• 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.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.12
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• pp.651-658
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• 2000

This paper presents a new method to extract traffic information such as number of passing vehicles and average speed by a pair of stereo road images. The whole process consists of the extraction of vehicles and the tracking of the extracted vehicles. For the extraction of vehicles, the outline of each vehicle is obtained by using binary region growing technique applied to disparity map based on multi-resolution stereo matching. The Kalman filter tracking algorithm is applied to the extracted vehicle outlines to determine the flow of vehicles. Experimental results show that the proposed method significantly improved recognition rate of vehicles over the conventional methods-frame difference and background elimination methods.

• 한국정보디스플레이학회:학술대회논문집
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• 2000.01a
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• pp.79-80
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• 2000

General stereo vision system shows things in 3D, using two visions of left and right side. When the viewpoints of left/right sides are not in accord with each other, it gives fatigue to human eyes and prevents them from having the 3-D feeling. Also, it would be difficult to track mobile objects that are not in the middle of a screen. Therefore, the object tracking function of stereo vision system is to control tracking objects to always be in the middle of a screen while controlling convergence angles of mobile objects in the input image of the left/right cameras. In this paper, object-tracker in stereo vision system is presented which would track mobile objects by using block matching algorithm of preprocessing and JTC.

• Journal of Sensor Science and Technology
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• v.33 no.2
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• pp.98-104
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• 2024

This study proposes a method to overcome the limited detection range of short-baseline stereo cameras (SBSCs). The proposed method includes two steps: (1) predicting an unscaled initial depth using monocular depth estimation (MDE) and (2) adjusting the unscaled initial depth by a scale factor. The scale factor is computed by triangulating the sparse visual keypoints extracted from the left and right images of the SBSC. The proposed method allows the use of any pre-trained MDE model without the need for additional training or data collection, making it efficient even when considering the computational constraints of small platforms. Using an open dataset, the performance of the proposed method was demonstrated by comparing it with other conventional stereo-based depth estimation methods.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.3
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• pp.74-83
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• 1997

In this paper, a new stereo matching algorithm is proposed which uses th econstrainted optimization technique and the matching measures between the segments extracted from zero-crossing edges. The initial matching measures and average disparities are calculated by the features of segments on the searching window of the left and right images. The matching measure is calculated by applying an exponential function using the differences of slope, overlapped length and intensity. The coherency constraint is that neighbouring image points corresponding to the same object should have nearly the same disparities. The matching measures are iteratively updated by applying the coherency constraint. Simulation results on various images show that the proposed algorithm more acculately extracts the segment disparity.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.414-417
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• 1993

The methods for stereo matching are divided into two techniques: area-based matching and feature-based matching. To find corresponding points by area-based method, it takes a lot of time because there are many points to be matched. Feature-based matching algorithm is often used because with this method it matches only some feature points so that the processing time is fast even though it requires interpolation after matching. In this paper, we propose the smart technique by which we makes features simpler than conventional methods to match an image pair by feature-based matching algorithm.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.437-438
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• 2006

Virtual view synthesis is essential for 3DTV systems, which utilizes the motion parallax cue. In this paper, we propose a multi-step view synthesis algorithm to efficiently reconstruct an arbitrary view from limited number of known views of a 3D scene. We describe an efficient image rectification procedure which guarantees that an interpolation process produce valid views. This rectification method can deal with all possible camera motions. The idea consists of using a polar parameterization of the image around the epipole. Then, to generate intermediate views, we use an efficient dense disparity estimation algorithm considering features of stereo image pairs. Main concepts of the algorithm are based on the region dividing bidirectional pixel matching. The estimated disparities are used to synthesize intermediate view of stereo images. We use computer simulation to show the result of the proposed algorithm.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.3
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• pp.175-182
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• 2017

In this paper, we present a multi-depth generation method using a time-of-flight (ToF) fusion camera system. Multi-view color cameras in the parallel type and ToF depth sensors are used for 3D scene capturing. Although each ToF depth sensor can measure the depth information of the scene in real-time, it has several problems to overcome. Therefore, after we capture low-resolution depth images by ToF depth sensors, we perform a post-processing to solve the problems. Then, the depth information of the depth sensor is warped to color image positions and used as initial disparity values. In addition, the warped depth data is used to generate a depth-discontinuity map for efficient stereo matching. By applying the stereo matching using belief propagation with the depth-discontinuity map and the initial disparity information, we have obtained more accurate and stable multi-view disparity maps in reduced time.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.1558-1563
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• 2004

A measurement technique for the void fraction and the bubble dynamics in gas-liquid two-phase flows has been proposed using a time-resolved two-phase PIV system. For the three-dimensional evaluation of the bubble information, both the images from the front and side views are simultaneously recorded into a high speed CCD camera by reflecting the side image into the front view with the help of a $45^{\circ}$ oriented mirror. Then, a stereo-matching technique is applied to calculate the void fraction, bubble size and shape. To obtain the rising bubble velocities, the 2-frame PTV method was applied. Consequently, the present technique shows good feasibility for the measurements of the volume fractions, mean diameters, aspect ratios and velocities of the bubbles at the three-dimensional point of view.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.931-932
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• 2008

An implementation of modified stereo matching using efficient belief propagation(BP) algorithm is presented in this paper. Edges of the image were found using conventional edge detection algorithms. Resulting edge information is used to suppress propagation of wrong probabilistic information. Proposed method can effectively reduce errors that incurred by ambiguous scene properties.