• 제목/요약/키워드: stereo image

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Evaluation of Digital Elevation Models by Interpreting Correlations (상관관계 해석을 통한 수치표고모델 평가 방법)

  • Lee, Seung-Woo;Oh, Hae-Seok
    • The KIPS Transactions:PartB
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    • v.11B no.2
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    • pp.141-148
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    • 2004
  • The ground positions and elevations information called DEMs(Digital Elevation Models) which are extracted from the stereo aerial photographs and/or satellite images using image matching method have the natural errors caused by variant environments. This study suggests the method to evaluate DEMs using correlation values between the reference and the target DEMs. This would be strongly helpful for experts to correct these errors. To evaluate the whole area of DEMs in the horizontal and vertical errors, the target cell is matched for each reference cell using the correlation values of these two cells. When the target cell is matched for each reference cell, horizontal and vertical error was calculated so as to help experts to recognize a certain area of DEMs which should be corrected and edited. If the correlation value is low and tile difference in height is high, the target cell will be candidated as changed or corrupted cell. When the area is clustered with those candidated cells, that area will be regarded as changed or corrupted area to be corrected and edited. Using this method, the evaluation for all DEM cells is practicable, the horizontal errors as well as vertical errors is calculable and the changed or corrupted area can be detected more efficiently.

Images Grouping Technology based on Camera Sensors for Efficient Stitching of Multiple Images (다수의 영상간 효율적인 스티칭을 위한 카메라 센서 정보 기반 영상 그룹핑 기술)

  • Im, Jiheon;Lee, Euisang;Kim, Hoejung;Kim, Kyuheon
    • Journal of Broadcast Engineering
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    • v.22 no.6
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    • pp.713-723
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    • 2017
  • Since the panoramic image can overcome the limitation of the viewing angle of the camera and have a wide field of view, it has been studied effectively in the fields of computer vision and stereo camera. In order to generate a panoramic image, stitching images taken by a plurality of general cameras instead of using a wide-angle camera, which is distorted, is widely used because it can reduce image distortion. The image stitching technique creates descriptors of feature points extracted from multiple images, compares the similarities of feature points, and links them together into one image. Each feature point has several hundreds of dimensions of information, and data processing time increases as more images are stitched. In particular, when a panorama is generated on the basis of an image photographed by a plurality of unspecified cameras with respect to an object, the extraction processing time of the overlapping feature points for similar images becomes longer. In this paper, we propose a preprocessing process to efficiently process stitching based on an image obtained from a number of unspecified cameras for one object or environment. In this way, the data processing time can be reduced by pre-grouping images based on camera sensor information and reducing the number of images to be stitched at one time. Later, stitching is done hierarchically to create one large panorama. Through the grouping preprocessing proposed in this paper, we confirmed that the stitching time for a large number of images is greatly reduced by experimental results.

A Experimental Study on the 3-D Image Restoration Technique of Submerged Area by Chung-ju Dam (충주댐 수몰지구의 3차원 영상복원 기법에 관한 실험적 연구)

  • 연상호
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.22 no.1
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    • pp.21-27
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    • 2004
  • It will be a real good news fer the people who were lost their hometown by the construction of a large dam to be restored to the farmer state. Focused on Cheung-pyung around where most part were submerged by the Chungju large Dam founded in eurly 1980s, It used remote sensing image restoration Technique in this study in order to restore topographical features before the flood with stereo effects. We gathered comparatively good satellite photos and remotely sensed digital images, then its made a new fusion image from these various satellite images and the topographical map which had been made before the water filled by the DAM. This task was putting together two kinds of different timed images. And then, we generated DEM including the outskirts of that area as matching current contour lines with the map. That could be a perfect 3D image of test areas around before when it had been water filled by making perspective images from all directions included north, south, east and west, fer showing there in 3 dimensions. Also, for close range visiting made of flying simulation can bring to experience their real space at that time. As a result of this experimental task, it made of new fusion images and 3-D perspective images and simulation live images by remotely sensed photos and images, old paper maps about vanished submerged Dam areas and gained of possibility 3-D terrain image restoration about submerged area by large Dam construction.

Quantitative Assessment of 3D Reconstruction Procedure Using Stereo Matching (스테레오 정합을 이용한 3차원 재구성 과정의 정량적 평가)

  • Woo, Dong-Min
    • Journal of IKEEE
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    • v.17 no.1
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    • pp.1-9
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    • 2013
  • The quantitative evaluation of DEM(Digital Elevation Map) is very important to the assessment of the effectiveness for the applied 3D image analysis technique. This paper presents a new quantitative evaluation method of 3D reconstruction process by using synthetic images. The proposed method is based on the assumption that a preacquired DEM and ortho-image should be the pseudo ground truth. The proposed evaluation process begins by generating a pair of photo-realistic synthetic images of the terrain from any viewpoint in terms of application of the constructed ray tracing algorithm to the pseudo ground truth. By comparing the DEM obtained by a pair of photo-realistic synthetic images with the assumed pseudo ground truth, we can analyze the quantitative error in DEM and evaluate the effectiveness of the applied 3D analysis method. To verify the effectiveness of the proposed evaluation method, we carry out the quantitative and the qualitative experiments. For the quantitative experiment, we prove the accuracy of the photo-realistic synthetic image. Also, the proposed evaluation method is experimented on the 3D reconstruction with regards to the change of the matching window. Based on the fact that the experimental result agrees with the anticipation, we can qualitatively manifest the effectiveness of the proposed evaluation method.

Implementation of Random Controlling of Convergence Point in VR Image Content Production (VR 영상콘텐츠 제작을 위한 컨버전스 포인트 임의조절 구현)

  • Jin, Hyung Woo;Baek, Gwang Ho;Kim, Mijin
    • Smart Media Journal
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    • v.4 no.4
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    • pp.111-119
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    • 2015
  • As a variety of HMD(Head Mounted Display) has come out, the production of 3D images onto which VR(Virtual Reality) technologies are grafted has been contributed to activating the production of image contents depending on a tangible or immersing type. VR-based image contents have enlarged their applicability across the entertainment industry from animation and game to realistic images. At the same time, the solution development for producing VR image contents has also gained elasticity. However, among those production solutions which have been used until now, fixed stereo camera based photographing has a limit that the binocular disparity of a user is fixed. This does not only restrict a way of expression a producer intends to direct, but also may cause the effect of 3D or space not to be sensed enough as view condition is not considered enough in a user's side. This study is aimed at resolving with skills applying in the latter part of 3D image production the problem that convergence points may be adjusted with restriction, which tends to happen at the time of the production of VR image contents. The later stage of the 3D imaging work analyzes and applies to game engines the significance of adjusting convergence points through the visualization of binocular disparity so that it is available to implement a function that the points could be controlled at random by a user.

An Epipolar Rectification for Object Segmentation (객체분할을 위한 에피폴라 Rectification)

  • Jeong, Seung-Do;Kang, Sung-Suk;CHo, Jung-Won;Choi, Byung-Uk
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.1C
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    • pp.83-91
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    • 2004
  • An epipolar rectification is the process of transforming the epipolar geometry of a pair of images into a canonical form. This is accomplished by applying a homography to each image that maps the epipole to a predetermined point. In this process, rectified images transformed by homographies must be satisfied with the epipolar constraint. These homographies are not unique, however, we find out homographies that are suited to system's purpose by means of an additive constraint. Since the rectified image pair be a stereo image pair, we are able to find the disparity efficiently. Therefore, we are able to estimate the three-dimensional information of objects within an image and apply this information to object segmentation. This paper proposes a rectification method for object segmentation and applies the rectification result to the object segmentation. Using color and relative continuity of disparity for the object segmentation, the drawbacks of previous segmentation method, which are that the object is segmented to several region because of having different color information or another object is merged into one because of having similar color information, are complemented. Experimental result shows that the disparity of result image of proposed rectification method have continuity about unique object. Therefore we have confirmed that our rectification method is suitable to the object segmentation.

HMM-based Intent Recognition System using 3D Image Reconstruction Data (3차원 영상복원 데이터를 이용한 HMM 기반 의도인식 시스템)

  • Ko, Kwang-Enu;Park, Seung-Min;Kim, Jun-Yeup;Sim, Kwee-Bo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.2
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    • pp.135-140
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    • 2012
  • The mirror neuron system in the cerebrum, which are handled by visual information-based imitative learning. When we observe the observer's range of mirror neuron system, we can assume intention of performance through progress of neural activation as specific range, in include of partially hidden range. It is goal of our paper that imitative learning is applied to 3D vision-based intelligent system. We have experiment as stereo camera-based restoration about acquired 3D image our previous research Using Optical flow, unscented Kalman filter. At this point, 3D input image is sequential continuous image as including of partially hidden range. We used Hidden Markov Model to perform the intention recognition about performance as result of restoration-based hidden range. The dynamic inference function about sequential input data have compatible properties such as hand gesture recognition include of hidden range. In this paper, for proposed intention recognition, we already had a simulation about object outline and feature extraction in the previous research, we generated temporal continuous feature vector about feature extraction and when we apply to Hidden Markov Model, make a result of simulation about hand gesture classification according to intention pattern. We got the result of hand gesture classification as value of posterior probability, and proved the accuracy outstandingness through the result.

Entropy-Based 6 Degrees of Freedom Extraction for the W-band Synthetic Aperture Radar Image Reconstruction (W-band Synthetic Aperture Radar 영상 복원을 위한 엔트로피 기반의 6 Degrees of Freedom 추출)

  • Hyokbeen Lee;Duk-jin Kim;Junwoo Kim;Juyoung Song
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1245-1254
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    • 2023
  • Significant research has been conducted on the W-band synthetic aperture radar (SAR) system that utilizes the 77 GHz frequency modulation continuous wave (FMCW) radar. To reconstruct the high-resolution W-band SAR image, it is necessary to transform the point cloud acquired from the stereo cameras or the LiDAR in the direction of 6 degrees of freedom (DOF) and apply them to the SAR signal processing. However, there are difficulties in matching images due to the different geometric structures of images acquired from different sensors. In this study, we present the method to extract an optimized depth map by obtaining 6 DOF of the point cloud using a gradient descent method based on the entropy of the SAR image. An experiment was conducted to reconstruct a tree, which is a major road environment object, using the constructed W-band SAR system. The SAR image, reconstructed using the entropy-based gradient descent method, showed a decrease of 53.2828 in mean square error and an increase of 0.5529 in the structural similarity index, compared to SAR images reconstructed from radar coordinates.

Pallet Measurement Method for Automatic Pallet Engaging in Real-Time (자동 화물처리를 위한 실시간 팔레트 측정 방법)

  • Byun, Sung-Min;Kim, Min-Hwan
    • Journal of Korea Multimedia Society
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    • v.14 no.2
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    • pp.171-181
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    • 2011
  • A vision-based method for positioning and orienting of pallets is presented in this paper, which guides autonomous forklifts to engage pallets automatically. The method uses a single camera mounted on the fork carriage instead of two cameras for stereo vision that is conventionally used for positioning objects in 3D space. An image back-projection technique for determining the orient of a pallet without any fiducial marks is suggested in tins paper, which projects two feature lines on the front plane of the pallet backward onto a virtual plane that can be rotated around a given axis in 3D space. We show the fact that the rotation angle of the virtual plane on which the back-projected feature lines are parallel can be used to describe the orient of the pallet front plane. The position of the pallet is determined by using ratio of the distance between the back-projected feature lines and their real distance on the pallet front plane. Through a test on real pallet images, we found that the proposed method was applicable to real environment practically in real-time.

Fast Disparity Estimation Method Considering Temporal and Spatial Redundancy Based on a Dynamic Programming (시.공간 중복성을 고려한 다이내믹 프로그래밍 기반의 고속 변이 추정 기법)

  • Yun, Jung-Hwan;Bae, Byung-Kyu;Park, Se-Hwan;Song, Hyok;Kim, Dong-Wook;Yoo, Ji-Sang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.10C
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    • pp.787-797
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    • 2008
  • In this paper, we propose a fast disparity estimation method considering temporal and spatial redundancy based on a dynamic programming for stereo matching. For the first step, the dynamic programming is performed to estimate disparity vectors with correlation between neighboring pixels in an image. Next, we efficiently compensate regions, which disparity vectors are not allocated, with neighboring disparity vectors assuming that disparity vectors in same object are quite similar. Moreover, in case of video sequence, we can decrease a complexity with temporal redundancy between neighboring frames. For performance comparison, we generate an intermediate-view image using the estimated disparity vector. Test results show that the proposed algorithm gives $0.8{\sim}2.4dB$-increased PSNR(peak signal to noise ratio) compared to a conventional block matching algorithm, and the proposed algorithm also gives approximately 0.1dB-increased PSNR and $48{\sim}68%$-lower complexity compared to the disparity estimation method based on general dynamic programming.