• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1666-1669
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• 2002

In the process of creating architectural scenes from photographs using Model-based Stereo 〔1〕, the geometric model is used as prior information to solve correspondence problems and recover the depth or disparity of real scenes. This paper presents an Image Subregioning algorithm that divides left and right images into several rectangular sub-images. The division is done according to the estimated depth of real scenes using a Heuristic Approach. The depth difference between the reality and the model can be partitioned into each depth level. This reduces disparity search range in the Similarity Function. For architectural scenes with complex depth, experiments using the above approach show that accurate disparity maps and better results when rendering scenes can be achieved by the proposed algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.2
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• pp.1-9
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• 2008

In this paper, to extract object regions in stereo image, we propose an enhanced algorithm that extracts objects combining both of brightness information and disparity information. The approach that extracts objects using both has been studied by Ping and Chaohui. In their algorithm, the segmentation for an input image is carried out using the brightness, and integration of segmented regions in consideration of disparity information within the previously segmented regions. In the regions where the brightness values between object regions and background regions are similar, however, the segmented regions probably include both of object regions and background regions. It may cause incorrect object extraction in the merging process executed in the unit of the segmented region. To solve this problem, in proposed method, we adopt the merging process which is performed in pixel unit. In addition, we perform the bi-directional stereo matching process to enhance reliability of the disparity information and supplement the disparity information resulted from a single directional matching process. Further searching for disparity is decided by edge information of the input image. The proposed method gives good performance in the object extraction since we find the disparity information that is not extracted in the traditional methods. Finally, we evaluate our method by experiments for the pictures acquired from a real stereoscopic camera.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.5
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• pp.317-321
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• 2013

This paper proposes a detection algorithm for view reversal in a stereoscopic video using a disparity map and motion vector field. We obtain the disparity map of a stereo image was obtained using a specific stereo matching algorithm and classify the image into the foreground and background. Next, the motion vector field of the image on a block basis was produced using a full search algorithm. Finally, the stereo image was considered to be reversed when the foreground moved toward the background and the covered region was in the foreground. The proposed algorithm achieved a good detection rate when the background was covered sufficiently by its moving foreground.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.143-146
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• 1998

A new stereoscopic codec. structure using MPEG-2 multiview profile is presented in this paper. In the suggested codec., the left image is coded with motion estimation in the base layerand the right image is coded with disparity estimation in the enhancement layer. Since it is possible to calculate rough motion of the right image sequence with disparity and motion of the left image sequence, motion compensation of the enhancement layer is performed without motion estimation. Since the proposed codec. does not perform motion estimation in the enhancement layer encoding, it is simple and reduces the encoding time. We compared the PSNR of encoded image with three different structured codec., and the experimental results show that suggested codec. has comparable with other codecs.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.583-587
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• 2009

In this paper we propose a new method of Depth-Image-Based Rendering (DIBR) for Free-viewpoint TV (FTV). In the proposed method, virtual viewpoint images are rendered with 3D warping instead of estimating the view-dependent depth since depth estimation is usually costly and it is desirable to eliminate it from the rendering process. However, 3D warping causes some problems that do not occur in the method with view-dependent depth estimation; for example, the appearance of holes on the rendered image, and the occurrence of depth discontinuity on the surface of the object at virtual image plane. Depth discontinuity causes artifacts on the rendered image. In this paper, these problems are solved by reconstructing disparity information at virtual camera position from neighboring two real cameras. In the experiments, high quality arbitrary viewpoint images were obtained.

• Journal of Broadcast Engineering
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• v.7 no.3
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• pp.238-247
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• 2002

In this paper, we propose an object-based stereo sequence compression technique using disparity-motion vector relationship. The proposed method uses the coherence of motion vectors and disparity vectors in the left and right Image sequences. After two motion vectors and one disparity vector ate computed using FBMA(Fixed Block Matching Algorithm), the disparity vector of the current stereoscopic pall is computed by disparity-motion vector relationship with vectors which are previously estimated. Moreover, a vector regularization technique is applied in order to obtain reliable vectors. For an object-based coding. the object is defined and coded in terms of layers of VOP such as in MPEG-4. we present a method using disparity and motion vector relationship for extending two-frame compensation into three-frame compensation method for prediction coding of B-VOP. The proposed algorithm shows a high performance when comparing with a conventional method.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.2
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• pp.50-59
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• 2000

Stereo vision is a technique extracting depth information from stereo images, which are two images that view an object or a scene from different locations. The most important procedure in stereo vision, which is called stereo matching, is to find the same points in stereo images. It is difficult to match stereo images in real time because stereo matching requires heavy calculation. In this Paper we design a digital VLSI to Process stereo matching in real time, which we call stereo image match processor (SIMP). For implementation of real time stereo matching, sliding memory and minimum selection tree are presented. SIMP is designed with pipeline architecture and parallel processing. SIMP takes 64 gray level 64$\times$64 stereo images and yields 8 level 64 $\times$64 disparity map by 3 bit disparity and 12 bit address outputs. SIMP can process stereo images with process speed of 240 frames/sec.

• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.63-68
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• 2010

In this paper, we propose a multiresolution stereo matching method based on genetic algorithm using edge information. The proposed approach considers the matching environment as an optimization problem and finds the solution by using a genetic algorithm. A cost function composes of certain constraints which are commonly used in stereo matching. We defines the structure of chromosomes using edge pixel information of reference image of stereo pair. To increase the efficiency of process, we apply image pyramid method to stereo matching and calculate the initial disparity map at the coarsest resolution. Then initial disparity map is propagated to the next finer resolution, interpolated and performed disparity refinement. We valid our approach not only reduce the search time for correspondence but alse ensure the validity of matching.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.4
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• pp.59-64
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• 2001

In this paper it was proposed method that solve problems of method to segment region of zero disparity and algorithm that extract binocular disparity to estimate position of object by vergence movement of moving stereo cameras experimented to compare those. There was not change of density value almost in region that change of critcal value was not found almost in image, because a high critical value was set so that critical value may be kipt changelessly about all small regions in studied treatise so far. The corresponding points were extracted wrongly by the result. By because the characteristics of small region was evaluated by autocorrelation and the critical value was established that may be proportional to the autocorrelation value, it was confirmed that corresponding points are not extracted almost by mistake and binocular disparity could by extracted with high speed.

• Journal of Broadcast Engineering
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• v.17 no.5
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• pp.789-807
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• 2012

The purpose of this paper is to find various disparity factors in conjunction with situations and contexts of the contents that cause viewer's discomfort, which is to make a content production guideline for viewer's safety, eventually. As a methodology, we extract the experimental data by letting various viewers push a pre-defined key as long as they feel discomfort during watching stereo 3D contents. For each contents, we extract the disparities and disparity changes for the focal point, vicinity of the focal point (ROI, region of interest), and the whole image. For each contents, each point or part of contents is analyzed to find the factors causing discomfort with the two prepared data with watching the contents in 3D. Then, all the analyzed data are re-analyzed to find the strength of each factor. The results from the analyses are explained from the factors having relatively high strength first. It includes the factors that are not known as well as the ones that we can already guess.