• Journal of Broadcast Engineering
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• v.26 no.3
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• pp.283-295
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• 2021

This paper proposes a method for generating dense depth map using information of color images and depth map generated based on lidar based on self-organizing map. The proposed depth map upsampling method consists of an initial depth prediction step for an area that has not been acquired from LiDAR and an initial depth filtering step. In the initial depth prediction step, stereo matching is performed on two color images to predict an initial depth value. In the depth map filtering step, in order to reduce the error of the predicted initial depth value, a self-organizing map technique is performed on the predicted depth pixel by using the measured depth pixel around the predicted depth pixel. In the process of self-organization map, a weight is determined according to a difference between a distance between a predicted depth pixel and an measured depth pixel and a color value corresponding to each pixel. In this paper, we compared the proposed method with the bilateral filter and k-nearest neighbor widely used as a depth map upsampling method for performance comparison. Compared to the bilateral filter and the k-nearest neighbor, the proposed method reduced by about 6.4% and 8.6% in terms of MAE, and about 10.8% and 14.3% in terms of RMSE.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.2
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• pp.155-160
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• 2014

In this paper, an algorithm using RGB-depth camera is proposed to detect smoke in interrior. RGB-depth camera, the Kinect provides RGB color image and depth information. The Kinect sensor consists of an infra-red laser emitter, infra-red camera and an RGB camera. A specific pattern of speckles radiated from the laser source is projected onto the scene. This pattern is captured by the infra-red camera and is analyzed to get depth information. The distance of each speckle of the specific pattern is measured and the depth of object is estimated. As the depth of object is highly changed, the depth of object plain can not be determined by the Kinect. The depth of smoke can not be determined too because the density of smoke is changed with constant frequency and intensity of infra-red image is varied between each pixels. In this paper, a smoke detection algorithm using characteristics of the Kinect is proposed. The region that the depth information is not determined sets the candidate region of smoke. If the intensity of the candidate region of color image is larger than a threshold, the region is confirmed as smoke region. As results of simulations, it is shown that the proposed method is effective to detect smoke in interior.

• Journal of Ginseng Research
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• v.37 no.2
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• pp.254-260
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• 2013

Greenhouse and field experiments with American ginseng (Panax quinquefolius L.) stratified seed sown at depths of 10 to 100 mm were carried out to determine effects of seeding depth on seedling emergence, growth and development and to calculate optimum seeding depth. The time to 50% seedling emergence ($E_{50}$) in the field increased linearly from 17 d at 20 mm seeding depth to 42.5 d at 80 mm. Seedling emergence and root weight (economic yield) at the end of the first year each increased quadratically with the increase of seeding depth. Maximum emergence and root yields were produced at sowing depths of 26.9 and 30.6 mm respectively. In a greenhouse pot experiment, increasing seeding depth from 10 to 100 mm increased partitioning of dry matter to leaves from 23.6% to 26.1%, to stems from 6.9% to 14.2%, and decreased dry matter to roots from 69.5% to 59.7%. Optimum seeding depth was 31.1 mm for a corresponding maximum root weight of 119.9 mg. A predictor equation [X (seeding depth, mm)=Y (seed weight, mg)/9.1+20.96] for seeding depth for ginseng, based on data for ten vegetable crops, their seed weights and suggested seeding depths, predicted a seeding depth of 28.3 mm for ginseng similar to that reported above for most pot and field experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.1121-1139
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• 2015

In texture-plus-depth format, depth map compression is an important task. Different from normal texture images, depth maps have less texture information, while contain many homogeneous regions separated by sharp edges. This feature will be employed to form an efficient depth map coding scheme in this paper. Firstly, the histogram of the depth map will be analyzed to find an appropriate threshold that segments the depth map into the foreground and background regions, allowing the edge between these two kinds of regions to be obtained. Secondly, the two regions will be encoded through rate distortion optimization with a shape adaptive wavelet transform, while the edges are lossless encoded with JBIG2. Finally, a depth-updating algorithm based on the threshold and the depth range is applied to enhance the quality of the decoded depth maps. Experimental results demonstrate the effective performance on both the depth map quality and the synthesized view quality.

• Journal of The Korean Digital Architecture Interior Association
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• v.3 no.1
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• pp.1-8
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• 2003

Perceiving the depth of space in the spatial organization of architecture is perceiving spaces as well three dimensions as the fourth dimensions -perceive the time-. Physical depth in architectural space differs from perceptional depth in aspects of not only dimension but also perceptional effects. In this study, the perceptional depth is defined as visual depth and physical depth is depth of space. These purposes of this study are classifying the perceptional effects of visual depth -visual access, sense of variety, dynamic and cubic effect... - and the methods of spatial composition which causes visual depth in architectural space.

• Journal of Broadcast Engineering
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• v.24 no.2
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• pp.281-291
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• 2019

Depth from defocus estimates the 3D depth by using a phenomenon in which the object in the focal plane of the camera forms a clear image but the object away from the focal plane produces a blurred image. In this paper, algorithms are studied to estimate 3D depth by analyzing the degree of blur of the image taken with a single camera. The optimized object range was obtained by 3D depth estimation derived from depth from defocus using one image of a single camera or two images of different focus of a single camera. For depth estimation using one image, the best performance was achieved using a focal length of 250 mm for both smartphone and DSLR cameras. The depth estimation using two images showed the best 3D depth estimation range when the focal length was set to 150 mm and 250 mm for smartphone camera images and 200 mm and 300 mm for DSLR camera images.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.1
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• pp.27-33
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• 2016

In this study we propose a method for 3D landform reconstruction and object modeling method by generating contour lines on the map using a depth sensor which abstracts characteristics of geological layers from the depth map. Unlike the common visual camera, the depth-sensor is not affected by the intensity of illumination, and therefore a more robust contour and object can be extracted. The algorithm suggested in this paper first abstracts the characteristics of each geological layer from the depth map image and rearranges it into the proper order, then creates contour lines using the Bezier curve. Using the created contour lines, 3D images are reconstructed through rendering by mapping RGB images of the visual camera. Experimental results show that the proposed method using depth sensor can reconstruct contour map and 3D modeling in real-time. The generation of the contours with depth data is more efficient and economical in terms of the quality and accuracy.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.697-698
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• 2006

In this paper, we propose a new scheme to generate multi-view images using a depth-image-based rendering (DIBR) technique. In order to improve the quality of multi-view images at newly exposed areas during mesh-based rendering, we preprocess the depth map using a Gaussian smoothing filter. Previous algorithms apply a smoothing filter to the whole depth map even if the depth map is collapsed. After extracting objects from the depth map, we apply the smoothing filter to their boundaries. Finally, we cannot only maintain the depth quality, but also generate high quality multi-view images. Experimental results show that our proposed algorithm outperforms previous works and supports an efficient depth keying technique.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3558-3577
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• 2017

In 2D-to-3D video conversion process, the virtual left and right view can be generated from 2D video and its corresponding depth map by depth image based rendering (DIBR). The depth map plays an important role in conversion system, so the copyright protection for depth map is necessary. However, the provided virtual views may be distributed illegally and the depth map does not directly expose to viewers. In previous works, the copyright information embedded into the depth map cannot be extracted from virtual views after the DIBR process. In this paper, a new copyright protection scheme for the depth map is proposed, in which the copyright information can be detected from the virtual views even without the depth map. The experimental results have shown that the proposed method has a good robustness against JPEG attacks, filtering and noise.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.02a
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• pp.347-347
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• 2011

Secondary ion mass spectrometry (SIMS) was fascinated by a quantitative analysis and a depth profiling and it was convinced of a in-depth analysis of multi-layer films. Precision determination of the interfaces of multi-layer films is important for conversion from the original SIMS depth profiling to the compositional depth profiling and the investigation of structure of multi-layer films. However, the determining of the interface between two kinds of species of the SIMS depth profile is distorted from original structure by the several effects due to sputtering with energetic ions. In this study, the feasibility of 50 atomic % definition for the determination of interface between two kinds of species in SIMS depth profiling of multilayer films was investigated by Si/Ge and Ti/Si multi-layer films. The original SIMS depth profiles were converted into compositional depth profiles by the relative sensitivity factors from Si-Ge and Si-Ti alloy reference films. The atomic compositions of Si-Ge and Si-Ti alloy films determined by Rutherford backscattering spectroscopy (RBS).