• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.42 no.4 s.304
• /
• pp.87-94
• /
• 2005

3D image mosaicking is useful for 3D visualization of the roadside scene of urban area by projecting 2D images to the 3D planes. When a sequence of images are filmed from a side-looking video camera passing long distance areas, the ghost effect in which same objects appear repeatively occurs. To suppress such ghost effect, the long distance range areas are detected by using the distance between the image frame and the 3D coordinate of tracked optical flows. The ghost effects are suppressed by projecting the part of image frames onto 3D multiple planes utilizing vectors passing the focal point of frames and a virtual focal point. The virtual focal point is calculated by utilizing the first and last frames of the long distance range areas. We demonstrate algorithm that creates efficient 3D Panoramic mosaics without the ghost effect at the long distance area.

• 한국지형공간정보학회:학술대회논문집
• /
• 1993.10a
• /
• pp.101-106
• /
• 1993

본 연구의 목적은 토지자원의 유효한 개발과 관리를 위해 원격탐사 자료 및 지상자료를 이용하여 토지 이용의 예측 모형을 정립하고 실제로 제주도 지역에 적용하여 그 실증을 거치는 것이었다. 본 토형은 계절분석(multi-date processing) 및 다중분석 (multi-file processing)기법을 채택하고 Markov의 확률 이전 계산법 및 판별 함수 (discriminant function) 계산법으로부터 합성 출현된 공간적/시간적 토지이용 투영방법을 채택하였다. 판별 함수 계산법은 토지이용 변화상의 최다 경향치를 산출하기 위해 제주도 경관 평면(landscape plane) 전지역의 각 화소(pixel)에 적용되고, 확률 이전 계산법은 특정 미래 시간 간극상에서 상이한 토지이용으로 변화하는 이들 화소의 수량을 결정한다. 본 합성 모형은 이렇게 토지이용 변화성(정성적)과 그 화소의 수량(정량적)을 결합하여 경관 평면상에서 미래의 토지이용 예측을 가능케하는 것이다.

• Journal of Broadcast Engineering
• /
• v.25 no.6
• /
• pp.954-964
• /
• 2020

In immersive media, the most important factor that provides immersion is depth information. Therefore, it is essential to obtain high quality depth information in order to produce high quality immersive media. In this paper we propose an algorithm to improve depth map, considering the segmentation of images and the relationship between multiple views in multi-view systems. The proposed algorithm uses a super-pixel segmentation technique to divide the depth map of the reference view into several segments, and project each segment into adjacent view. Subsequently, the depth map of the adjacent view is improved using plane estimation using the information of the projected segment, and then reversed to the reference view. This process is repeated for several adjacent views to improve the reference depth map by updating the values of the improved adjacent views and the initial depth map of the reference view. Through simulation, the proposed algorithm is shown to surpass the conventional algorithm subjectively and objectively.

• The Journal of the Korea Contents Association
• /
• v.10 no.7
• /
• pp.10-22
• /
• 2010

This study proposes a new method of multiple homographies estimation between two images. With a large proportion of outliers, RANSAC is a general and very successful robust parameter estimator. However it is limited by the assumption that a single model acounts for all of the data inliers. Therefore, it has been suggested to sequentially apply RANSAC to estimate multiple 2D projective transformations. In this case, because outliers stay in the correspondence data set through the estimation process sequentially, it tends to progress slowly for all models. And, it is difficult to parallelize the sequential process due to the estimation order by the number of inliers for each model. We introduce a guided sequential RANSAC algorithm, using the local model instances that have been obtained from RANSAC procedure, which is able to reduce the number of random samples and deal simultaneously with multiple models.

• Journal of the Institute of Convergence Signal Processing
• /
• v.12 no.4
• /
• pp.242-249
• /
• 2011

In this paper, the correspondence matching method of stereo images was proposed by means of sampling projective transformation matrix in planar region of scene. Though this study is based on RANSAC, it does not use uniform distribution by random sampling in RANSAC, but use multi non-uniform computed from difference in positions of feature point of image or templates matching. The existing matching method sampled that the correspondence is presumed to correct by use of the condition which the correct correspondence is almost satisfying, and applied RANSAC by matching the correspondence into one to one, but by sampling in stages in multi probability distribution computed for image in the proposed method, the correct correspondence of high probability can be sampled among multi correspondence candidates effectively. In the result, we could obtain many correct correspondence and verify effectiveness of the proposed method in the simulation and experiment of real images.

• Spatial Information Research
• /
• v.2 no.1
• /
• pp.47-51
• /
• 1994

The purpose of the study is to establ ish models of land Cover (use) prediction system for development and management of land resources using remotely sensed data as well as ancillary data in the context of multi-dis¬ciplinary approach in the application to CheJoo Island. The model adopts multi-date processing techniques and is a spatial/temporal land-Cover projection strategy emerged as a synthesis of the probability tra-nsition model and the discrimnant-analys is model. A discriminant modelis applied to all pixels in CheJoo landscape plane to predict the most likely change in land Cover. The probability transition model provides the number of these pixels that will convert to different land Cover in a given future time increment. The syntheric model predicts the future change in land Cover and its volume of pixels in the landscape plane.

• Journal of Korea Society of Industrial Information Systems
• /
• v.25 no.5
• /
• pp.41-48
• /
• 2020

Recently, as the demand for the mobile platform market in the virtual/augmented/mixed reality field is increasing, experiential content that gives users a real-world felt through a virtual environment is drawing attention. In this paper, as a method of tracking a tracker for user location estimation in a virtual space movement platform for motion capture of trainees, we present a method of estimating 3D coordinates of the 3D cross covariance through the coordinates of the markers projected on the image. In addition, the validity of the proposed algorithm is verified through rigid body tracking experiments.

• KIPS Transactions on Software and Data Engineering
• /
• v.4 no.4
• /
• pp.177-186
• /
• 2015

For data fusion of laser range finder (LRF) and vision camera, accurate calibration of external parameters which describe relative pose between two sensors is necessary. This paper proposes a new calibration method which can acquires more accurate external parameters between a LRF and a vision camera compared to other existing methods. The main motivation of the proposed method is that any corner data of a known 3D structure which is acquired by the LRF should be projected on a straight line in the camera image. To satisfy such constraint, we propose a 3D geometric model and a numerical solution to minimize the energy function of the model. In addition, we describe the implementation steps of the data acquisition of LRF and camera images which are necessary in accurate calibration results. In the experiment results, it is shown that the performance of the proposed method are better in terms of accuracy compared to other conventional methods.