We convert the human motion tracking problem into a nonlinear programming problem. A cost function for parameter optimization is used to estimate the degree of the overlapping between the foreground input image silhouette and a projected 3D model body silhouette. The overlapping is computed using computational geometry by converting a set of pixels from the image domain to a polygon in the real projection plane domain. Our method is used to recognize various human motions. Motion tracking results from video sequences are very encouraging.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.6
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• pp.355-365
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• 2022

This paper addresses the problem of real-time tracking a high-speed ballistic target. Particle filters can be considered to overcome the nonlinearity in motion and measurement models in the ballistic target. However, it is difficult to apply particle filters to real-time systems because particle filters generally require much computation time. This paper proposes an accelerated particle filter using graphics processing unit (GPU) for real-time ballistic target tracking. The real-time performance of the proposed method was tested and analyzed on a widely-used embedded system. The comparison results with the conventional particle filter on CPU (central processing unit) showed that the proposed method improved the real-time performance by reducing computation time significantly.

• Clinics in Shoulder and Elbow
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• v.26 no.2
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• pp.126-130
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• 2023

Background: Arm swing plays a role in gait by accommodating forward movement through trunk balance. This study evaluates the biomechanical characteristics of arm swing during gait. Methods: The study performed computational musculoskeletal modeling based on motion tracking in 15 participants without musculoskeletal or gait disorder. A three-dimensional (3D) motion tracking system using three Azure Kinect (Microsoft) modules was used to obtain information in the 3D location of shoulder and elbow joints. Computational modeling using AnyBody Modeling System was performed to calculate the joint moment and range of motion (ROM) during arm swing. Results: Mean ROM of the dominant elbow was 29.7°±10.2° and 14.2°±3.2° in flexion-extension and pronation-supination, respectively. Mean joint moment of the dominant elbow was 56.4±12.7 Nm, 25.6±5.2 Nm, and 19.8±4.6 Nm in flexion-extension, rotation, and abduction-adduction, respectively. Conclusions: The elbow bears the load created by gravity and muscle contracture in dynamic arm swing movement.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.61.6-61
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• 2001

In this paper, we propose a method to analyze measured data from 3D Laser tracking system and to enhance precision performance of a Cartesian robot. Position data are obtained over the stroke of a Cartesian robot with variable speeds. The measured data is need to model errors with several different sources. In general, the error is a function of part accuracy, assembly accuracy, temperature, and control etc. After the sources of errors are identified, they are used to enhance precision performance. The proposed method is more complete than others because we use very accurate 3D Laser tracking system.