• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.3
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• pp.331-341
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• 2002

In order to extract 3-dimensional information from 2-D image, stereo images are prerequisite. Moreover, for the measurement of moving objects, the synchronized sequential stereo images have to be captured and image matching should be implemented for determining the location of moving objects. In this research, a simple method computing 3-dimensional coordinates from sequential images of moving objects was implemented. The sequential stereo images were captured by a video camera with a beam splitter. Once video images were digitalized by frame grabber, the interest points were extracted and matched in each stereo image, and the coordinates of center of them are calculated using weighted average method. Then, 3-dimensional coordinates of moving objects were computed by DLT algorithms.

• Journal of the Institute of Convergence Signal Processing
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• v.18 no.1
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• pp.21-24
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• 2017

Passive millimeter wave (MMW) imaging penetrates clothing to detect concealed objects. The distances extraction to the concealed objects is critical for the security and defense. In this paper, we address a passive stereo 3 mm MMW imaging system to extract the longitudinal distance to the concealed object. The concealed object area is segmented and extracted by the k-means clustering algorithm with splitting initialization. The distance to the concealed object is estimated by the corresponding centers of the segmented objects. In the experimental two pairs (each pair for horizontal and vertical polarization) of stereo MMW images are obtained to estimate distances to concealed objects.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.10
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• pp.14-21
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• 2006

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.264-264
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• 2000

In this paper, we propose a method to automatically extract stable visual landmarks from observed data for a mobile robot with stereo vision system. The robot selects as stable landmarks vertical line segments which are distinct and on planar surfaces, because they are expected to be observed reliably from various view-points. When the robot moves, it uses several, less uncertain landmarks for estimating its motion. Experimental results in real scenes show the validity of the proposed method.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.5
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• pp.459-464
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• 2015

An on-line quality control of hot steel products is one of the important issues in the steel industry because of cost minimization. In recent years, relative depth information of surface defects is increasingly required for strict quality control. In this paper, a 3D shape reconstruction scheme for defects on a hot steel surface based on a multi-spectral photometric stereo method is proposed. After simultaneously illuminating a hot steel surface by using vertical/horizontal linearly polarized lights of green and blue light sources, the corresponding 4 images are obtained. The photometric stereo method is then applied with the aid of a GPU (Graphic Processing Unit) to reconstruct the shape of the target surface based on these images. The proposed scheme was validated through experiments.

• Journal of Multimedia Information System
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• v.9 no.3
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• pp.183-190
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• 2022

Image-based 3D object detection is one of the important and difficult problems in autonomous driving and robotics, and aims to find and represent the location, dimension and orientation of the object of interest. It generates three dimensional (3D) bounding boxes with only 2D images obtained from cameras, so there is no need for devices that provide accurate depth information such as LiDAR or Radar. Image-based methods can be divided into three main categories: monocular, stereo, and multi-view 3D object detection. In this paper, we investigate the recent state-of-the-art models of the above three categories. In the multi-view 3D object detection, which appeared together with the release of the new benchmark datasets, NuScenes and Waymo, we discuss the differences from the existing monocular and stereo methods. Also, we analyze their performance and discuss the advantages and disadvantages of them. Finally, we conclude the remaining challenges and a future direction in this field.

• 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 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.