• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.275-280
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• 2013

In this paper, a new stereo object extraction algorithm using a block-based MSE (mean square error) algorithm and the configuration parameters of a stereo camera is proposed. That is, by applying the SSD algorithm between the initial reference image and the next stereo input image, location coordinates of a target object in the right and left images are acquired and then with these values, the pan/tilt system is controlled. And using the moving angle of this pan/tilt system and the configulation parameters of the stereo camera system, the mask window size of a target object is adaptively determined. The newly segmented target image is used as a reference image in the next stage and it is automatically updated in the course of target tracking basing on the same procedure. Meanwhile, a target object is under tracking through continuously controlling the convergence and FOV by using the sequentiall extracted location coordinates of a moving target.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2962-2964
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• 1999

We know the traffic information about the velocity and position of vehicle by extraction and tracking vehicle from continuosly obtained road image of camera. The conventional method of vehicle detection indicate increment of error due to headlight and taillight in night road image. This paper show such as vehicle detection of binary, Edge detection. amalgamation of image are applied to extract the vehicle, and Kalman filter is adaptive methods for tracking position and velocity of vehicle.

• International Journal of Aeronautical and Space Sciences
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• v.10 no.2
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• pp.86-94
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• 2009

This paper deals with the creation of a new, low-cost point/position tracking system that can measure deformations in engineering structures with simple commercially widespread cameras. Though point tracking systems do exist today, such as Stereo Pattern Recognition (SPR) and Projection Moir$\acute{e}$ Interferometry (PMI) systems, they are far too costly to use to analyze small, simple structures because complex optical components such as large flashes, high-resolution cameras and data acquisition systems with several computers are required. We developed a point tracking system using commercial cameras. This system used IR LEDs and commercial IR CCD cameras to minimize the interference posed by other extraneous light sources. The main algorithm used for this system is an optical point tracking algorithm, which is composed of the point extraction algorithm and the point matching algorithm for 3-D motion estimation. a series of verification tests were performed. Then, the developed point tracking system was applied to measure deformations of an acrylic plate under a mechanical load. The measured deformations of the acrylic plate matched well with the numerical analysis results. The results indicate that the developed point tracking system is reliable enough to measure continuous deformed shapes of various engineering structures.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.10 no.2
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• pp.67-80
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• 2006

In this paper, we propose a new pointing device that is replaced a mouse as the pointing device with. For reducing the existing pointing device's problem which had marker and high-cost, we develop a new pointing device using computer vision like as a similar human vision system. The proposed system first carries out a real-time movement tracking system using image data which are segmented by color modeling, and finally does the pointing action by 3-D coordinate calculated from stereo geometry information resulting from stereo matching of the segmented region.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.171-174
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• 2003

In this paper, we propose the method of stereo images composition using adaptive dense disparity estimation. For the correct composition of stereo image and 3D virtual object, we need correct marker position and depth information. The existing algorithms use position information of markers in stereo images for calculating depth of calibration object. But this depth information may be wrong in case of inaccurate marker tracking. Moreover in occlusion region, we can't know depth of 3D object, so we can't composite stereo images and 3D virtual object. In these reasons, the proposed algorithm uses adaptive dense disparity estimation for calculation of depth. The adaptive dense disparity estimation is the algorithm that use pixel-based disparity estimation and the search range is limited around calibration object.

• Journal of Information Display
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• v.3 no.2
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• pp.19-25
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• 2002

In this paper, a new target extraction algorithm is proposed, in which the coordinates of target are obtained adaptively by using the difference image information and the optical BPEJTC(binary phase extraction joint transform correlator) with which the target object can be segmented from the input image and background noises are removed in the stereo vision system. First, the proposed algorithm extracts the target object by removing the background noises through the difference image information of the sequential left images and then controlls the pan/tilt and convergence angle of the stereo camera by using the coordinates of the target position obtained from the optical BPEJTC between the extracted target image and the input image. From some experimental results, it is found that the proposed algorithm can extract the target object from the input image with background noises and then, effectively track the target object in real time. Finally, a possibility of implementation of the adaptive stereo object tracking system by using the proposed algorithm is also suggested.

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

• The Journal of Engineering Research
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• v.6 no.2
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• pp.109-117
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• 2004

In this paper, we propose an object contour tracking algorithm using snakes in stereo image sequences. The proposed technique is composed of two steps. In the first step, the candidate Snake points are determined from the motion information in 3-D disparity space. In the second step, the energy of Snake function is calculated to check whether the candidate Snake points converge to the edges of the interested objects. The energy of Snake function is calculated from the candidate Snake points using the disparity information obtained by patch matching. The performance of the proposed technique is evaluated by applying it to various sample images. Results prove that the proposed technique can track the edges of objects of interest in the stereo image sequences even in the cases of complicated background images or additive components.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.1261-1264
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• 2005

In this paper, a new intelligent moving target tracking and surveillance system basing on the pan/tilt-embedded stereo camera system is suggested and implemented. In the proposed system, once the face area of a target is detected from the input stereo image by using a YCbCr color model and then, using this data as well as the geometric information of the tracking system, the distance and 3D information of the target are effectively extracted in real-time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.1C
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• pp.26-35
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• 2006

In this paper, an automatic mobile robot system for a intelligent path planning using the detection scheme of the spatial coordinates based on stereo camera is proposed. In the proposed system, face area of a moving person is detected from a left image among the stereo image pairs by using the YCbCr color model and its center coordinates are computed by using the centroid method and then using these data, the stereo camera embedded on the mobile robot can be controlled for tracking the moving target in real-time. Moreover, using the disparity map obtained from the left and right images captured by the tracking-controlled stereo camera system and the perspective transformation between a 3-D scene and an image plane, depth information can be detected. Finally, based-on the analysis of these calculated coordinates, a mobile robot system is derived as a intelligent path planning and a estimation. From some experiments on robot driving with 240 frames of the stereo images, it is analyzed that error ratio between the calculated and measured values of the distance between the mobile robot and the objects, and relative distance between the other objects is found to be very low value of $2.19\%$ and $1.52\%$ on average, respectably.