• Journal of IKEEE
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• v.24 no.2
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• pp.419-425
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• 2020

The market size of immersive 360-degree video contents, which are noted as one of the main technology of the fourth industry, increases every year. However, since most of the images are distributed through illegal distribution networks such as Torrent after the DRM gets lifted, the damage caused by illegal copying is also increasing. Although filtering technology is used as a technology to respond to these issues in 2D videos, most of those filtering technology has issues in that it has to overcome the technical limitation such as huge feature-point data volume and the related processing capacity due to ultra high resolution such as 4K UHD or higher in order to apply the existing technology to immersive 360° videos. To solve these problems, this paper proposes a feature-point recognition ratio improvement method for immersive 360-degree videos using deep learning technology.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.2
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• pp.93-98
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• 2013

Multi-temporal high resolution satellite images are essential data for efficient city analysis and monitoring. Yet even when acquired from the same location, identical sensors as well as different sensors, these multi-temporal images have a geometric inconsistency. Matching points between images, therefore, must be extracted to match the images. With images of an urban area, however, it is difficult to extract matching points accurately because buildings, trees, bridges, and other artificial objects cause shadows over a wide area, which have different intensities and directions in multi-temporal images. In this study, we analyze a shadow effect on image matching of high resolution satellite images in urban area using Scale-Invariant Feature Transform(SIFT), the representative matching points extraction method, and automatic shadow extraction method. The shadow segments are extracted using spatial and spectral attributes derived from the image segmentation. Also, we consider information of shadow adjacency with the building edge buffer. SIFT matching points extracted from shadow segments are eliminated from matching point pairs and then image matching is performed. Finally, we evaluate the quality of matching points and image matching results, visually and quantitatively, for the analysis of shadow effect on image matching of high resolution satellite image.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.563-566
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• 2022

본 논문에서는 증강현실에서 객체 증강 시, 특징점과 GPS를 이용하여 증강 위치를 효율적으로 보간할 수 있는 ICP(Iterative closest point) 매칭 기법을 제안한다. 다양한 환경에서 제한받지 않고 객체를 증강하기 위해 일반적으로 마커리스(Markerless) 방식을 사용하며, 대표적으로 평면 검출과 페이스 검출을 사용한다. 이는 현실과 자연스러운 동기화를 위한 것으로 계산은 작지만, 인식의 범위가 넓기 때문에 증강 위치에 대한 오차가 존재한다. 이러한 작은 오차는 특정 산업에서는 치명적일 수 있으며, 특히 건설이나 의료시설에서 발생하면 큰 사고로 이어진다. 객체를 증강 시킬 때 해당 환경에 대한 점 구름(Point cloud)을 수집하여 데이터베이스에 저장한다. 본 논문에서는 관측되는 점 구름과의 오차를 줄이기 위해 ICP 매칭 기법을 사용하며, 실린더 기반의 각도 보간을 이용하여 계산량을 줄인다. 결과적으로 특징점과 GPS를 이용하여 ICP 매칭 기법을 통해 효율적으로 처리함으로써, 증강 위치에 대한 정확도가 개선된 증강 방식을 보여준다.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1351-1367
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• 2018

Image registration is an essential process for image fusion, change detection and time series analysis using multi-sensor images. For this purpose, we need to detect accurately the difference of scale and rotation between the multi-sensor images with difference spatial resolution. In this paper, we propose a new feature matching method using variable circular template for image registration between multi-resolution images. The proposed method creates a circular template at the center of a feature point in a coarse scale image and also a variable circular template in a fine scale image, respectively. After changing the scale of the variable circular template, we rotate the variable circular template by each predefined angle and compute the mutual information between the two circular templates and then find the scale, the angle of rotation and the center location of the variable circular template, respectively, in fine scale image when the mutual information between the two circular templates is maximum. The proposed method was tested using Kompsat-2, Kompsat-3 and Kompsat-3A images with different spatial resolution. The experimental results showed that the error of scale factor, the error of rotation angle and the localization error of the control point were less than 0.004, $0.3^{\circ}$ and one pixel, respectively.

• The Journal of the Korea Contents Association
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• v.17 no.3
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• pp.42-52
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• 2017

Panorama image is a single image obtained by combining images taken at several viewpoints through matching of corresponding points. Existing panoramic image generation methods that find the corresponding points are extracting local invariant feature points in each image to create descriptors and using descriptor matching algorithm. In the case of video sequence, frames may be a lot, so therefore it may costs significant amount of time to generate a panoramic image by the existing method and it may has done unnecessary calculations. In this paper, we propose a method to quickly create a single panoramic image from a video sequence. By assuming that there is no significant changes between frames of the video such as in locally, we use the FAST algorithm that has good repeatability and high-speed calculation to extract feature points and the Lucas-Kanade algorithm as each feature point to track for find the corresponding points in surrounding neighborhood instead of existing descriptor matching algorithms. When homographies are calculated for all images, homography is changed around the center image of video sequence to warp images and obtain a planar panoramic image. Finally, the spherical panoramic image is obtained by performing inverse transformation of the spherical coordinate system. The proposed method was confirmed through the experiments generating panorama image efficiently and more faster than the existing methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.99-104
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• 2021

The technology of estimating a movement trajectory using a monocular camera such as a smartphone and composing a surrounding 3D image is key not only in indoor positioning but also in the metaverse service. The most important thing in this technique is to estimate the coordinates of the moving camera center. In this paper, a new algorithm for geometrically estimating the moving distance is proposed. The coordinates of the 3D object point are obtained from the first and second photos, and the movement distance vector is obtained using the matching feature points of the first and third photos. Then, while moving the coordinates of the origin of the third camera, a position where the 3D object point and the feature point of the third picture coincide is obtained. Its possibility and accuracy were verified by applying it to actual continuous image data.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.9-18
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• 2004

This paper proposes a new and simple stereo matching algorithm using the disparity space image (DSI) technique. First of all, we detect some salient feature points on each scan-line of the image pair and set the matching area using those points and define a simple cost matrix. And we take advantage of matching by pixel-by-pixel instead of using the matching window. While the pixel-by-pixel method boost up the speed of matching, because of no using neighbor information, the correctness of the matching may not be better. To cover this point, we expand the matching path using character of disparity-space-image for using neighbor information. In addition, we devise the compensated matching module using the volume of the disparity space image in order to improve the accuracy of the match. Consequently, we can reduce mismatches at the disparity discontinuities and can obtain the more detailed and correct disparity map.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.939-947
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• 2019

With the revitalization of the media market, the necessity of compression, searching, editing and copyright protection of videos is increasing. In this paper, we propose a method to detect scene change in all these fields. We propose a pre-processing, feature point extraction using SIFT, and matching algorithm for detecting the same scene change even if distortions such as resolution change, subtitle insertion, compression, and flip are added in the distribution process. Also, it is applied to filtering technology and it is confirmed that it is effective for all transformations other than considering transform.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.181.5-181
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• 2001

This paper presents the method of 3D reconstruction of the depth information from the endoscopic stereo scopic images. After camera modeling to find camera parameters, we performed feature-point based stereo matching to find depth information. Acquired some depth information is finally 3D reconstructed using the NURBS(Non Uniform Rational B-Spline) algorithm. The final result image is helpful for the understanding of depth information visually.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.446-448
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• 1998

본 논문은 두 장의 스테레오 영상으로부터 자동적으로 특징점 정합을 수행하도록 하는 한 방법을 제안한다. Correlation기반의 특징점 정합을 빠르고 안정적으로 수행하며 이 때에 발생하는 애매성 문제에 대한 해결방법을 제시한다. 또한, LMedS방법을 사용하여 outlier를 효과적으로 제거시키고 에피폴라 기하를 이용하여 정합의 성능을 향상시킨다. 실내, 실외 영상에 대한 다양한 실험결과는 본 논문에서 제안하는 방법이 빠르고 효율적임을 보여준다.