• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.100.2-100
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• 2002

In this paper we propose a new visual servoing method for door opening with mobile manipulator. We use an eye-to-hand system that stereo camera is mounted on mobile platform, and adopt the position-based method. The previous methods for door opening mostly used eye-in-hand system with mono camera and required predefined knowledge such as radius and position about door grip, which was mainly caused by using mono cam era. This is also a severe constraint for pursuing general-purpose algorithm for door opening. For overcoming such drawback, we use stereo camera and suggest a new method that detect the door grip and estimate its pose from stereo depth information without predefined knowledge. Al...

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.3
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• pp.151-157
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• 2008

In this paper, we propose a three dimensional distance measurement method for a stereo system by using web cams. Using a parallel stereo system, a robot gets two images from each webcam and equalize brightness of both images. And we suggest an image processing method such as labeling, isolating an object from background and finding center of an object. We also propose a method of calculating the focal distance by using least square algorithm based on triangulation and we can reduce calculation error by this method. From experimental results, we show that the proposed method can be effective for 3D distance measurement.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2407-2410
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• 2003

In this paper, we propose a new stereoscopic video conversion methodology that converts two-dimensional (2-D) MPEG-4 video to stereoscopic video. In MPEG-4, each Image is composed of background object and primary object. In the first step of the conversion methodology, the camera motion type is determined for stereo Image generation. In the second step, the object-based stereo image generation is carried out. The background object makes use of a current image and a delayed image for its stereo image generation. On the other hand, the primary object uses a current image and its horizontally-shifted version to avoid the possible vertical parallax that could happen. Furthermore, URFA(Uncovered Region Filling Algorithm) is applied in the uncovered region which might be created after the stereo image generation of a primary object. In our experiment, show MPEG-4 test video and its stereoscopic video based upon out proposed methodology and analyze Its results.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.265-266
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• 1998

This paper describes a depth extraction algorithm in the stereo endoscopic images using adaptive window. First, The relation between the 3D coordinates in the world and the 2D coordinates in the image plane is estimated using camera calibration. Next, stereo matching is performed to find the conjugate pairs in the left and right images. To improve the precision of the matching result, adaptive window which can be varied on the shape as well as on the size according to the area characteristics is used. Finally, the result from the stereo matching and that of camera modeling are combined to extract the real depth information.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.2
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• pp.191-198
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• 2015

In this paper, six-degree-of-freedom (DoF). Displacement measurement technique using a compact stereo-vision system is proposed. The measuring system consists of a camera, an optical prism, two plane mirrors, and a planar marker on a target. The target was attached on an object so that its six-DoF displacement can be calculated using a proposed coordinates estimating algorithm and stereo images of the marker. A prototype was designed and fabricated for performance test. From the test results, it can be confirmed that the proposed measuring technique can be applied to monitoring and control of various manipulators.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.3
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• pp.163-172
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• 2003

A stereo matching has been an important tool for the reconstruction of 3D terrain. The current state of stereo matching technology has reached the level where a very elaborate DEM(Digital Elevation Map) can be obtained. However, there still exist many factors causing DEM error in stereo matching. This paper propose a new method to reduce the error caused by the lack of significant features in the correlation window The proposed algorithm keeps the correlation window as small as possible, as long as there is a significant feature in the window. Experimental results indicate that the proposed method increases the DEM accuracy by $72.65\%$ in the plain area and $41.96\%$ in the mountain area over the conventional scheme. Comparisons with Kanade's result show that the proposed method eliminates spike type of errors more efficiently than Kanade's adaptive window technique and produces reliable DEM.

• International journal of advanced smart convergence
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• v.7 no.3
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• pp.8-14
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• 2018

In the field of surveillance cameras, it is possible to increase the people detection accuracy by using depth information indicating the distance between the camera and the object. In general, depth information is obtained by calculating the parallax information of the stereo camera. However, this method is difficult to operate in real time in the embedded environment due to the large amount of computation. Jetson TX2, released by NVIDIA in March 2017, is a high-performance embedded board with a GPU that enables parallel processing using the GPU. In this paper, a stereo camera is installed in Jetson TX2 to acquire depth information in real time, and we proposed a people counting method using acquired depth information. Experimental results show that the proposed method had a counting accuracy of 98.6% and operating in real time.

• Journal of Electrical Engineering and information Science
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• v.2 no.5
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• pp.79-88
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• 1997

This paper introduces a new energy function, as maximum a posteriori(MAP) estimate of binocular disparity, that can deal with both random dot stereo-gram(RDS) and natural scenes. The energy function uses phase-magnitude as features to detect only the shift for a pair of corrupted conjugate images. Also we adopted Fleet singularity that effectively detects unstable areas of image plant and thus eliminates in advance error-prone stereo mathcing. The multi-scale concept is applied to the multi laser architecture that can search the solutions systematically from coarse to fine details and thereby avoids drastically the local minima. Using mean field approximation, we obtained a compact representation that is suitable for fast computation. In this manner, the energy function satisfies major natural constraints and requirements for implementing parallel relaxation. As an experiment, the proposed algorithm is applied to RDS and natural stereo images. As a result we will see that it reveals good performance in terms of recognition errors, parallel implementation, and noise characteristics.

• Journal of Broadcast Engineering
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• v.10 no.4 s.29
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• pp.576-586
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• 2005

This paper presents a new estimation and representation of a disparity map for stereo-based video communication systems. Several pixel-based and block-based algorithms have been proposed to estimate the disparity map. While the pixel-based algorithms can achieve high accuracy in computing the disparity map, they require a lost of bits to represent the disparity information. The bit rate can be reduced by the block-based algorithm, sacrificing the representation accuracy. In this paper, the block enclosing a distinct edge is divided into two regions and the disparity of each region is set to that of a neighboring block. The proposed algorithm employs accumulated histograms and a neural network to classify a type of a block. In this paper, we proved that the proposed algorithm is more effective than the conventional algorithms in estimating and representing disparity maps through several experiments.