• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.620-624
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• 2009

In this paper, we present a new camera system combining a high-quality 3-D scanner and hybrid camera system to generate a multiview video-plus-depth. In order to get the 3-D video using the hybrid camera system and 3-D scanner, we first obtain depth information for background region from the 3-D scanner. Then, we get the depth map for foreground area from the hybrid camera system. Initial depths of each view image are estimated by performing 3-D warping with the depth information. Thereafter, multiview depth estimation using the initial depths is carried out to get each view initial disparity map. We correct the initial disparity map using a belief propagation algorithm so that we can generate the high-quality multiview disparity map. Finally, we refine depths of the foreground boundary using extracted edge information. Experimental results show that the proposed depth maps generation method produces a 3-D video with more accurate multiview depths and supports more natural 3-D views than the previous works.

• Journal of the Korean association of regional geographers
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• v.10 no.3
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• pp.606-623
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• 2004

Emergency medical service pertains highly to the public service sector which has to be provided equally in a society and evenly in a spatial dimension by the government. However, emergency medical centers in Korea are inequally distributed in a space and also human capital, facility, and equipment for emergency medical centers show clear disparity among regions. This research analyzed the spatial balance of the demand supply level for emergency medical service in Seoul by constructing the potential demand surface map and supply surface map for this service. The surface map of demand-supply balance for emergency medical service was constructed by GIS based map algebra algorism. The results by this analysis very clearly reveal the spatial disparity of emergency medical service. The places where are over-represented by demand level compared to their supply level are estimated to require an additional establishment of emergency medical centers in the near future. While, the places where are over-represented by supply level compared to their potential demand for emergency medical services indicate the possibility of problems in the management of emergency medical centers because of a surplus in the supply of emergency medical services. The results of this research can be utilized in providing valuable information for the adequate provision of emergency medical centers and for the estimation of range on the service area of emergency medical services.

• 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.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.3
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• pp.143-150
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• 2008

In this paper, we investigate a real-time environment recognition system based on stereo vision for moving object. This system consists of stereo matching, obstacle detection and distance estimation. In stereo matching part, depth maps can be obtained real road images captured adjustable baseline stereo vision system using belief propagation(BP) algorithm. In detection part, various obstacles are detected using only depth map in case of both v-disparity and column detection method under the real road environment. Finally in estimation part, asymmetric parabola fitting with NCC method improves estimation of obstacle detection. This stereo vision system can be applied to many applications such as unmanned vehicle and robot.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.01a
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• pp.59-62
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• 2011

A new method is proposed for stereo vision where solution to disparity map is presented in terms of Line constraint and Reliability space -- the first constraint proposes a progressive framework for stereo matching which applies local area pixel-values from corresponding lines in the left and right image pairs. The second states that reliability space based on corresponding points records the disparity and then we are able to apply the median filter in order to reduce the noises which occur in the process. A coarse to fine result is presented after the median filtering, which improves the final result qualitatively. Experiment is evaluated by rectified stereo matching images pairs from Middlebury datasets and has proved that those two adopted strategies yield good matching quantitative results in terms of fast running speed.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.433-434
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• 2006

A new disparity estimation method in hierarchical frameworks is proposed. The two main ideas for improving accuracy are to obtain an object boundary map for distinction of homogeneous/object boundary region and to choose adaptive window size/shapes. Moreover, for the reduction of computational complexity, we change reference regions in hierarchical framework. The experimental results show that the proposed method can acquire good results which are robust to homogeneous and object boundary regions.

• Korean Journal of Remote Sensing
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• v.25 no.3
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• pp.287-294
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• 2009

KOMPSAT-2 like other high-resolution satellites has the time and angle difference in the acquisition of the panchromatic (PAN) and multispectral (MS) images because the imaging systems have the offset of the charge coupled device combination in the focal plane. Due to the differences, high altitude and moving objects, such as clouds, have a different position between the PAN and MS images. Therefore, a mis-registration between the PAN and MS images occurs when a registration algorithm extracted matching points from these cloud objects. To overcome this problem, we proposed a new registration method. The main idea is to discard the matching points extracted from cloud boundaries by using an automatic thresholding technique and a classification technique on a distance disparity map of the matching points. The experimental result demonstrates the accuracy of the proposed method at ground region around cloud objects is higher than a general method which does not consider cloud objects. To evaluate the proposed method, we use KOMPSAT-2 cloudy images.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.241-243
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• 2010

Previous approaches to the 2D to 3D conversion problem require heavy computation or considerable amount of user input. In this paper, we propose a rather simple method in estimating the depth map from a single image using a monocular depth cue: haze. Using the haze imaging model, we obtain the distance information and estimate a reliable depth map from a single scenery image. Using the depth map, we also suggest an algorithm that converts the single image to 3D stereoscopic images. We determine a disparity value for each pixel from the original 'left' image and generate a corresponding 'right' image. Results show that the algorithm gives well refined depth maps despite the simplicity of the approach.

• Journal of the Semiconductor & Display Technology
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• v.10 no.3
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• pp.99-103
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• 2011

The stereoscopic vision system is the algorithm to obtain the depth of target object of stereo vision image. This paper presents an efficient disparity matching method using blue edge filter and graph cut algorithm. We do recommend the use of the simple sobel edge operator. The application of B band sobel edge operator over image demonstrates result with somewhat noisy (distinct border). The basic technique is to construct a specialized graph for the energy function to be minimized such that the minimum cut on the graph also minimizes the energy (either globally or locally). This method has the advantage of saving a lot of data. We propose a preprocessing effective stereo matching method based on sobel algorithm which uses blue edge information and the graph cut, we could obtain effective depth map.

• Journal of the Semiconductor & Display Technology
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• v.9 no.3
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• pp.65-69
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• 2010

The stereoscopic vision system is the algorithm to obtain the depth of target object of stereo vision image. This paper presents an efficient disparity matching method using nagao filter, octree color quantization and dynamic programming algorithm. we describe methods for performing color quantization on full color RGB images, using an octree data structure. This method has the advantage of saving a lot of data. We propose a preprocessing stereo matching method based on Nagao-filter algorithm using color information. using the nagao filter, we could obtain effective depth map and using the octree color quantization, we could reduce the time of computation.