• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12C
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• pp.1147-1153
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• 2009

We propose a novel image segmentation and segment-based stereo matching technique using color, depth, and motion information. Proposed technique firstly splits reference images into foreground region or background region using depth information from depth camera. Then each region is segmented into small segments with color information. Moreover, extracted segments in current frame are tracked in the next frame in order to maintain depth consistency between frames. The initial depth from the depth camera is also used to set the depth search range for stereo matching. Proposed segment-based stereo matching technique was compared with conventional one without foreground and background separation and other conventional one without motion tracking of segments. Simulation results showed that the improvement of segment extraction and depth estimation consistencies by proposed technique compared to conventional ones especially at the static background region.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.224-241
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• 2015

Multiview plus depth (MVD) videos are widely used in free-viewpoint TV systems. The best-known technique to determine depth information is based on stereo vision. In this paper, we propose a novel local stereo matching algorithm which is radiometric invariant. The key idea is to use a combined matching cost of intensity and gradient based similarity measure. In addition, we realize an adaptive cost aggregation scheme by constructing an adaptive support window for each pixel, which can solve the boundary and low texture problems. In the disparity refinement process, we propose a four-step post-processing technique to handle outliers and occlusions. Moreover, we conduct stereo reconstruction tests to verify the performance of the algorithm more intuitively. Experimental results show that the proposed method is effective and robust against local radiometric distortion. It has an average error of 5.93% on the Middlebury benchmark and is compatible to the state-of-art local methods.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.817-818
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• 2008

In the present paper we propose a new method of intermediate view reconstruction between stereo images using belief propagation_based stereo matching. Intermediate view reconstruction is an important step for multiview 3D display. Many previous paper about intermediate view reconstruction using depth information to synthesize interview though stereo matching were proposed. But depth information is different to estimated accurately. In the present paper, in order to obtain accurate depth information, belief propagation_based stereo matching was used.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.3
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• pp.13-18
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• 2011

In this paper, we explain capturing, postprocessing, and depth generation methods using multiple color and depth cameras. Although the time-of-flight (TOF) depth camera measures the scene's depth in real-time, there are noises and lens distortion in the output depth images. The correlation between the multi-view color images and depth images is also low. Therefore, it is essential to correct the depth images and then we use them to generate the depth information of the scene. The results of stereo matching based on the disparity information from the depth cameras showed the better performance than the previous method. Moreover, we obtained the accurate depth information even at the occluded or textureless regions which are the weaknesses of stereo matching.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.2
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• pp.99-105
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• 2017

Generally, stereo matching methods are used to estimate depth information based on color and spatial similarity. However, most depth estimation methods suffer from the occlusion region because occlusion regions cause inaccurate depth information. Moreover, they do not consider the temporal dimension when estimating the disparity. In this paper, we propose a temporal stereo matching method, considering occlusion and disregarding inaccurate temporal depth information. First, we apply a global stereo matching algorithm to estimate the depth information, we segment the image to occlusion and non-occlusion regions. After occlusion detection, we fill the occluded region with a reasonable disparity value that are obtained from neighboring pixels of the current pixel. Then, we apply a temporal disparity estimation method using the reliable information. Experimental results show that our method detects more accurate occlusion regions, compared to a conventional method. The proposed method increases the temporal consistency of estimated disparity maps and outperforms per-frame methods in noisy images.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.10
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• pp.874-880
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• 2002

A number of techniques have been proposed for 3D display using view-difference of two eyes. These methods do not express enough reality like real world. The display images have to change according to the position of a viewer to improve reality. In this paper, we present an approach for generating intermediate image between two different view images by applying new image interpolation algorithm The interpolation algorithm is designed to cope with complex shapes. The proposed image interpolation algorithm generates rotated image about vertical axes by any angle from base images. Each base image that was obtained from CCD camera has an view-angle difference of $3^{\circ}C$, $5.5^{\circ}C$, $^{\circ}C$, $22^{\circ}C$, and $45^{\circ}C$. The proposed into mediate image generation method uses the geometric analysis of image and depth information through the block-based matching method.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2228-2230
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• 1998

This paper presents the development of depth extraction algorithm for the stereoscopic endoscope data using a stereo matching method. generally, the purpose of existing stereo algorithms is to reconstruct stereo object surface and depth map. but the main purpose of our processing is to give exact depth feeling to doctor showing depth information in some points. for this purpose, this paper presents two stereo matching algorithms which are to measure exact depth. one is using variable window, and the other is reference points-based algorithm for a fast processing.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.256-267
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• 2017

An active research area in computer vision, stereo matching is aimed at obtaining three-dimensional (3D) information from a stereo image pair captured by a stereo camera. To extract accurate 3D information, a number of studies have examined stereo matching algorithms that employ adaptive support weight. Among them, the adaptive census transform (ACT) algorithm has yielded a relatively strong matching capability. The drawbacks of the ACT, however, are that it produces low matching accuracy at the border of an object and is vulnerable to noise. To mitigate these drawbacks, this paper proposes and analyzes the features of an improved stereo matching algorithm that not only enhances matching accuracy but also is also robust to noise. The proposed algorithm, based on the ACT, adopts the truncated absolute difference and the multiple sparse windows method. The experimental results show that compared to the ACT, the proposed algorithm reduces the average error rate of depth maps on Middlebury dataset images by as much as 2% and that is has a strong robustness to noise.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.541-541
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• 2000

This paper Presents the method of 3D reconstruction of the depth information from the endoscopic stereo scopic images. After camera modeling to find camera parameters, we peformed feature-point based stereo matching to find depth information. Acquired some depth information is finally 3D reconstructed using the NURBS(Non Uniform Rational B-Spline) algorithm. The final result image is helpful for the understanding of depth information visually.