• The KIPS Transactions:PartB
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• v.10B no.2
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• pp.135-142
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• 2003

Robust extraction of 3D object's features, shape and global motion information from 2D image sequence is described. The object's 21 feature points on the pyramid type synthetic object are extracted automatically using color transform technique. The extracted features are used to recover the 3D shape and global motion of the object using stereo paraperspective camera model and sequential SVD(Singuiar Value Decomposition) factorization method. An inherent error of depth recovery due to the paraperspective camera model was removed by using the stereo image analysis. A 30 synthetic object with 21 features reflecting various position was designed and tested to show the performance of proposed algorithm by comparing the recovered shape and motion data with the measured values.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.2
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• pp.75-80
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• 2017

Recently, there has been growing interest in spatial data that combines information and communication technology with smart cities. The high-precision LiDAR (Light Dectection and Ranging) equipment is mainly used to collect three-dimensional spatial data, and the acquired data is also used to model geographic features and to manage plant construction and cultural heritages which require precision. The LiDAR equipment can collect precise data, but also has limitations because they are expensive and take long time to collect data. On the other hand, in the field of computer vision, research is being conducted on the methods of acquiring image data and performing 3D reconstruction based on image data without expensive equipment. Thus, precise 3D spatial data can be constructed efficiently by collecting and processing image data using CCTVs which are installed as infrastructure facilities in smart cities. However, this method can have an accuracy problem compared to the existing equipment. In this study, experiments were conducted and the results were analyzed to increase the number of extracted matching points by applying the feature-based method and the area-based method in order to improve the precision of 3D spatial data built with image data acquired from stereo CCTVs. For techniques to extract matching points, SIFT algorithm and PATCH algorithm were used. If precise 3D reconstruction is possible using the image data from stereo CCTVs, it will be possible to collect 3D spatial data with low-cost equipment and to collect and build data in real time because image data can be easily acquired through the Web from smart-phones and drones.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.10
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• pp.870-887
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• 2012

This paper qualitatively analyzes the stereo 3D content factors causing viewer's discomfort. For this, we perform a subjective test that each subject strokes a specific key whenever he or she feels discomfort during watching stereo 3D contents. Also we extract the quantitative values of the factors in the 3D contents to obtain the temporal changes of the factors. Those two sets of data are used to analyze the contents to find the content factors which cause viewer's discomfort. The factors to be considered are the amount and the frequency of the disparity change, story of the contents, situation or environments of a scene, movement and position of the image or camera, color and luminance information as well as disparities themselves. Most researches have dealt with each factor causing viewer's discomfort but this paper focuses on the composite factors rather than each of them. That is, this paper deals with the various strong and weak factors and their composites causing viewer's discomfort in addition to the big disparities which have been mostly so far.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.3 s.309
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• pp.30-38
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• 2006

In this paper, we improved to drops recognition rate according to distance using distance and depth information with 3D from stereo face images. A monocular face image has problem to drops recognition rate by uncertainty information such as distance of an object, size, moving, rotation, and depth. Also, if image information was not acquired such as rotation, illumination, and pose change for recognition, it has a very many fault. So, we wish to solve such problem. Proposed method consists of an eyes detection algorithm, analysis a pose of face, md principal component analysis (PCA). We also convert the YCbCr space from the RGB for detect with fast face in a limited region. We create multi-layered relative intensity map in face candidate region and decide whether it is face from facial geometry. It can acquire the depth information of distance, eyes, and mouth in stereo face images. Proposed method detects face according to scale, moving, and rotation by using distance and depth. We train by using PCA the detected left face and estimated direction difference. Simulation results with face recognition rate of 95.83% (100cm) in the front and 98.3% with the pose change were obtained successfully. Therefore, proposed method can be used to obtain high recognition rate with an appropriate scaling and pose change according to the distance.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.82-84
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• 2003

Watershed boundaries and flow paths within the watershed are the most important factors required in watershed analysis. Most often the derivation of watershed boundaries and stream network and flow paths is based on topographical maps but spatial variation of flow direction is not clearly understandable using this method. Water resources projects currently use 1: 50, 000-scale ground survey or aerial photography-based topographical maps to derive watershed boundary and stream network. In basins, where these maps are not available or not accessible it creates a real barrier to watershed geo-spatial analysis. Such situations require the use of global datasets, like GTOPO30. Global data sets like ETOPO5, GTOPO30 are the only data sets, which can be used to derive basin boundaries and stream network and other terrain variations like slope aspects and flow direction and flow accumulation of the watershed in the absence of topographic maps. Approximately 1-km grid-based GTOPO 30 data sets can derive better outputs for larger basins, but they fail in flat areas like the Karkheh basin in Iran and the Amudarya in Uzbekistan. A new window in geo-spatial hydrology has opened after the launching of the space-borne satellite stereo pair of the Terra ASTER sensor. ASTER data sets are available at very low cost for most areas of the world and global coverage is expected within the next four years. The DEM generated from ASTER data has a reasonably good accuracy, which can be used effectively for hydrology application, even in small basins. This paper demonstrates the use of stereo pairs in the generation of ASTER DEMs, the application of ASTER DEM for watershed boundary delineation, sub-watershed delineation and explores the possibility of understanding the drainage flow paths in irrigation command areas. All the ASTER derived products were compared with GTOPO and 1:50,000-based topographic map products and this comparison showed that ASTER stereo pairs can derive very good data sets for all the basins with good spatial variation, which are equal in quality to 1:50,000 scale maps-based products.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.466-468
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• 2022

3D reconstruction is important issue in many applications such as Augmented Reality (AR), eXtended Reality (XR), and Metaverse. For 3D reconstruction, depth map can be acquired by stereo camera and time-of-flight (ToF) sensor. We used both sensors complementarily to improve the accuracy of 3D information of the data. First, we applied general multi-camera calibration technique which uses both color and depth information. Next, the depth map of the two sensors are fused by 3D registration and reprojection approach. The fused data is compared with the ground truth data which is reconstructed using RTC360 sensor. We used Geomagic Wrap to analysis the average RMSE of the two data. The proposed procedure was implemented and tested with real-world data.

• Journal of IKEEE
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• v.13 no.2
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• pp.181-185
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• 2009

In this paper, we are concerned with a 3D line segment extraction method by area-based stereo matching technique. The main idea is based on line fitting of elevation data on 2D line coordinates of ortho-image. Elevation data and ortho-image can be obtained by well-known area-based stereo matching technique. In order to use elevation in line fitting, the elevation itself should be reliable. To measure the reliability of elevation, in this paper, we employ the concept of self-consistency. We test the effectiveness of the proposed method with a quantitative accuracy analysis using synthetic images generated from Avenches data set of Ascona aerial images. Experimental results indicate that our method generates 3D line segments almost 7.5 times more accurate than raw elevations obtained by area-based method.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.8
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• pp.1188-1200
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• 1990

In this paper, the 3-D positioning problem for a quadruped walking robot is investigated. In order to determine the robot's exterior position and orentation in a worls coordinate system, a stereo 3-D positioning algorithm is proposed. The proposed algorithm uses a Guide-Mark Pattern (GMP) specialy designed for fast and reliable extraction of 3-D robot position information from the uncontrolled working environment. Some experimental results along with error analysis and several means of reducing the effects of vision processing error in the proposed algorithm are disscussed.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.3
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• pp.224-229
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• 2007

This paper presents a camera calibration method using several images for three dimensional measurement applications such as stereo systems, mobile robots, and visual inspection systems in factories. Conventional calibration methods that use single image suffer from errors related to reference point extraction in image, lens distortion, and numerical analysis of nonlinear optimization. The camera parameter values obtained from images of same camera is not same even though we use same calibration method. The camera parameters that are obtained from several images of different view for a calibration target is usaully not same with large error values and we can not assume a special probabilistic distribution when we estimate the parameter values. In this paper, the median value of camera parameters from several images is used to improve estimation of the camera values in an iterative step with nonlinear optimization. The proposed method is proved by experiments using real images.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.7-7
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• 2000

This paper describes a mirror control system that can adjust the location of side and room mirror of the vehicle automatically using 3D coordinates to monitor the location of driver's eyes. Through analysis of the image inputted by two B/W CCD camera and infrared lamps installed on top of the driver's dashboard, we can estimate the values of 3D coordinate of the driver's eyes. Using these values, this system can determine the absolute position of each mirror and activate each actuator to the appropriate position. The stereo vision system can detect the driver's eyes whether it is day or night by virtue of infrared Lamps. We have tested this system using 10 drivers who drive a car currently, and most of the drivers were satisfied with the convenience of this system.