• Journal of the Ergonomics Society of Korea
• /
• v.19 no.1
• /
• pp.77-90
• /
• 2000

The aim of this study is to develop and evaluate an efficient camera calibration method for vision-based head tracking. Tracking head movements is important in the design of an eye-controlled human/computer interface. A vision-based head tracking system was proposed to allow the user's head movements in the design of the eye-controlled human/computer interface. We proposed an efficient camera calibration method to track the 3D position and orientation of the user's head accurately. We also evaluated the performance of the proposed method. The experimental error analysis results showed that the proposed method can provide more accurate and stable pose (i.e. position and orientation) of the camera than the conventional direct linear transformation method which has been used in camera calibration. The results of this study can be applied to the tracking head movements related to the eye-controlled human/computer interface and the virtual reality technology.

• International Journal of Advanced Culture Technology
• /
• v.7 no.4
• /
• pp.302-307
• /
• 2019

In this paper, we propose an efficient method for AR toolkit Vuforia. In order to increase the scan rate when using the 3D object scanner, the scan rate parameters need to be analyzed in terms of the angle and distance. In addition, in order to increase the tracking rate when tracking an object, the tracking rate has to be evaluated according to the position, complexity, and contrast of the object. To this end, we have defined the difference of scan rate according to angle and distance between camera and object when using object scanner and the recognition time according to object's position, complexity and contrast when tracking object.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.9 no.4
• /
• pp.114-119
• /
• 2006

Data post-processing programs are used for analysis and visualization of the data obtained from computational fluid methods or flow field experiments. In this paper 3D data visualization system which combines a data visualization program with position tracking system using stereo cameras is introduced. This system offers virtual environment for visualization and analysis of three dimensional data.

• Journal of International Society for Simulation Surgery
• /
• v.2 no.1
• /
• pp.17-25
• /
• 2015

Purpose In this paper, we propose a robust 3D vessel tracking algorithm by utilizing an active contour model and unscented Kalman filter which are the two representative algorithms on segmentation and tracking. Materials and Methods The proposed algorithm firstly accepts user input to produce an initial estimate of vessel boundary segmentation. On each Computed Tomography Angiography (CTA) slice, the active contour is applied to segment the vessel boundary. After that, the estimation process of the unscented Kalman filter is applied to track the vessel boundary of the current slice to estimate the inter-slice vessel position translation and shape deformation. Finally both active contour and unscented Kalman filter are inter-operated for vessel segmentation of the next slice. Results The arbitrarily shaped blood vessel boundary on each slice is segmented by using the active contour model, and the Kalman filter is employed to track the translation and shape deformation between CTA slices. The proposed algorithm is applied to the 3D visualization of chest CTA images using graphics hardware. Conclusion Through this algorithm, more opportunities, giving quick and brief diagnosis, could be provided for the radiologist before detailed diagnosis using 2D CTA slices, Also, for the surgeon, the algorithm could be used for surgical planning, simulation, navigation and rehearsal, and is expected to be applied to highly valuable applications for more accurate 3D vessel tracking and rendering.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.8
• /
• pp.3136-3150
• /
• 2015

A vision-based 3D tracking of articulated human hand is one of the major issues in the applications of human computer interactions and understanding the control of robot hand. This paper presents an improved approach for tracking and recovering the 3D position and orientation of a human hand using the Kinect sensor. The basic idea of the proposed method is to solve an optimization problem that minimizes the discrepancy in 3D shape between an actual hand observed by Kinect and a hypothesized 3D hand model. Since each of the 3D hand pose has 23 degrees of freedom, the hand articulation tracking needs computational excessive burden in minimizing the 3D shape discrepancy between an observed hand and a 3D hand model. For this, we first created a 3D hand model which represents the hand with 17 different parts. Secondly, Random Forest classifier was trained on the synthetic depth images generated by animating the developed 3D hand model, which was then used for Haar-like feature-based classification rather than performing per-pixel classification. Classification results were used for estimating the joint positions for the hand skeleton. Through the experiment, we were able to prove that the proposed method showed improvement rates in hand part recognition and a performance of 20-30 fps. The results confirmed its practical use in classifying hand area and successfully tracked and recovered the 3D hand pose in a real time fashion.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.1
• /
• pp.89-101
• /
• 2015

This paper proposes a statistical model of 3-D positions when tracking moving targets using the uncooled infrared (IR) stereo camera system. The proposed model is derived from two errors. One is the position error which is caused by the sampling pixels in the digital image. The other is the timing jitter which results from the irregular capture-timing in the infrared cameras. The capture-timing in the IR camera is measured using the jitter meter designed in this paper, and the observed jitters are statistically modeled as Gaussian distribution. This paper derives an integrated probability distribution by combining jitter error with pixel position error. The combined error is modeled as the convolution of two error distributions. To verify the proposed statistical position error model, this paper has some experiments in tracking moving objects with IR stereo camera. The 3-D positions of object are accurately measured by the trajectory scanner, and 3-D positions are also estimated by stereo matching from IR stereo camera system. According to the experiments, the positions of moving object are estimated within the statistically reliable range which is derived by convolution of two probability models of pixel position error and timing jitter respectively. It is expected that the proposed statistical model can be applied to estimate the uncertain 3-D positions of moving objects in the diverse fields.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.35 no.2
• /
• pp.128-133
• /
• 2015

This paper describes the construction of a static 3D ultrasonography image by tracking the radiation beam position during the handy operation of a 1D array probe to enable point-of-care use. The theoretical model of the transformation from the translational and rotational information of the sensor mounted on the probe to the reference Cartesian coordinate system was given. The signal amplification and serial communication interface module was made using a commercially available sensor. A test phantom was also made using silicone putty in a donut shape. During the movement of the hand-held probe, B-mode movie and sensor signals were recorded. B-mode images were periodically selected from the movie, and the gray levels of the pixels for each image were converted to the gray levels of 3D voxels. 3D and 2D images of arbitrary cross-section of the B-mode type were also constructed from the voxel data, and agreed well with the shape of the test phantom.

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

• Proceedings of the IEEK Conference
• /
• 2006.06a
• /
• pp.1003-1004
• /
• 2006

In this paper we extract the position value of the tracking object using the hierarchical optic-digital algorithm and to control the main visual angle and Pan/Tilt. And then we propose the optic-digital stereo object tracking system for adaptive extracting the moving-target.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2012.05a
• /
• pp.133-136
• /
• 2012

In this paper, we found the many effective ways and apply for improve the 3D quality of Autostereoscopic 3D display products. Autostereoscopic products compared to traditional 3D glasses, the disadvantage is the poor depth of 3D picture quality and it only can see the fixed distance and position. So, for the compensate this disadvantage, we use the Head tracking technology and video placement algorithms and several techniques. In this paper, the will report on how to improve the Parallax Barrier Autostereoscopic 3D quality through the Head tracking of the user identification, video replacement algorithms and crosstalk improving method.