• 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.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.11
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• pp.899-905
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• 2003

An intermediate images generation method using multi-resolution based hierarchical block matching disparity map is proposed. This method is composed of a disparity estimation, an occlusion detection and intermediate image synthesis. For the disparity estimation, which is one of the important processes in intermediate image synthesis, we use the multi-resolution based hierarchical block matching algorithm to overcome the imperfect ness of block matching algorithm. The proposed method makes disparity maps more accurate and dense by multi-resolution based hierarchical block matching, and the estimated disparity maps are used to generate intermediate images of stereo images. Generated intermediate images show 0.1∼1.4 ㏈ higher PSNR than the images obtained by block matching algorithm.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.3
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• pp.175-182
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• 2017

In this paper, we present a multi-depth generation method using a time-of-flight (ToF) fusion camera system. Multi-view color cameras in the parallel type and ToF depth sensors are used for 3D scene capturing. Although each ToF depth sensor can measure the depth information of the scene in real-time, it has several problems to overcome. Therefore, after we capture low-resolution depth images by ToF depth sensors, we perform a post-processing to solve the problems. Then, the depth information of the depth sensor is warped to color image positions and used as initial disparity values. In addition, the warped depth data is used to generate a depth-discontinuity map for efficient stereo matching. By applying the stereo matching using belief propagation with the depth-discontinuity map and the initial disparity information, we have obtained more accurate and stable multi-view disparity maps in reduced time.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1817_1818
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• 2009

Disparity 맵은 스테레오 카메라의 이미지 평면에 동일한 3차원 포인터를 나타내는 픽셀간의 차이를 나타내는 이미지이다. 이는 3차원 정보를 얻기 위하여 생성 한며 생성된 Disparity 맵은 Triangulation을 이용하여 3차원 복원이 가능하다. Disparity 맵은 픽셀의 intensity의 차를 이용하여 구하므로 Repeated Pattern 이나 Textureless 부분에서 많은 에러가 생기는 문제가 있다. 본 논문에서는 이런 문제점을 해결하기 위하여 싱글 카메라와 레이저 레인지 파인더의 캘리브레이션을 통해 알아낸 기하학적인 관계를 이용하여 3차원 정보를 카메라의 이미지 평면으로 역 사영 시켜서 Disparity 맵을 생성하는 알고리즘을 제안한다. 이 방법은 기존의 스트레오 카메라 기반으로 Disparity 맵을 생성하는 경우에 생기는 Repeated Pattern 이나 Textureless 부분의 문제를 해결 할 수 있다는 것을 실험을 통하여 검증 하였다.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.428-435
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• 2017

In this paper, we propose a novel motion field estimation algorithm for which a U-disparity map and forward-and-backward error removal are applied in a vehicular environment. Generally, a motion exists in an image obtained by a camera attached to a vehicle by vehicle movement; however, the obtained motion vector is inaccurate because of the surrounding environmental factors such as the illumination changes and vehicles shaking. It is, therefore, difficult to extract an accurate motion vector, especially on the road surface, due to the similarity of the adjacent-pixel values; therefore, the proposed algorithm first removes the road surface region in the obtained image by using a U-disparity map, and uses then the optical flow that represents the motion vector of the object in the remaining part of the image. The algorithm also uses a forward-backward error-removal technique to improve the motion-vector accuracy and a vehicle's movement is predicted through the application of the RANSAC (RANdom SAmple Consensus) to the previously obtained motion vectors, resulting in the generation of a motion field. Through experiment results, we show that the performance of the proposed algorithm is superior to that of an existing algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.7
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• pp.36-48
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• 2010

This paper is concerned with stereo vision-based approach to detect obstacles and to generate the path of destination from the start. The hexapod robot in the experiment is cable of walking by legs and driving by wheels simultaneously. The hexapod robot operates under the driving mode normally, and it changes driving mode to walking mode to overcome obstacles using its legs. Disparity map, which is the correlation between two images taken by stereo camera, is employed for calculation of the distance between the robot and obstacles. When the obstacles information is extracted from the disparity map, the potential field algorithm is applied to create the obstacle-avoidance path. Simulator, based on OpenGL, is developed to generate the graphical path, and the experimental results are shown for the verification of the proposed algorithm.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.904-907
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• 2002

In this paper, we describe an algorithm to automatically generate an intermediate scene using the bidirectional disparity morphing from the parallel stereopair. To compute the disparity between two reference images, we use the 2-step fast block matching algorithm that restricts the searching range and accelerates the speed of the computation of the disparity. We also define three occluding patterns so as to smooth the computed disparities, especially for occluded regions. They are derived from the peculiar properties of the disparity map. The smoothed disparity maps present that the false disparities are well corrected and the boundary between foreground and background becomes sharper. We discuss the advantages of this algorithm compared to the commonly used schemes and we show some experimental results with real data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.201-208
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• 2015

3D image must have depth image for depth information in order for 3D realistic media broadcasting. We used generally belief propagation algorithm to solve probability model. Belief propagation algorithm is operated by message passing between nodes corresponding to each pixel. The high resolution image will be able to precisely represent but that required much computational complexity for 3D representation. We proposed fast stereo matching algorithm using belief propagation with multi-resolution based wavelet or lifting. This method can be shown efficiently computational time at much iterations for accurate disparity map.

• Journal of Broadcast Engineering
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• v.14 no.2
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• pp.164-177
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• 2009

The DIBR(depth image-based rendering) method gives the sense of depth to viewers by using one color image and corresponding depth image. At this time, the qualities of the generated left- and right-image depend on the baseline distance of the virtual cameras corresponding to the view of the generated left- and right-image. In this paper, we present a novel method for enhancing the sense of depth by adjusting baseline distance of virtual cameras. Geometric analysis shows that the sense of depth is better in accordance with the increasing disparity due to the reduction of the image distortion. However, the entailed image degradation is not considered. Experimental results show that there is maximum bound in the disparity increasement due to image degradation and the visual field. Since the image degradation is reduced for increasing that bound, we add a depth map preprocessing. Since the interactive service where the disparity and view position are controlled by viewers can also be provided, the proposed method can be applied to the mobile broadcasting system such as DMB as well as 3DTV system.