• Title/Summary/Keyword: disparity map

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Refinements of Multi-sensor based 3D Reconstruction using a Multi-sensor Fusion Disparity Map (다중센서 융합 상이 지도를 통한 다중센서 기반 3차원 복원 결과 개선)

  • Kim, Si-Jong;An, Kwang-Ho;Sung, Chang-Hun;Chung, Myung-Jin
    • The Journal of Korea Robotics Society
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    • v.4 no.4
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    • pp.298-304
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    • 2009
  • This paper describes an algorithm that improves 3D reconstruction result using a multi-sensor fusion disparity map. We can project LRF (Laser Range Finder) 3D points onto image pixel coordinatesusing extrinsic calibration matrixes of a camera-LRF (${\Phi}$, ${\Delta}$) and a camera calibration matrix (K). The LRF disparity map can be generated by interpolating projected LRF points. In the stereo reconstruction, we can compensate invalid points caused by repeated pattern and textureless region using the LRF disparity map. The result disparity map of compensation process is the multi-sensor fusion disparity map. We can refine the multi-sensor 3D reconstruction based on stereo vision and LRF using the multi-sensor fusion disparity map. The refinement algorithm of multi-sensor based 3D reconstruction is specified in four subsections dealing with virtual LRF stereo image generation, LRF disparity map generation, multi-sensor fusion disparity map generation, and 3D reconstruction process. It has been tested by synchronized stereo image pair and LRF 3D scan data.

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Estimation of Disparity Map having Reliability to Changes of Radiometric (Radiometric 특성 변화에 신뢰성을 가지는 Disparity Map 예측)

  • Shin, Kwang-mu;Kim, Sung-min;Cho, Mi-sook;Chung, Ki-dong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.10a
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    • pp.93-96
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    • 2015
  • The aim of the estimation of disparity map is to find the corresponding pixels from similar two or more images. However, it is a difficult problem to get precise and consistent disparity under a variety of real world situations. In other words, the color values of stereo images are easily influenced by radiometric properties such as illumination direction, illumination color, and camera exposure. Therefore, conventional stereo matching methods can have low performances under radiometric conditions. In this paper, we propose an approaching of disparity map estimation that is reliable in controlling various radiometric variations close to the real environment. This method is motivated by following constancy. Even though each other has different radiometric property in stereo images, intensity of pixels of object have general constancy in specific block. Experimental results show that the proposed method has better performances compared to the comparison group under different radiometric conditions between stereo images. Consequentially, the proposed method is able to estimate the disparity map in stable under various radiometric variations.

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Hierarchical Stereo Matching with Color Information (영상의 컬러 정보를 이용한 계층적 스테레오 정합)

  • Kim, Tae-June;Yoo, Ji-Sang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.3C
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    • pp.279-287
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    • 2009
  • In this paper, a hierarchical stereo matching with color information is proposed. To generate an initial disparity map, feature based stereo matching is carried out and to generate a final disparity map, hierarchical stereo matching is carried out. The boundary (edge) region is obtained by segmenting a given image into R, G, B and White components. From the obtained boundary, disparity is extracted. The initial disparity map is generated when the extracted disparity is spread to the surrounding regions by evaluating autocorrelation from each color region. The initial disparity map is used as an initial value for generating the final disparity map. The final disparity map is generated from each color region by changing the size of a block and the search range. 4 test images that are provided by Middlebury stereo vision are used to evaluate the performance of the proposed algorithm objectively. The experiment results show better performance compared to the Graph-cuts and Dynamic Programming methods. In the final disparity map, about 11% of the disparities for the entire image were inaccurate. It was verified that the boundary for the non-contiguous point was clear in the disparity map.

Estimation of Disparity Map using MMAD and SIFT (MMAD와 SIFT를 이용한 디스패리티 맵 생성)

  • Shin, Do-Kyung;Moon, Young-Shik
    • Proceedings of the Korean Information Science Society Conference
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    • 2007.10c
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    • pp.510-515
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    • 2007
  • 2차원 영상으로부터 3차원 정보를 획득하기 위해서는 disparity map의 정확한 계산이 요구된다. Disparity map을 구하기 위한 기존의 알고리즘은 크게 상관도 기반 방법과 특징 기반 방법으로 분류되는데, 본 논문에서는 이들 각 방법에 대한 분석을 통해서 좀 더 정확한 disparity map을 구하는 방법을 모색한다. 이를 위해 스테레오 카메라로부터 획득된 2차원 영상에서 건물에 대한 깊이 정보 추출을 위해 SIFT 기법을 이용한 disparity map 생성 알고리즘을 제안한다. 제안된 기법은 수정된 MAD인 MMAD(Modified Mean of Absolute Differences) 알고리즘을 새로 제안하여 영역 기반의 유사도 측정을 기반으로 하면서 특징 기반 방법의 하나인 SIFT를 적용하여 거짓 정합(false matching)에 의한 에러를 줄이고 폐색(occlusion) 영역에 대한 오류를 보정한 disparity map을 생성하는데 초점을 둔다.

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View interpolation using Bidirectional Disparity Map (Bidirectional disparity map을 이용한 view interpolation)

  • 김대현;김정훈;김상훈;서민정;홍현기;최종수
    • Proceedings of the IEEK Conference
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    • 2001.06d
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    • pp.65-68
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    • 2001
  • In this paper, we propose a method to interpolate two images obtained from two parallel cameras. The proposed method uses BDM(Bidirectional Disparity Map) to prevent hole generation due to occlusion. Furthermore, we use the block-based DM(Disparity Map) to decrease the amount of computation, and also use the adaptive block size to minimize the error of the block-based DM.

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Head Pose Estimation by using Morphological Property of Disparity Map

  • Jun, Se-Woong;Park, Sung-Kee;Lee, Moon-Key
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.735-739
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    • 2005
  • This paper presents a new system to estimate the head pose of human in interactive indoor environment that has dynamic illumination change and large working space. The main idea of this system is to suggest a new morphological feature for estimating head angle from stereo disparity map. When a disparity map is obtained from stereo camera, the matching confidence value can be derived by measurements of correlation of the stereo images. Applying a threshold to the confidence value, we also obtain the specific morphology of the disparity map. Therefore, we can obtain the morphological shape of disparity map. Through the analysis of this morphological property, the head pose can be estimated. It is simple and fast algorithm in comparison with other algorithm which apply facial template, 2D, 3D models and optical flow method. Our system can automatically segment and estimate head pose in a wide range of head motion without manual initialization like other optical flow system. As the result of experiments, we obtained the reliable head orientation data under the real-time performance.

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Refinement of Disparity Map using the Rule-based Fusion of Area and Feature-based Matching Results

  • Um, Gi-Mun;Ahn, Chung-Hyun;Kim, Kyung-Ok;Lee, Kwae-Hi
    • Proceedings of the KSRS Conference
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    • 1999.11a
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    • pp.304-309
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    • 1999
  • In this paper, we presents a new disparity map refinement algorithm using statistical characteristics of disparity map and edge information. The proposed algorithm generate a refined disparity map using disparity maps which are obtained from area and feature-based Stereo Matching by selecting a disparity value of edge point based on the statistics of both disparity maps. Experimental results on aerial stereo image show the better results than conventional fusion algorithms in the disparity error. This algorithm can be applied to the reconstruction of building image from the high resolution remote sensing data.

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Development of Stereo Microsope Measurement System through the Line Disparity Map (Line Disparity Map을 활용한 스테레오 현미경 측정 시스템 개발)

  • Park, Chan;Jeong, Ji-Seong;Kwon, Ki-Chul;Kim, Nam;Han, Jae-Jong;Im, Myoung-Sook;Jang, Rae-Hyun;Yoo, Kwan-Hee
    • Proceedings of the Korea Contents Association Conference
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    • 2011.05a
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    • pp.499-500
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    • 2011
  • Line Disparity Map[1]은 스테레오 영역기반 정합방법에서 블록단위의 영역이 아닌 라인의 기울기를 바탕으로 비교하기 때문에 실시간 스테레오 정합이 가능하다. 따라서 본 논문은 이러한 Line Disparity Map 알고리즘을 사용하여 단순히 관찰로만 사용되어 지는 입체현미경에 스테레오 비전을 기반으로 하는 3D 형상계측 시스템을 개발하여 사람이 손으로 측정하기 힘든 미세의 오브젝트를 측정하는 시스템을 개발하고자 한다.

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Hole-filling Based on Disparity Map for DIBR

  • Liu, Ran;Xie, Hui;Tian, Fengchun;Wu, Yingjian;Tai, Guoqin;Tan, Yingchun;Tan, Weimin;Li, Bole;Chen, Hengxin;Ge, Liang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.10
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    • pp.2663-2678
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    • 2012
  • Due to sharp depth transition, big holes may be found in the novel view that is synthesized by depth-image-based rendering (DIBR). A hole-filling method based on disparity map is proposed. One important aspect of the method is that the disparity map of destination image is used for hole-filling, instead of the depth image of reference image. Firstly, the big hole detection based on disparity map is conducted, and the start point and the end point of the hole are recorded. Then foreground pixels and background pixels are distinguished for hole-dilating according to disparity map, so that areas with matching errors can be determined and eliminated. In addition, parallaxes of pixels in the area with holes and matching errors are changed to new values. Finally, holes are filled with background pixels from reference image according to these new parallaxes. Experimental results show that the quality of the new view after hole-filling is quite well; and geometric distortions are avoided in destination image, in contrast to the virtual view generated by depth-smoothing methods and image inpainting methods. Moreover, this method is easy for hardware implementation.

Boundary-preserving Stereo Matching based on Confidence Region Detection and Disparity Map Refinement (신뢰 영역 검출 및 시차 지도 재생성 기반 경계 보존 스테레오 매칭)

  • Yun, In Yong;Kim, Joong Kyu
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.5
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    • pp.132-140
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    • 2016
  • In this paper, we propose boundary-preserving stereo matching method based on adaptive disparity adjustment using confidence region detection. To find the initial disparity map, we compute data cost using the color space (CIE Lab) combined with the gradient space and apply double cost aggregation. We perform left/right consistency checking to sort out the mismatched region. This consistency check typically fails for occluded and mismatched pixels. We mark a pixel in the left disparity map as "inconsistent", if the disparity value of its counterpart pixel differs by a value larger than one pixel. In order to distinguish errors caused by the disparity discontinuity, we first detect the confidence map using the Mean-shift segmentation in the initial disparity map. Using this confidence map, we then adjust the disparity map to reduce the errors in initial disparity map. Experimental results demonstrate that the proposed method produces higher quality disparity maps by successfully preserving disparity discontinuities compared to existing methods.