• 한국정보디스플레이학회:학술대회논문집
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• 2007.08b
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• pp.1504-1507
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• 2007

Depth data for is very important data for 3D display. Disparity and depth data makes users to feel 3D effect. We used stereo camera to measure depth and made fast algorithm to get in real time. This vision system can be substituted for expensive laser system.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.205-206
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• 2007

In stereo vision applications, disparity estimation is often performed to corresponding pixels. Using window-based correlations is a fast and standard approach to the disparity estimation. In this paper, we analyse the behaviour of the correlation-based disparity estimation and improve its performance by combining it with a segmentation scheme. Simulation results demonstrate that the proposed algorithm provides faithful disparity maps.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10C
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• pp.813-819
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• 2008

In this paper, we implemented a real-time system which displays 3-dimensional (3D) stereoscopic image with stereo camera. The system consists of a set of stereo camera, FPGA board, and 3D stereoscopic LCD. Two CMOS image sensor were used for the stereo camera. FPGA which processes video data was designed with Verilog-HDL, and it can accommodate various resolutional videos. The stereoscopic image is configured by two methods which are side-by-side and up-down image configuration. After the left and right images are converted to the type for the stereoscopic display, they are stored into SDRAM. When the next frame is inputted into FPGA from two CMOS image sensors, the previous video data is output to the DA converter for displaying it. From this pipeline operation, the real-time operation is possible. After the proposed system was implemented into hardware, we verified that it operated exactly.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.1A
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• pp.57-63
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• 2012

In this paper, we propose a real-time view interpolation method using virtual viewpoint disparity estimation and convergence check. For the real-time process, we estimate a disparity map at the virtual viewpoint from stereo images using the belief propagation method. This method needs only one disparity map, compared to the conventional methods that need two disparity maps. In the view synthesis part, we warp pixels from the reference images to the virtual viewpoint image using the disparity map at the virtual viewpoint. For real-time acceleration, we utilize a high speed GPU parallel programming, called CUDA. As a result, we can interpolate virtual viewpoint images in real-time.

• Journal of Digital Contents Society
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• v.17 no.6
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• pp.523-529
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• 2016

Stereo matching algorithm is an essential part in computer vision and photography. Accuracy and computational complexity are challenges of stereo matching algorithm. Much research has been devoted to stereo matching based on cost volume filtering of matching costs. Local stereo matching based guided image filtering (GIF) has a computational complexity of O(N), but is still not enough to provide real-time 3-dimensional (3-D) video services. The proposed algorithm concentrates reduction of computational complexity using the concept of fast guided image filter, which increase the speed up to $O(N/\small{s}^2)$ with a sub-sampling ratio $\small{s}$. Experimental results indicated that the proposed algorithm achieves effective local stereo matching as well as a fast execution time for 3-D video service.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.3
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• pp.53-61
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• 2012

This paper proposes a real-time distance measurement system of high temperature and high speed target using infrared stereo camera. We construct an infrared stereo camera system that measure the difference between target and background temperatures for automatic target measurement. First, the proposed method detects target region based on target motion and intensity variation of local region using difference between target and background temperatures. Second, stereo matching by left and right target information is used to estimate disparity about real-time distance of target. In the proposed method using infrared stereo camera system, we compare distances in three dimension trajectory measuring instrument and in infrared stereo camera measurement. In this experiment from three video data, the result shows an average 9.68% distance error rate. The proposed method is suitable for distance and position measurement of varied targets using infrared stereo system.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08b
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• pp.1239-1241
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• 2007

In this paper, we present a tiled display system for tangible meeting. We built our system as a distributed system and use GPU based warping and image blending technique for real-time processing. For efficiency, we update specific area only, where the remote user exist, in real-time and blended it with static panoramic image of remote site.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.3
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• pp.21-29
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• 2011

This paper presents a method that estimates distance and velocity of an object with reliability regardless of maneuver status of the target in stereo vision system. A stereo vision system can calculate a distance with disparity from left and right images. However, the distance estimation error may occur due to quantization error of image pixel. A sub-pixel interpolation method minimizes the quantization error and estimates accurate disparity with real value. Extended Kalman filter (EKF) was used to minimize the error covariance and estimate the object's velocity. However, divergence problem occurs due to model uncertainty when a target maneuvers highly, which makes the estimation error increase. In this paper, we propose a virtual model extended Kalman filter (VMEKF) method that minimizes the processing time and provides reliable estimation ability regardless of maneuver status. Computer simulations and experimental results in real road environments demonstrate that the proposed method gives a reliable estimation performance and reduces processing time under various maneuver status while comparing other estimation filters.

• Journal of Sensor Science and Technology
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• v.19 no.2
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• pp.99-111
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• 2010

This paper proposes an efficient hardware architecture to estimate disparities between 2D images for generating 3D depth images in a stereo vision system. Stereo matching methods are classified into global and local methods. The local matching method uses the cost functions based on pixel windows such as SAD(sum of absolute difference), SSD(sum of squared difference) and NCC(normalized cross correlation). The NCC-based cost function is less susceptible to differences in noise and lighting condition between left and right images than the subtraction-based functions such as SAD and SSD, and for this reason, the NCC is preferred to the other functions. However, software-based implementations are not adequate for the NCC-based real-time stereo matching, due to its numerous complex operations. Therefore, we propose a fast pipelined hardware architecture suitable for real-time operations of the NCC function. By adopting a block-based box-filtering scheme to perform NCC operations in parallel, the proposed architecture improves processing speed compared with the previous researches. In this architecture, it takes almost the same number of cycles to process all the pixels, irrespective of the window size. Also, the simulation results show that its disparity estimation has low error rate.

• 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.