• 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 Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.25-32
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• 2004

We propose a hierarchical disparity estimation algorithm with edge-preserving energy-based regularization. Initial disparity vectors are obtained from downsampled stereo images using a feature-based region-dividing disparity estimation technique. Dense disparities are estimated from these initial vectors with shape-adaptive windows in full resolution images. Finally, the vector fields are regularized with the minimization of the energy functional which considers both fidelity and smoothness of the fields. The first two steps provide highly reliable disparity vectors, so that local minimum problem can be avoided in regularization step. The proposed algorithm generates accurate disparity map which is smooth inside objects while preserving its discontinuities in boundaries. Experimental results are presented to illustrate the capabilities of the proposed disparity estimation technique.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.3
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• pp.1-10
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• 2008

An occupancy map is a representation methodology describing the region occupied by objects in 3D space, which can be utilized for autonomous navigation and object recognition. In this paper, we describe a technique for building an occupancy map using depth data extracted from stereo images. In addition, some techniques are proposed for utilizing the occupancy map for the segmentation of object regions. After the geometric information on the ground plane is extracted from a disparity image, the occupancy map is constructed by projecting each matched point to the ground plane-based 3D space. We explain techniques for extracting moving object regions using the occupancy map and present experimental results using real stereo images.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.51-59
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• 2012

This paper suggests an efficient method which tracks articulated human body modeled with markov network using disparity map derived from stereo images. The conventional methods which only use color information to calculate likelihood for energy function tend to fail when background has same colors with objects or appearances of object are changed during the movement. In this paper, we present a method evaluating likelihood with both disparity information and color information to find human body parts. Since the human body part are cylinder projected to rectangles in 2D image plane, we use the properties of distribution of disparity of those rectangles that do not have discontinuous distribution. In addition to that we suggest a conditional-messages-update that is able to reduce unnecessary message update of belief propagation. Since the message update has comprised over 80% of the whole computation in belief propagation, the conditional-message-update yields 9~45% of improvements of computational time. Furthermore, we also propose an another speed up method called three dimensional dynamic models assumed the body motion is continuous. The experiment results show that the proposed method reduces the computational time as well as it increases tracking accuracy.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.6
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• pp.86-96
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• 2010

In this paper, we propose stereo vision-based obstacle detection and vehicle verification methods using U-disparity map and bird's-eye view mapping. First, we extract a road feature using maximum frequent values in each row and column. And we extract obstacle areas on the road using the extracted road feature. To extract obstacle areas exactly we utilize U-disparity map. We can extract obstacle areas exactly on the U-disparity map using threshold value which consists of disparity value and camera parameter. But there are still multiple obstacles in the extracted obstacle areas. Thus, we perform another processing, namely segmentation. We convert the extracted obstacle areas into a bird's-eye view using camera modeling and parameters. We can segment obstacle areas on the bird's-eye view robustly because obstacles are represented on it according to ranges. Finally, we verify the obstacles whether those are vehicles or not using various vehicle features, namely road contacting, constant horizontal length, aspect ratio and texture information. We conduct experiments to prove the performance of our proposed algorithms in real traffic situations.

• Journal of the Korea Society of Computer and Information
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• v.14 no.6
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• pp.117-123
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• 2009

In this paper, An algorithm which converts 2D video frames into 3D video frames of parallel looking stereo camea is proposed. The proposed algorithm finds the disparity information between two consecutive video frames and generates 3D video frames from the obtained disparity maps. The disparity information is obtained from the modified iterative convergence algorithm. The method of generating 3D video frames from the disparity information is also proposed. The proposed algorithm uses coherence method which overcomes the video pattern based algorithms.

• Journal of Broadcast Engineering
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• v.20 no.4
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• pp.545-556
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• 2015

A HEVC-compatible 3D video coding method (3D-HEVC) has been recently developed as an extension of the high efficiency video coding (HEVC) standard. In order to efficiently deal with the multi-view video plus depth (MVD) format, 3D-HEVC exploits an inter-component prediction which allows the prediction between texture and depth map images in addition to a temporal prediction used in the conventional single layer video coding such as H.264/AVC and HEVC. The performance of the inter-component prediction is normally affected by the accuracy of the disparity vector, and thus it is important to have an accurate disparity vector used for the inter-component prediction. This paper, therefore, introduces a disparity derivation method and inter-component algorithms using the disparity vector for the efficient 3D video coding. Simulation results show that the 3D-HEVC provides higher coding performance compared with the simulcast approach using HEVC and the simple multi-view extension (MH-HEVC).

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.12
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• pp.659-666
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• 2000

A stereo matching has been an important tool for reconstructing three dimensional terrain. By using stereo matching technique, DEM(Digital Elevaton Map) can be generated by the disparity from a reference image to a target image. Generally disparity map can be evaluated by matching the reference image to the target image and if the role of the reference and the target are interchanged, a different DEM can be obtained. In this paper, we propose a new fusion technique to estimate the optimal DEM by eliminating the false DEM due to occlusion. To detect the false DEM, we utilize two measure of accuracy: self-consistency and cross-correlation score. We test the effectiveness of the proposed methods with a quantitative analysis using simulated images. Experimental result indicate that the proposed methods show 24.4% and 33.1% improvement over either DEM.

• 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.

• Journal of Sensor Science and Technology
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• v.29 no.2
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• pp.123-127
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• 2020

In this paper, the estimation of the disparity for depth extraction in monochrome complementary metal-oxide-semiconductor (CMOS) image sensors with offset pixel apertures is presented. To obtain the depth information, the disparity information between two different channel data of the offset pixel apertures is required. The disparity is caused by the difference in the response angle between the left- and right-offset pixel aperture images. A depth map is implemented by the generated disparity. Therefore, the disparity is the most important factor for realizing 3D images from the designed CMOS image sensor with offset pixel apertures. The disparity is influenced by the pixel height and offset value of the offset pixel aperture. To confirm this correlation, the offset value is set to maximum within the pixel area, and the disparity values corresponding to the difference in the heights are calculated and compared. The disparity is derived using the camera-lens formula. Two monochrome CMOS image sensors with offset pixel apertures are used in the disparity estimation.