• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.403-404
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• 2006

In this paper, we proposed muli-dimensional feature vector matching method combined with disparity smoothness constraint. The smoothness constraint was calculated using the difference between disparity of center pixel and those of 4-neighbor pixels. By applying proposed algorithm to IKONOS satellite stereo imagery, we obtained robust stereo matching result in urban areas.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11a
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• pp.179-182
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• 2003

기존의 단일영상을 통한 얼굴인식기술이 갖는 단점을 극복하고자 본 논문에서는 스테레오 영상을 사용하여 단일영상의 제약조건 약화와 스테레오 영상의 깊이 정보를 이용한 보다 강건한 얼굴정보의 추출을 통한 다양한 특징 정보를 이용함으로써 얼굴인식의 인식률을 향상 시키고자 하였다.

• The Journal of Korea Robotics Society
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• v.9 no.2
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• pp.96-103
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• 2014

Global localization is one of the essential issues for mobile robot navigation. In this study, an indoor global localization method is proposed which uses a Kinect sensor and a monocular upward-looking camera. The proposed method generates an environment map which consists of a grid map, a ceiling feature map from the upward-looking camera, and a spatial feature map obtained from the Kinect sensor. The method selects robot pose candidates using the spatial feature map and updates sample poses by particle filter based on the grid map. Localization success is determined by calculating the matching error from the ceiling feature map. In various experiments, the proposed method achieved a position accuracy of 0.12m and a position update speed of 10.4s, which is robust enough for real-world applications.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.39-44
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• 2022

This paper presents LiDAR static obstacle map based vehicle position correction algorithm for urban autonomous driving. Real Time Kinematic (RTK) GPS is commonly used in highway automated vehicle systems. For urban automated vehicle systems, RTK GPS have some trouble in shaded area. Therefore, this paper represents a method to estimate the position of the host vehicle using AVM camera, front camera, LiDAR and low-cost GPS based on Extended Kalman Filter (EKF). Static obstacle map (STOM) is constructed only with static object based on Bayesian rule. To run the algorithm, HD map and Static obstacle reference map (STORM) must be prepared in advance. STORM is constructed by accumulating and voxelizing the static obstacle map (STOM). The algorithm consists of three main process. The first process is to acquire sensor data from low-cost GPS, AVM camera, front camera, and LiDAR. Second, low-cost GPS data is used to define initial point. Third, AVM camera, front camera, LiDAR point cloud matching to HD map and STORM is conducted using Normal Distribution Transformation (NDT) method. Third, position of the host vehicle position is corrected based on the Extended Kalman Filter (EKF).The proposed algorithm is implemented in the Linux Robot Operating System (ROS) environment and showed better performance than only lane-detection algorithm. It is expected to be more robust and accurate than raw lidar point cloud matching algorithm in autonomous driving.

• Journal of the Korean association of regional geographers
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• v.9 no.4
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• pp.425-436
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• 2003

Integrated approach is presented by developing the technology and the ways of the practical use of the integrated digital map of and Electronical Navigational Chart (ENC) and Digital Terrain Map (DTM) for the effective and scientific based conservation, development and management of coastal area in this study. At first as preliminary studies to make eventual integrated maps, the necessity of the integrated map is described with the concept of coastal areas. Then, the characteristics of digital maps developed by Korean Geography Institute and National Marine Investigation Institute are carefully analyzed and integrated to a digital map as a test for edge matching in coastal line. Developed test coastal map was overlayed with a high-resolution satellite image (KVR-1000). The ground survey using Global Positioning System was conducted for the analysis of edge matching along the coastal line. Results from the edge matching analysis of coastal lines showed about 14 meters mean difference in artificial terrain and 4 meters mean difference in natural terrain. The problems, causes and solutions for the edge-matched differences are described. Furthermore, the value of utilization, the future use and various fields of application produced by the integrated digital map database are suggested as a basis for ICZM implementation in South Korea.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.5
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• pp.179-186
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• 2021

For stereo matching based on deep learning, the design of network structure is crucial to the calculation of matching cost, and the time-consuming problem of convolutional neural network in image processing also needs to be solved urgently. In this paper, a method of stereo matching using sparse loss volume in parallax dimension is proposed. A sparse 3D loss volume is constructed by using a wide step length translation of the right view feature map, which reduces the video memory and computing resources required by the 3D convolution module by several times. In order to improve the accuracy of the algorithm, the nonlinear up-sampling of the matching loss in the parallax dimension is carried out by using the method of multi-category output, and the training model is combined with two kinds of loss functions. Compared with the benchmark algorithm, the proposed algorithm not only improves the accuracy but also shortens the running time by about 30%.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.83-91
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• 2011

Recently, many researchers in the world are concentrated to develop the robot platform which is to reduce the developing cost by reusing existing softwares. In this paper, we describe that the 3 dimension recognition object components for OPRoS (Open Platform for Robotic Services) which is developed in Korea. We present that the structure of the component, disparity map and depth map algorithm for recognizing 3 dimension space. We used stereo matching and block matching method to produce the disparity map. We test the component on the computer with OPRoS platform and show the results of accuracy and performance time.

• Journal of Korea Multimedia Society
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• v.14 no.2
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• pp.288-294
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• 2011

In this paper we define the probability models for determining the disparity map given stereo images and derive the methods for solving the problem, which is proven to be equivalent to an energy-based stereo matching. Under the assumptions the difference between the pixel on the left image and the corresponding pixel on the right image and the difference between the disparities of the neighboring pixels are exponentially distributed, a recursive approach for estimating the MRF regularizing parameter is proposed. The proposed method alternates between estimating the parameters with the intermediate disparity map and estimating the disparity map with the estimated parameters, after computing it with random initial parameters. Our algorithm is applied to the stereo matching algorithms based on the dynamic programming and belief propagation to verify its operation and measure its performance.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.112-119
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• 2010

This paper defines the probability models for determining the disparity map given stereo images and derives the methods for solving the problem, which is proven to be equivalent to an energy-based stereo matching. Under the assumptions the difference between the pixel on the left image and the corresponding pixel on the right image and the difference between the disparities of the neighboring pixels are exponentially distributed, a recursive approach for estimating the MRF regularizing parameter is proposed. Usually energy-based stereo matching methods are so sensitive to the parameter that it should be carefully determined. The proposed method alternates between estimating the parameter with the intermediate disparity map and estimating the disparity map with the estimated parameter, after computing it with random initial parameter. It is shown that the parameter estimated by the proposed method converges to the optimum and its performance can be improved significantly by adjusting the parameter and modifying the energy term.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.4
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• pp.23-29
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• 2009

Recent growth of the geospatial information on the Web has made it possible to easily access a wide variety of geospatial information. An integration of different geospatial objects consists of the following three steps; extracting geospatial objects from the maps, converting the coordinate system and discovering pairs of objects that represent the same real-world entity in the two maps. This paper deals mainly with the third step to correspond conjugate objects and four matching types and criteria is presented. The techniques designed and developed can be utilized to efficiently integrate distributed heterogeneous spatial databases such as the digital maps and POIs from other data sources. To achieve the goal, we presented four types and criteria for the matching schema. The main contributions of this paper are as follows. A complete process of integrating data from maps on the Web is presented. Then, we show how attributes of the objects can be used in the integration process.