• Journal of Broadcast Engineering
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• v.9 no.3
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• pp.185-195
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• 2004

This paper presents a multi-depth map fusion method for the 3D scene reconstruction. It fuses depth maps obtained from the stereo matching technique and the depth camera. Traditional stereo matching techniques that estimate disparities between two images often produce inaccurate depth map because of occlusion and homogeneous area. Depth map obtained from the depth camera is globally accurate but noisy and provide a limited depth range. In order to get better depth estimates than these two conventional techniques, we propose a depth map fusion method that fuses the multi-depth maps from stereo matching and the depth camera. We first obtain two depth maps generated from the stereo matching of 3-view images. Moreover, a depth map is obtained from the depth camera for the center-view image. After preprocessing each depth map, we select a depth value for each pixel among them. Simulation results showed a few improvements in some background legions by proposed fusion technique.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1286-1301
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• 2003

This paper introduces segmentation based environment modeling method and integration method using multiple environment map for constructing the realtime image-based panoramic navigation system. The segmentation-based environment modeling method is easy to implement on the environment map and can be used for environment modeling by extracting the depth value by the segmentation of the environment map. However, an environment model that is constructed using a single environment map has the problem of a blurring effect caused by the fixed resolution, and the stretching effect of the 3D model caused when information that does not exist on the environment map occurs due to the occlusion. In this paper, we suggest environment models integration method using multiple environment map to resolve the above problem. This method can express parallax effect and expand the environment model to express wide range of environment. The segmentation-based environment modeling method using multiple environment map can build a detail model with optimal resolution.

• Archives of Pharmacal Research
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• v.25 no.5
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• pp.697-703
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• 2002

We investigated that the role of nitric oxide (NO) on ischemic rats in brain and heart. Ischemia was induced by both common carotid arteries (CCA) occlusion for 24h following reperfusion. Then tissue samples were removed and measured NOx. In brain, NOx was increased by about 40% vs. normal and it was significantly inhibited by aminoguanidine, selective iNOS inhibitor. This result showed that NOx concentration was increased by iNOS. We investigated the role of $Ca^{2+}$ during ischemia. Nimodipine, L-type calcium channel blocker, didn't inhibit the increases of NOx concentration during ischemia. It suggested that increased NOx was due to calcium-independent NOS. MK-801, which N-methyl-D-aspartate (NMDA) receptor antagonist, didn't significantly prevent the increases of NOx. In heart, ischemia caused NOx decrease and it is inconsistent with NOx increase in brain. Aminoguanidine and nimodipine didnt affect on NOx decrease. But MK-801 more lowered NOx concentration than those of ischemia control group. It seemed that $Ca^{2+}$ influx in heart partially occurred via NMDA receptor and inhibited by NMDA receptor antagonist. The mean arterial pressure (MAP) in ischemic rats after 24h of CCA occlusion was decreased when compared to normal value, whereas the heart rates (HR) was not different between two groups. Aminoguanidine or MK801 had no effect on MAP or HR, but nimodipine reduced MAP. There was no difference the effects of aminoguanidine, nimodipine, or MK-801, on MAP and HR between normal rats and ischemic rats. In summary, ischemic model caused an increase of NOx concentration, suggesting that this may be produced via iNOS, which is calcium independent in brain. However in heart, ischemia decreased NOx concentration and NMDA receptor was partially involved. The basal MAP was decreased in ischemic rats but HR was not different from normal control, suggesting that increased NOx in brain of ischemic rat may result in the hypotension.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.11
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• pp.899-905
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• 2003

An intermediate images generation method using multi-resolution based hierarchical block matching disparity map is proposed. This method is composed of a disparity estimation, an occlusion detection and intermediate image synthesis. For the disparity estimation, which is one of the important processes in intermediate image synthesis, we use the multi-resolution based hierarchical block matching algorithm to overcome the imperfect ness of block matching algorithm. The proposed method makes disparity maps more accurate and dense by multi-resolution based hierarchical block matching, and the estimated disparity maps are used to generate intermediate images of stereo images. Generated intermediate images show 0.1∼1.4 ㏈ higher PSNR than the images obtained by block matching algorithm.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.06a
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• pp.133-134
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• 2014

Conventional stereo matching algorithms fail when they deal with anaglyph image as its input because anaglyph image does not have similar intensity on both view images. To ameliorate such problems, we propose a robust method to obtain accurate disparity maps. The novel Absolute Adaptive Normalized Cross Correlation (AANCC) for anaglyph data cost is introduced in this paper. Then, it is followed by occlusion detection and segmentation-based plane fitting to achieve accurate depth map acquisition. Experimental results confirm that the proposed anaglyph data cost is robust and gives accurate disparity maps.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.418-422
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• 2009

Generally, algorithms for generating disparity maps can be clssified into two categories: region-based method and feature-based method. The main focus of this research is to generate a disparity map with an accuracy depth information for 3-dimensional reconstructing. Basically, the region-based method and the feature-based method are simultaneously included in the proposed algorithm, so that the existing problems including false matching and occlusion can be effectively solved. As a region-based method, regions of false matching are extracted by the proposed MMAD(Modified Mean of Absolute Differences) algorithm which is a modification of the existing MAD(Mean of Absolute Differences) algorithm. As a feature-based method, the proposed method eliminates false matching errors by calculating the vector with SIFT and compensates the occluded regions by using a pair of adjacent SIFT matching points, so that the errors are reduced and the disparity map becomes more accurate.

• Current Optics and Photonics
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• v.4 no.6
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• pp.545-550
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• 2020

We propose a hole-filling method to solve discontinuous depth representation and to reduce the visible seams and cracks that cause the limitation of the viewing angle of the three-dimensional (3D) image in the multilayer type 3D display system. The occlusion and the disocclusion regions between layers, such as the visible seams and cracks, are a major bottleneck of the multilayer type 3D display system to represent a volumetric 3D image by stacking multiple images. As a result, in the reconstructed 3D image, the visible seams and cracks appear as brighter overlapping and undesirable cut-off. In order to resolve the problems above, we applied the depth-fused effect to the sub-depth map generating algorithm and improve the viewing characteristics of the multilayer type 3D display. The experimental demonstrations are also provided to verify the proposed scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1795-1811
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• 2019

In order to achieve rapid and accurate detection of vehicle objects in complex traffic conditions, we propose a novel vehicle detection method. Firstly, more contextual and small-object vehicle information can be obtained by our Joint Feature Network (JFN). Secondly, our Evolved Region Proposal Network (EPRN) generates initial anchor boxes by adding an improved version of the region proposal network in this network, and at the same time filters out a large number of false vehicle boxes by soft-Non Maximum Suppression (NMS). Then, our Mask Network (MaskN) generates an example that includes the vehicle occlusion, the generator and discriminator can learn from each other in order to further improve the vehicle object detection capability. Finally, these candidate vehicle detection boxes are optimized to obtain the final vehicle detection boxes by the Fine-Tuning Network(FTN). Through the evaluation experiment on the DETRAC benchmark dataset, we find that in terms of mAP, our method exceeds Faster-RCNN by 11.15%, YOLO by 11.88%, and EB by 1.64%. Besides, our algorithm also has achieved top2 comaring with MS-CNN, YOLO-v3, RefineNet, RetinaNet, Faster-rcnn, DSSD and YOLO-v2 of vehicle category in KITTI dataset.

• The Journal of the Korea Contents Association
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• v.11 no.11
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• pp.492-502
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• 2011

20 fossil sites of numerous fossil sites in Korea have been designated as Natural Monument for protection and conservation. Many of the sites which is located at the coastal area have been gradually disfigured by natural weathering, erosion and human activity. Thus the conservation of the original form and the documentation for the original figure are necessary. In this study, we applied 3D digital documentation to Natural Monument No. 394, Haenam Uhangri dinosaur, pterosaur, and bird footprint fossil site, for maintaining the original form of the dinosaur footprints. We were able to obtain the 3D digital data on two dinosaur footprint sites, a high resolution distributional map, and more accurate digital data of the dinosaur footprints applied the rendering method by ambient occlusion. 3D digital data on the dinosaur footprints is worth for the conservation and research data, moreover content for applying to the various fields such as to make 3D brochure, interactive contents, and so on.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.8
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• pp.123-132
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• 2017

Traffic lights contain very important information for safety driving. So, the delivery of the information to drivers in real-time is a very critical issue for advanced driver assistance systems. However, traffic light detection is quite difficult because of the small sized traffic lights and the occlusion in real world. In this paper, a traffic light detection method using modified color based saliency map and morphological information is proposed. It shows 98.14% of precisions and 83.52% of recalls on computer simulations.