• ETRI Journal
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• v.27 no.2
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• pp.172-180
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• 2005

Image resampling according to epipolar geometry is an important prerequisite for a variety of photogrammetric tasks. Established procedures for resampling frame images according to epipolar geometry are not suitable for scenes captured by line cameras. In this paper, the mathematical model describing epipolar lines in scenes captured by line cameras moving with constant velocity and attitude is established and analyzed. The choice of this trajectory is motivated by the fact that many line cameras can be assumed to follow such a flight path during the short duration of a scene capture (especially when considering space-borne imaging platforms). Experimental results from synthetic along-track and across-track stereo-scenes are presented. For these scenes, the deviations of the resulting epipolar lines from straightness, as the camera's angular field of view decreases, are quantified and presented.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.108-115
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• 2011

This paper describes a new sensor system for mobile robot motion estimation using stereo infrared light sources and a camera. Visibility is being applied to robotic obstacle avoidance path planning and localization. Using simple visibility computation, the environment is partitioned into many visibility sectors. Based on the recognized edges, the sector a robot belongs to is identified and this greatly reduces the search area for localization. Geometric modeling of the vision system enables the estimation of the characteristic pixel position with respect to the robot movement. Finite difference analysis is used for incremental movement and the error sources are investigated. With two characteristic points in the image such as vertices, the robot position and orientation are successfully estimated.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1003-1004
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• 2008

In this paper, we propose a 3D modeling method using Laser Slit Beam and Stereo Camera. We can get depth information of image by analyzing projected Laser Slit Beam on object. 3D modeling is demanded exquisite merge of 3D data. In our approach, we can get the depth image where the reliability is high. Each reconstructed 3D modeling is combined by the sink information which is acquired by SIFT (Scale Invariant Feature Transform) Algorithm. We perform experiments using indoor images. The results show that the proposed method works well in indoor environments

• Proceedings of the KSME Conference
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• 2001.11b
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• pp.410-416
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• 2001

An algorithm of 3-D particle image velocimetry(3D-PIV) was developed for the measurement of 3-D velocity field of complex flows. The measurement system consists of two or three CCD camera and one RGB image grabber. In this study, stereo photogrammetty was applied for the 3-D matching of tracer particles. Epipolar line was used to decect the stereo pair. 3-D CFD data was used to estimate algorithm. 3-D position data of the first frame and the second frame was used to find velocity vector. Continuity equation was applied to extract error vector. The algorithm result involved error vecotor of about 0.13 %. In Pentium III 450MHz processor, the calculation time of cross-correlation for 1500 particles needed about 1 minute.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.157-160
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• 2008

A realization for moving object detecting and tracking system in two dimensional plane using stereo line CCDs and lighting source is presented in this paper. Instead of processing camera images directly, two line CCD sensor and input line image is used to measure two dimensional distance by comparing the brightness on line CCDs. The algorithms are used the moving object tracking and coordinate converting method. To ensure the effective detection of moving path, a detection algorithm to evaluate the reliability of each measured distance is developed. The realized system results are that the performance of moving object recognizing shows 5mm resolution and mean error is 1.89%, and enables to track a moving path of object per 100ms period.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.694-699
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• 2003

Simultaneous measurement with PLIF(Planar Laser-Induced Fluorescence) and Stereo-PIV(Stereoscopic Particle Image Velocimetry) was performed to investigate the structural characteristics of flow field in Rushton Turbine Mixer. Instantaneous 3D velocity fields are measured by two 2K ${\times}$ 2K CCD cameras focused on an object plane with the angular displacement methods while the concentration fields are obtained through the measurement of the fluorescence intensity of Rhodamine B tracer excited by the second pulse of Nd:Yag laser light. Image distortion due to the camera view-angle is compensated by a mapping function. Finally, the spatial structures of turbulent mixing around Rushton turbine were identified by the calculation of cross-correlation fields between the velocity and concentration field.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.313-314
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• 2006

Obtained disparity map from the stereo camera by using the several stereo matching algorithms carries lots of noise because of various causes. In our approach, mode filtering and noise elimination technique using the histogram and projection-based region merging methods are adopted for improving the quality of disparity map and image segmentation. The proposed algorithms are implemented in VHDL and the real-time experimentation shows the accurately divided objects.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.70.1-70
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• 2001

Recently, research of visual control is getting more essential in robotic application, and acquiring 3D informations from the 2D images is becoming more important with development of vision system. For this application, we propose the effective way of controlling stereo vision tracking system for target tracking and calculating distance between target and camera. In this paper we address improved controller using dual-loop visual servo which is more effective compared with using single-loop visual servo for stereo vision tracking system. The speed and the accuracy for realizing a real time tracking are important. However, the vision processing speed is too slow to track object in real time by using only vision feedback data. So we use another feedback data from controller parts which offer state feedback ...

• Journal of the Korean Society for Precision Engineering
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• v.10 no.1
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• pp.77-88
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• 1993

In this paper, we propose a stereo vision system to solve correspondence problem with large disparity and sudden change in environment which result from small distance between camera and working objects. First of all, a specific feature is divided by predfined elementary feature. And then these are combined to obtain coded data for solving correspondence problem. We use Neural Network to extract elementary features from specific feature and to have adaptability to noise and some change of the shape. Fourier transformation and Log-polar mapping are used for obtaining appropriate Neural Network input data which has a shift, scale, and rotation invariability. Finally, we use associative memory to obtain coded data of the specific feature from the combination of elementary features. In spite of specific feature with some variation in shapes, we could obtain satisfactory 3-dimensional data from corresponded codes.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.129-134
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• 2003

Mobile Mapping System needs system calibration of multi sensors. System calibration is defined as determination of spatial and rotational offsets between the sensors. Especially, EO parameters of GPS/INS require knowledge of the calibration to camera frame. The calibration parameters must be determined with the highest achievable accuracy in order to get 3D coordinate points in stereo CCD images. This study applies Boresight calibration for the calibration between GPS/INS and camera, and estimates the Performance of the calibration.