• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.119-126
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• 2012

Recently, we used to recognize for human motions with some recognition algorithms. examples, HMM, DTW, PCA etc. In many human motions, we concentrated our research on recognizing fighting motions. In previous work, to obtain the fighting motion data, we used motion capture system which is developed with some active markers and infrared rays cameras and 3 dimension information converting algorithms by the stereo matching method. In this paper, we describe that the different method to acquiring 3 dimension fighting motion data and a HMM algorithm to recognize the data. One of the obtaining 3d data we used is depth map algorithm which is calculated by a stereo method. We test the 3d acquiring and the motion recognition system, and show the results of accuracy and performance results.

• The Journal of Korea Robotics Society
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• v.11 no.3
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• pp.172-182
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• 2016

Lane-level vehicle positioning is an important task for enhancing the accuracy of in-vehicle navigation systems and the safety of autonomous vehicles. GPS (Global Positioning System) and DGPS (Differential GPS) are generally used in navigation service systems, which however only provide an accuracy level up to 2~3 m. In this paper, we propose a 3D vision based lane-level positioning technique which can provides accurate vehicle position. The proposed method determines the current driving lane of a vehicle by tracking the 3D position of traffic signs which stand at the side of the road. Using a stereo camera, the 3D tracking paths of traffic signs are computed and their projections to the 2D road plane are used to determine the distance from the vehicle to the signs. Several experiments are performed to analyze the feasibility of the proposed method in many real roads. According to the experimental results, the proposed method can achieve 90.9% accuracy in lane-level positioning.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.6
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• pp.565-574
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• 2015

Recently, a medium-level representation named "Stixel" has been extensively researched in stereo vision-based environmental perception. Obstacle detection using Stixel representation consists of three steps: static Stixel generation, dynamic Stixel generation, and Stixel segmentation. This paper focuses on the Stixel segmentation step and has two contributions. One is that it shows that Stixel segmentation performance can be enhanced by utilizing both image domain and real world domain features. The other is that it suggests that parameters used for Stixel segmentation can be effectively tuned based on genetic algorithm. The proposed method was quantitatively evaluated and the result showed that the proposed method increased Stixel segmentation accuracy compared with the previous method.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.1
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• pp.61-67
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• 1985

The new computer vision system which can reconstruct contours of parallel fault planes with horizon of 3-D curved objects has been developed. With the system, the shape of 3-D objects was measured by Simple Back-Projection algorithm which is a fundamental one in C.T.(Computed Tomography). And, the curvature in differential geometry characterizes any curve. Devising it, the method to represent each contour of 3-D curved objects with the system is described in this paper.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.1
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• pp.31-40
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• 2010

For weapon cueing and Head-Mounted Display (HMD), it is essential to continuously estimate the motion of the helmet. The problem of estimating and predicting the position and orientation of the helmet is approached by fusing measurements from inertial sensors and stereo vision system. The sensor fusion approach in this paper is based on nonlinear filtering, especially expended Kalman filter(EKF). To reduce the computation time and improve the performance in vision processing, we separate the structure estimation and motion estimation. The structure estimation tracks the features which are the part of helmet model structure in the scene and the motion estimation filter estimates the position and orientation of the helmet. This algorithm is tested with using synthetic and real data. And the results show that the result of sensor fusion is successful.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.295-298
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• 1995

In this paper, one simple technique to calibrate the system setting of the three-dimensional measuring system is presented. Due to this technique, the three-dimensional shape of the huge structures and the buildings can be readily obtained. This technique is applied to the three-dimensional landscape simulation. Two examples are shown in this paper.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.492-498
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• 1994

The bicycle production process mainly consists of welding process of pipes and its quality is determined by geometrical symmetry of arrangement of welded pipes. Hence, manual quality control of bicycle frames was very inefficient and required much time in dimentional inspection and does not reserve high precision. In this paper we introduce a method of fast and accurate dimensional inspection of bicycle frame using the Stereo Vision system and related some image processing techniques.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.547-554
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• 2013

This paper proposes a novel formation algorithm of identical robots based on object tracking method using omni-directional images obtained through fisheye lenses which are mounted on the robots. Conventional formation methods of multi-robots often use stereo vision system or vision system with reflector instead of general purpose camera which has small angle of view to enlarge view angle of camera. In addition, to make up the lack of image information on the environment, robots share the information on their positions through communication. The proposed system estimates the region of robots using SURF in fisheye images that have $360^{\circ}$ of image information without merging images. The whole system controls formation of robots based on moving directions and velocities of robots which can be obtained by applying Lucas-Kanade Optical Flow Estimation for the estimated region of robots. We confirmed the reliability of the proposed formation control strategy for multi-robots through both simulation and experiment.

• Journal of Internet Computing and Services
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• v.6 no.6
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• pp.149-161
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• 2005

Catadioptric mirrors are widely used in automatic surveillance system. The major drawback of catadioptric mirror is its unequal image resolution. Equidistance catadioptric mirror can be the solution to this problem. Even double panoramic structure can generate stereo images with single camera system. So two images obtained from double panoramic equidistance catadioptric mirror can be used in finding the depth and height values of object's points. But compared to the single catadioptric mirror. the image size of double panoramic system is relatively small. This leads to the severe accuracy problem in estimation. The exact axial alignment and the exact mount of mirror are the sources that can be avoided but the focal length variation is inevitable. In this paper, the effects of focal length variation on the computation of depth and height of object' point are explained and the effective focal length finding algorithm, using the assumption that the object's viewing angles are almost same in stereo images, is presented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.780-781
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• 2016

The stereo radiation detection system detects gamma ray source and measures the two dimensional distribution image based on the detection result. Then the system is implemented to measure the distance to the radiation source from the system in 3D space using stereo vision algorithm. In this paper, we reduced the time for a gamma-ray scan space detection through image processing algorithms. In addition, it combines radiation and visible light images. Then we conducted a study for improving the distribution of gamma-ray detection efficiency through the stereo calibration using a 3D visualization. As a result, we obtain an improved detection time by more than 30% and have acquired a visible image with a 3D monitor.