• Journal of Broadcast Engineering
• /
• v.14 no.3
• /
• pp.366-377
• /
• 2009

In this paper, we implement the real-time system which extracts 3-dimensional coordinates from right and left images captured by a stereo camera and provides users with reality through a virtual space operated by the 3-dimensional coordinates. In general, all pixels in correspondence region are compared for the disparity estimation. However, for a real time process, the central coordinates of the correspondence region are only used in the proposed algorithm. In the implemented system, 3D coordinates are obtained by using the depth information derived from the estimated disparity and we set user's hand as a region of interest(ROI). After user's hand is detected as the ROI, the system keeps tracking a hand's movement and generates a virtual space that is controled by the hand. Experimental results show that the implemented system could estimate the disparity in real -time and gave the mean-error less than 0.68cm within a range of distance, 1.5m. Also It had more than 90% accuracy in the hand recognition.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.9 no.5
• /
• pp.1225-1233
• /
• 2008

In this paper, the 2D/3D converting algorithm is proposed. The single frame of 2D image is used fur the real-time processing of the proposed algorithm. The proposed algorithm creates a 3D image with the depth map by using the vertical position information of a object in a single frame. In order to real-time processing and improve the hardware complexity, it performs the generation of a depth map using the image sampling, the object segmentation with the luminance standardization and the boundary scan. It might be suitable to a still image and a moving image, and it can provide a good 3D effect on a image such as a long distance image, a landscape, or a panorama photo because it uses a vertical position information. The proposed algorithm can adapt a 3D effect to a image without the restrictions of the direction, velocity or scene change of an object. It has been evaluated with the visual test and the comparing to the MTD(Modified Time Difference) method using the APD(Absolute Parallax Difference).

• Journal of Internet Computing and Services
• /
• v.10 no.4
• /
• pp.25-33
• /
• 2009

In the paper, we proposed a new system to retrieve 3D wrinkle data based on stereo images. Usually, 3D reconstruction based on stereo images or video is very popular and it is the research focus, which has been applied for culture heritage, building and other scene. The target is object measurement, the scene depth calculation and 3D data obtained. There are several challenges in our research. First, it is hard to take the full information wrinkle images by cameras because of light influence, skin with non-rigid object and camera performance. We design a particular computer vision system to take winkle images with a long length camera lens. Second, it is difficult to get the dense stereo data because of the hard skin texture image segmentation and corner detection. We focus on semi-dense stereo matching algorithm for the wrinkle depth. Compared with the 3D scanner, our system is much cheaper and compared with the physical modeling based method, our system is more flexible with high performance.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.43 no.1 s.307
• /
• pp.45-52
• /
• 2006

In this paper, a real-time stereoscopic image conversion method using a single frame from a 2-D image is proposed. The Stereoscopic image is generated by creating depth map using vortical position information and parallax processing. For a real-time processing of stereoscopic conversion and reduction of hardware complexity, it uses image sampling, object segmentation by standardizing luminance and depth map generation by boundary scan. The proposed method offers realistic 3-D effect regardless of the direction, velocity and scene conversion of the 2-D image. It offers effective stereoscopic conversion using images suitable conditions assumed in this paper such as recorded image at long distance, landscape and panorama photo because it creates different depth sense using vertical position information from a single frame. The proposed method can be applied to still image because it uses a single frame from a 2-D image. The proposed method has been evaluated using visual test and APD for comparing the stereoscopic image of the proposed method with that of MTD. It is confirmed that stereoscopic images conversed by the proposed method offers 3-D effect regardless of the direction and velocity of the 2-D image.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.18 no.6
• /
• pp.1321-1330
• /
• 2023

This study attempts to address the problem of 3D pose estimation for multiple human objects through a single image generated during the character development process that can be used in augmented reality. In the existing top-down method, all objects in the image are first detected, and then each is reconstructed independently. The problem is that inconsistent results may occur due to overlap or depth order mismatch between the reconstructed objects. The goal of this study is to solve these problems and develop a single network that provides consistent 3D reconstruction of all humans in a scene. Integrating a human body model based on the SMPL parametric system into a top-down framework became an important choice. Through this, two types of collision loss based on distance field and loss that considers depth order were introduced. The first loss prevents overlap between reconstructed people, and the second loss adjusts the depth ordering of people to render occlusion inference and annotated instance segmentation consistently. This method allows depth information to be provided to the network without explicit 3D annotation of the image. Experimental results show that this study's methodology performs better than existing methods on standard 3D pose benchmarks, and the proposed losses enable more consistent reconstruction from natural images.

• Journal of Information Processing Systems
• /
• v.9 no.2
• /
• pp.333-348
• /
• 2013

Mobile authentication/identification has grown into a priority issue nowadays because of its existing outdated mechanisms, such as PINs or passwords. In this paper, we introduce gait recognition by using a mobile accelerometer as not only effective but also as an implicit identification model. Unlike previous works, the gait recognition only performs well with a particular mobile specification (e.g., a fixed sampling rate). Our work focuses on constructing a unique adaptive mechanism that could be independently deployed with the specification of mobile devices. To do this, the impact of the sampling rate on the preprocessing steps, such as noise elimination, data segmentation, and feature extraction, is examined in depth. Moreover, the degrees of agreement between the gait features that were extracted from two different mobiles, including both the Average Error Rate (AER) and Intra-class Correlation Coefficients (ICC), are assessed to evaluate the possibility of constructing a device-independent mechanism. We achieved the classification accuracy approximately $91.33{\pm}0.67%$ for both devices, which showed that it is feasible and reliable to construct adaptive cross-device gait recognition on a mobile phone.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.37 no.6
• /
• pp.725-736
• /
• 2013

This study segments information users according to depth and variety of use diffusion in order to differentiate between the influence of fashion information spread and diffusions from each segmented group. Data were collected from a fashion community to perform a social network analysis that used UCINET 6.0. Members completed the survey materials and the network materials were utilized in the analysis to test the hypothesis. The segmented groups of information users determined the study results according to use diffusion and the variables that affect them. The variables affecting information diffusion outcomes indicate different significant influence factors on each segmented market. Information variety and complexity represents elevated information reproductions and verbal acceptances from information diffusion outcomes.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.39 no.3
• /
• pp.11-22
• /
• 2002

The design of optimal filter yielding optimal texture feature separation is a most effective technique in many torture analyzing areas, such as perception of surface, object, shape and depth. But, most optimal filter design approaches are restricted to the issue of computational complexity and supervised problems. In this paper, Our proposed method yields new insight into the design of optimal Gabor filters for segmenting multiple texture images. The optimal frequency of Gator filter is turned to the optimal frequency of the distinct texture in frequency domain. In order to show the performance of the designed filters, we have attempted to build a various texture images. Our experimental results show that the performance of the system is very successful.

• Journal of Korean Library and Information Science Society
• /
• v.43 no.4
• /
• pp.113-137
• /
• 2012

This study aims to provide marketing strategies for the public libraries in Korea. For this purpose, this study focused on four public libraries in New York, USA, which have been providing the most excellent library services on the world. And this study examined what efforts these libraries have been making for the development of community and information needs of customers. The data for this study were collected by literature review, participant observation at the public libraries in New York, and gathering law materials. And in-depth interviews with the librarians and related professionals in New York and Korea were also proceeded. As a result, this study suggested marketing strategies for the management of public libraries in Korea.

• Journal of Korea Multimedia Society
• /
• v.19 no.6
• /
• pp.1003-1013
• /
• 2016

This paper proposes a framework of superpixel-based vehicle detection method using plane normal vector in disparity space. We utilize two common factors for detecting vehicles: Hypothesis Generation (HG) and Hypothesis Verification (HV). At the stage of HG, we set the regions of interest (ROI) by estimating the lane, and track them to reduce computational cost of the overall processes. The image is then divided into compact superpixels, each of which is viewed as a plane composed of the normal vector in disparity space. After that, the representative normal vector is computed at a superpixel-level, which alleviates the well-known problems of conventional color-based and depth-based approaches. Based on the assumption that the central-bottom of the input image is always on the navigable region, the road and obstacle candidates are simultaneously extracted by the plane normal vectors obtained from K-means algorithm. At the stage of HV, the separated obstacle candidates are verified by employing HOG and SVM as for a feature and classifying function, respectively. To achieve this, we trained SVM classifier by HOG features of KITTI training dataset. The experimental results demonstrate that the proposed vehicle detection system outperforms the conventional HOG-based methods qualitatively and quantitatively.