• Title/Summary/Keyword: Multi-Vision

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A Study on Design and Interpretation of Pattern Laser Coordinate Tracking Method for Curved Screen Using Multiple Cameras (다중카메라를 이용한 곡면 스크린의 패턴 레이저 좌표 추적 방법 설계와 해석 연구)

  • Jo, Jinpyo;Kim, Jeongho;Jeong, Yongbae
    • Journal of Platform Technology
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    • v.9 no.4
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    • pp.60-70
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    • 2021
  • This paper proposes a method capable of stably tracking the coordinates of a patterned laser image in a curved screen shooting system using two or more channels of multiple cameras. This method can track and acquire target points very effectively when applied to a multi-screen shooting method that can replace the HMD shooting method. Images of curved screens with severe deformation obtained from individual cameras are corrected through image normalization, image binarization, and noise removal. This corrected image is created and applied as an Euclidean space map that is easy to track the firing point based on the matching point. As a result of the experiment, the image coordinates of the pattern laser were stably extracted in the curved screen shooting system, and the error of the target point position of the real-world coordinate position and the broadband Euclidean map was minimized. The reliability of the proposed method was confirmed through the experiment.

Parallel Implementations of Digital Focus Indices Based on Minimax Search Using Multi-Core Processors

  • HyungTae, Kim;Duk-Yeon, Lee;Dongwoon, Choi;Jaehyeon, Kang;Dong-Wook, Lee
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.2
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    • pp.542-558
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    • 2023
  • A digital focus index (DFI) is a value used to determine image focus in scientific apparatus and smart devices. Automatic focus (AF) is an iterative and time-consuming procedure; however, its processing time can be reduced using a general processing unit (GPU) and a multi-core processor (MCP). In this study, parallel architectures of a minimax search algorithm (MSA) are applied to two DFIs: range algorithm (RA) and image contrast (CT). The DFIs are based on a histogram; however, the parallel computation of the histogram is conventionally inefficient because of the bank conflict in shared memory. The parallel architectures of RA and CT are constructed using parallel reduction for MSA, which is performed through parallel relative rating of the image pixel pairs and halved the rating in every step. The array size is then decreased to one, and the minimax is determined at the final reduction. Kernels for the architectures are constructed using open source software to make it relatively platform independent. The kernels are tested in a hexa-core PC and an embedded device using Lenna images of various sizes based on the resolutions of industrial cameras. The performance of the kernels for the DFIs was investigated in terms of processing speed and computational acceleration; the maximum acceleration was 32.6× in the best case and the MCP exhibited a higher performance.

Lotte Shopping's Marketing Strategy for Achieving the Goal of Becoming a Global Leader (글로벌 기업 도약을 위한 롯데쇼핑의 마케팅전략)

  • Lee, Jinyong;Kim, Chung Koo;Joo, Young-Hyuck
    • Asia Marketing Journal
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    • v.12 no.1
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    • pp.81-101
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    • 2010
  • Lotte Shopping Co. started its business from Lotte Department Store. From the beginning, Lotte Shopping Co. opened the largest department store and, since then, has expanded its business size through the processes of active developments of its own stores and merges and acquisitions of other companies. Currently, it operates a variety of retail shops such as department stores, discount stores, movies theaters, shopping malls, and supermarkets along with a TV home-shopping station and an online shopping mall. Lotte group, a business conglomerate Lotte Shopping belongs to, has an objective of becoming TOP 10 business group in Asia by 2018. Lotte group declared its vision statements in 2009 and has spent its effort to accomplish the goal. Lotte Shopping is implementing the group-level growth strategy through merges and acquisitions and diverse marketing programs. We will briefly investigate the current situation of Lotte Shopping and will then analyze its 1) entertainment shopping center and multi-channel strategy, 2) global market entry, and 3) education system.

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Dual-stream Co-enhanced Network for Unsupervised Video Object Segmentation

  • Hongliang Zhu;Hui Yin;Yanting Liu;Ning Chen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.4
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    • pp.938-958
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    • 2024
  • Unsupervised Video Object Segmentation (UVOS) is a highly challenging problem in computer vision as the annotation of the target object in the testing video is unknown at all. The main difficulty is to effectively handle the complicated and changeable motion state of the target object and the confusion of similar background objects in video sequence. In this paper, we propose a novel deep Dual-stream Co-enhanced Network (DC-Net) for UVOS via bidirectional motion cues refinement and multi-level feature aggregation, which can fully take advantage of motion cues and effectively integrate different level features to produce high-quality segmentation mask. DC-Net is a dual-stream architecture where the two streams are co-enhanced by each other. One is a motion stream with a Motion-cues Refine Module (MRM), which learns from bidirectional optical flow images and produces fine-grained and complete distinctive motion saliency map, and the other is an appearance stream with a Multi-level Feature Aggregation Module (MFAM) and a Context Attention Module (CAM) which are designed to integrate the different level features effectively. Specifically, the motion saliency map obtained by the motion stream is fused with each stage of the decoder in the appearance stream to improve the segmentation, and in turn the segmentation loss in the appearance stream feeds back into the motion stream to enhance the motion refinement. Experimental results on three datasets (Davis2016, VideoSD, SegTrack-v2) demonstrate that DC-Net has achieved comparable results with some state-of-the-art methods.

Fast and Efficient Implementation of Neural Networks using CUDA and OpenMP (CUDA와 OPenMP를 이용한 빠르고 효율적인 신경망 구현)

  • Park, An-Jin;Jang, Hong-Hoon;Jung, Kee-Chul
    • Journal of KIISE:Software and Applications
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    • v.36 no.4
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    • pp.253-260
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    • 2009
  • Many algorithms for computer vision and pattern recognition have recently been implemented on GPU (graphic processing unit) for faster computational times. However, the implementation has two problems. First, the programmer should master the fundamentals of the graphics shading languages that require the prior knowledge on computer graphics. Second, in a job that needs much cooperation between CPU and GPU, which is usual in image processing and pattern recognition contrary to the graphic area, CPU should generate raw feature data for GPU processing as much as possible to effectively utilize GPU performance. This paper proposes more quick and efficient implementation of neural networks on both GPU and multi-core CPU. We use CUDA (compute unified device architecture) that can be easily programmed due to its simple C language-like style instead of GPU to solve the first problem. Moreover, OpenMP (Open Multi-Processing) is used to concurrently process multiple data with single instruction on multi-core CPU, which results in effectively utilizing the memories of GPU. In the experiments, we implemented neural networks-based text extraction system using the proposed architecture, and the computational times showed about 15 times faster than implementation on only GPU without OpenMP.

Retrieval Spectral Albedo using red and NIR band of SPOT/VGT

  • Lee, Chang Suk;Seo, Min Ji;Han, Kyung-Soo
    • Korean Journal of Remote Sensing
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    • v.30 no.3
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    • pp.367-373
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    • 2014
  • Albedo is one of the critical parameters for understanding global climate change and energy/water balance. In this study, we used red and NIR reflectance from Satellite Pour I'Obervation de la Terre (SPOT)/Vegetation (VGT) S1 product. The product is preprocessed for users that they are atmospherically corrected using Simple Method Atmospheric Correction (SMAC) by Vision on Technology (VITO) for calculating broadband albedo. Roujean's Bi-directional Reflectance Distribution Function (BRDF) model is a semi-empirical method used for BRDF angular integration and inversion. Each kernel of Roujean's model was multi integrated by angle components (i.e., viewing zenith, solar zenith, and relative azimuth angle). Black-sky hemispherical function is integrated by observational angle; whereas, white-sky hemispherical efficient is integrated by incident angle. Estimated spectral albedo of red ($0.61{\sim}0.68{\mu}m$, B2) and near infrared ($0.79{\sim}0.89{\mu}m$, B3) have a good agreement with MODIS albedo products.

Interaction Intent Analysis of Multiple Persons using Nonverbal Behavior Features (인간의 비언어적 행동 특징을 이용한 다중 사용자의 상호작용 의도 분석)

  • Yun, Sang-Seok;Kim, Munsang;Choi, Mun-Taek;Song, Jae-Bok
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.8
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    • pp.738-744
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    • 2013
  • According to the cognitive science research, the interaction intent of humans can be estimated through an analysis of the representing behaviors. This paper proposes a novel methodology for reliable intention analysis of humans by applying this approach. To identify the intention, 8 behavioral features are extracted from the 4 characteristics in human-human interaction and we outline a set of core components for nonverbal behavior of humans. These nonverbal behaviors are associated with various recognition modules including multimodal sensors which have each modality with localizing sound source of the speaker in the audition part, recognizing frontal face and facial expression in the vision part, and estimating human trajectories, body pose and leaning, and hand gesture in the spatial part. As a post-processing step, temporal confidential reasoning is utilized to improve the recognition performance and integrated human model is utilized to quantitatively classify the intention from multi-dimensional cues by applying the weight factor. Thus, interactive robots can make informed engagement decision to effectively interact with multiple persons. Experimental results show that the proposed scheme works successfully between human users and a robot in human-robot interaction.

Stereo Calibration Using Support Vector Machine

  • Kim, Se-Hoon;Kim, Sung-Jin;Won, Sang-Chul
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.250-255
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    • 2003
  • The position of a 3-dimensional(3D) point can be measured by using calibrated stereo camera. To obtain more accurate measurement ,more accurate camera calibration is required. There are many existing methods to calibrate camera. The simple linear methods are usually not accurate due to nonlinear lens distortion. The nonlinear methods are accurate more than linear method, but it increase computational cost and good initial guess is needed. The multi step methods need to know some camera parameters of used camera. Recent years, these explicit model based camera calibration work with the development of more precise camera models involving correction of lens distortion. But these explicit model based camera calibration have disadvantages. So implicit camera calibration methods have been derived. One of the popular implicit camera calibration method is to use neural network. In this paper, we propose implicit stereo camera calibration method for 3D reconstruction using support vector machine. SVM can learn the relationship between 3D coordinate and image coordinate, and it shows the robust property with the presence of noise and lens distortion, results of simulation are shown in section 4.

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Linear Quadratic Servo Design for Magnetic Levitation Systems Considering Disturbance Forces from Linear Synchronous Motor

  • Kim, Chang-Hyun;Ahn, Hanwoong;Lee, Ju;Lee, Hyungwoo
    • Journal of Electrical Engineering and Technology
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    • v.12 no.2
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    • pp.944-949
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    • 2017
  • Recently, the demand of maglev systems in the manufacturing industry for LCD and OLED display panels, which are required to be very clean and possess vacuum systems, has been increasing due to their characteristics such as being non-contact, noise free and eco-friendly. However, it is still a challenge to simultaneously control both the propulsion and levitation for their interactive effect difficult to be exactly measured. In this paper, we proposed a new tuning method for controlling the magnetic levitation force robustly against the levitation disturbance caused by a propulsion system, based on LQ servo optimal control. The disturbance torque of the LSM propulsion system is calculated through FEM analysis in such a way that the LQ servo controller is determined in order to minimize the effect of the disturbance. The robust performance of the proposed LQ servo control method for the in-track type magnetic levitation systems is demonstrated via simulations and experiments.

Color and Brightness Calibration Convergence Technology for 5D Virtual Reality Attractions (5D 가상현실 어트랙션을 위한 색상 및 밝기 보정 융합 기술)

  • Han, Jung-Soo
    • Journal of the Korea Convergence Society
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    • v.7 no.1
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    • pp.25-30
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    • 2016
  • Virtual reality items are increased take-all type of markets like Universal, such as the United States as a leader in the virtual reality technology. Multi-user have to get direct experiences with the whole body like visual, tactile, hearing, sense of movement, and it must be developed new forms of content platform to enjoy immerse deeply into the content. Visitors are not to enjoy the content passively but rather to enjoy the content actively. So it like that should develope content to maximize the immersion. It need the development of new forms of mixed 5D virtual reality Attraction content with all of factors like $360^{\circ}$ circle vision, stereoscopic images, interaction, simulator, and the environmental effect. We proposes how to make the color and brightness calibration technology for this purpose.