• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.10
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• pp.920-927
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• 2013

Chroma key technique which composes images by separating an object from its background in specific color has restrictions on color and space. Especially, unlike general chroma key technique, image composition for stereo 3D display requires natural image composition method in 3D space. The thesis attempted to compose images in 3D space using depth keying method which uses high resolution depth information. High resolution depth map was obtained through camera calibration between the DSLR and Kinect sensor. 3D mesh model was created by the high resolution depth information and mapped with RGB color value. Object was converted into point cloud type in 3D space after separating it from its background according to depth information. The image in which 3D virtual background and object are composed obtained and played stereo 3D images using a virtual camera.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.8-17
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• 2011

Recently, fusion camera systems that consist of depth sensors and color cameras have been widely developed with the advent of a new type of sensor, time-of-flight (TOF) depth sensor. The physical limitation of depth sensors usually generates low resolution images compared to corresponding color images. Therefore, the pre-processing module, such as camera calibration, three dimensional warping, and hole filling, is necessary to generate the high resolution depth map that is placed in the image plane of the color image. However, the result of the pre-processing step is usually inaccurate due to errors from the camera calibration and the depth measurement. Therefore, in this paper, we present a depth map upsampling method robust these errors. First, the confidence of the measured depth value is estimated by the interrelation between the color image and the pre-upsampled depth map. Then, the detailed depth map can be generated by the modified kernel regression method which exclude depth values having low confidence. Our proposed algorithm guarantees the high quality result in the presence of the camera calibration errors. Experimental comparison with other data fusion techniques shows the superiority of our proposed method.

• Textile Coloration and Finishing
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• v.21 no.4
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• pp.63-67
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• 2009

m-Aramid dissolved in N,N-dimethylacetamide (DMAc), were coagulated in different coagulants such as water, methanol, ethanol, propanol and butanol. Various concentrations and temperatures of the coagulants were also used to evaluate dyeing properties of coagulated m-aramid films. Field emission scanning electron microscopy (FE-SEM) was employed to investigate the surface morphology of m-aramid films. Wide angle X-ray diffraction (WAXD) was conducted in order to measure crystallinity change of mcaramid fibers and films. WAXD patterns showed that crystallinity of m-aramid fibers was reduced after film formation. In addition, color depth (K/S value) was measured and the results revealed that the film coagulated in water possessed fairly enhanced color depth.

• Archives of design research
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• v.15 no.3
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• pp.167-180
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• 2002

This study investigates effective ways to help users form a correct mental model of the hierarchical information space (HIS) in small display. The focus is the effect of color cue on understanding the structure and navigating the information space. The concept of color space (CS) corresponds well to the HIS - one color has a unique position in the CS as a piece of information does in HIS. In this study, we empirically examined two types of color cue, namely, categorical and depth cue. Hue was used as a categorical cue and tone was used as a depth cue. In our experiment, we evaluate the effectiveness of the color cues in the mobile internet system. Subjects were asked to perform four searching tasks and four comparison tasks. The results of experiment reveal that the categorical cues significantly improve the user's mental model whereas decrease navigation performances. The depth cues cannot aid in understanding the HIS as well as improve navigation performances. This study concludes with limitations of the study and descriptions of future studies.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.194-202
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• 2008

This paper describes a new method for indoor environment mapping and localization with stereo camera. For environmental modeling, we directly use the depth and color information in image pixels as visual features. Furthermore, only the depth and color information at horizontal centerline in image is used, where optical axis passes through. The usefulness of this method is that we can easily build a measure between modeling and sensing data only on the horizontal centerline. That is because vertical working volume between model and sensing data can be changed according to robot motion. Therefore, we can build a map about indoor environment as compact and efficient representation. Also, based on such nodes and sensing data, we suggest a method for estimating mobile robot positioning with random sampling stochastic algorithm. With basic real experiments, we show that the proposed method can be an effective visual navigation algorithm.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.965-972
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• 2020

Depth maps have distance information of objects. They play an important role in organizing 3D information. Color and depth images are often simultaneously obtained. However, depth images have lower resolution than color images due to limitation in hardware technology. Therefore, it is useful to upsample depth maps to have the same resolution as color images. In this paper, we propose a novel method to upsample depth map by shifting the pixel position instead of compensating pixel value. This approach moves the position of the pixel around the edge to the center of the edge, and this process is carried out in several steps to restore blurred depth map. The experimental results show that the proposed method improves both quantitative and visual quality compared to the existing methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4A
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• pp.239-249
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• 2012

Recently, the virtual view generation method using depth data is employed to support the advanced stereoscopic and auto-stereoscopic displays. Although depth data is invisible to user at 3D video rendering, its accuracy is very important since it determines the quality of generated virtual view image. Many works are related to such depth enhancement exploiting a time-of-flight (TOF) camera. In this paper, we propose a fast 3D scene capturing system using one TOF camera at center and two high-resolution cameras at both sides. Since we need two depth data for both color cameras, we obtain two views' depth data from the center using the 3D warping technique. Holes in warped depth maps are filled by referring to the surrounded background depth values. In order to reduce mismatches of object boundaries between the depth and color images, we used the joint bilateral filter on the warped depth data. Finally, using two color images and depth maps, we generated 10 additional intermediate images. To realize fast capturing system, we implemented the proposed system using multi-threading technique. Experimental results show that the proposed capturing system captured two viewpoints' color and depth videos in real-time and generated 10 additional views at 7 fps.

• 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.

• The Research Journal of the Costume Culture
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• v.4 no.3
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• pp.349-359
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• 1996

The research was designed to find out the effects of design elements ; ①color, ②pattern, on image perception of clothing by using a qualitative depth interview method. The subjects were 40 women who lived in Taejon and aged 20 to 40. The interview results were both hand recorded and tape recorded for further analysis by researchers and judge groups. And the results were as follows. 1. The most preferred colors appeared to be blue and black, while stripes, checks and flowers were most favorite patterns. 2. There were individual difference in color and pattern perception, however the color image of yellow was brightness, red was dashing, green comfortable, blue cool, and black tightness. The image of geometric pattern was modesty and natural motif pattern was dynamics. 3. The tow major forces which affected the image of design elements were appeared as followed : 1) Color images affected by the image of natural objects which obtained the color. 2) Individuals past experience and emotional status also affected the personal image perception. 4. The color and pattern preference for the Koran traditional customes and Western tow piece were significantly different and this result imply cultural stereotyping on image perception of design elements. On conclusion, the results supported the research model of form perception and image evaluation.