• Title/Summary/Keyword: extrinsic detection

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B-snake Based Lane Detection with Feature Merging and Extrinsic Camera Parameter Estimation (특징점 병합과 카메라 외부 파라미터 추정 결과를 고려한 B-snake기반 차선 검출)

  • Ha, Sangheon;Kim, Gyeonghwan
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.1
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    • pp.215-224
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    • 2013
  • This paper proposes a robust lane detection algorithm for bumpy or slope changing roads by estimating extrinsic camera parameters, which represent the pose of the camera mounted on the car. The proposed algorithm assumes that two lanes are parallel with the predefined width. The lane detection and the extrinsic camera parameter estimation are performed simultaneously by utilizing B-snake in motion compensated and merged feature map with consecutive sequences. The experimental results show the robustness of the proposed algorithm in various road environments. Furthermore, the accuracy of extrinsic camera parameter estimation is evaluated by calculating the distance to a preceding car with the estimated parameters and comparing to the radar-measured distance.

Markerless camera pose estimation framework utilizing construction material with standardized specification

  • Harim Kim;Heejae Ahn;Sebeen Yoon;Taehoon Kim;Thomas H.-K. Kang;Young K. Ju;Minju Kim;Hunhee Cho
    • Computers and Concrete
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    • v.33 no.5
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    • pp.535-544
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    • 2024
  • In the rapidly advancing landscape of computer vision (CV) technology, there is a burgeoning interest in its integration with the construction industry. Camera calibration is the process of deriving intrinsic and extrinsic parameters that affect when the coordinates of the 3D real world are projected onto the 2D plane, where the intrinsic parameters are internal factors of the camera, and extrinsic parameters are external factors such as the position and rotation of the camera. Camera pose estimation or extrinsic calibration, which estimates extrinsic parameters, is essential information for CV application at construction since it can be used for indoor navigation of construction robots and field monitoring by restoring depth information. Traditionally, camera pose estimation methods for cameras relied on target objects such as markers or patterns. However, these methods, which are marker- or pattern-based, are often time-consuming due to the requirement of installing a target object for estimation. As a solution to this challenge, this study introduces a novel framework that facilitates camera pose estimation using standardized materials found commonly in construction sites, such as concrete forms. The proposed framework obtains 3D real-world coordinates by referring to construction materials with certain specifications, extracts the 2D coordinates of the corresponding image plane through keypoint detection, and derives the camera's coordinate through the perspective-n-point (PnP) method which derives the extrinsic parameters by matching 3D and 2D coordinate pairs. This framework presents a substantial advancement as it streamlines the extrinsic calibration process, thereby potentially enhancing the efficiency of CV technology application and data collection at construction sites. This approach holds promise for expediting and optimizing various construction-related tasks by automating and simplifying the calibration procedure.

A Low-Complexity CLSIC-LMMSE-Based Multi-User Detection Algorithm for Coded MIMO Systems with High Order Modulation

  • Xu, Jin;Zhang, Kai
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.4
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    • pp.1954-1971
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    • 2017
  • In this work, first, a multiuser detection (MUD) algorithm based on component-level soft interference cancellation and linear minimum mean square error (CLSIC-LMMSE) is proposed, which can enhance the bit error ratio (BER) performance of the traditional SIC-LMMSE-based MUD by mitigating error propagation. Second, for non-binary low density parity check (NB-LDPC) coded high-order modulation systems, when the proposed algorithm is integrated with partial mapping, the receiver with iterative detection and decoding (IDD) achieves not only better BER performance but also significantly computational complexity reduction over the traditional SIC-LMMSE-based IDD scheme. Extrinsic information transfer chart (EXIT) analysis and numerical simulations are both used to support the conclusions.

Hybrid Iterative Detection Algorithm for MIMO Systems (다중 안테나 시스템을 위한 Hybrid Iterative 검출 기법)

  • Kim, Sang-Heon;Shin, Myeong-Cheol;Kim, Kyeong-Yeon;Lee, Chung-Yong
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.4 s.316
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    • pp.117-122
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    • 2007
  • For multiple antenna systems, we consider the hybrid iterative detection of the maximum a posteriori probability(MAP) detection and the linear detection such as the minimum-mean-square-error(MMSE) filtering with soft cancelation. We devise methods to obtain both the lower complexity of the linear detection and the superior performance of the MAP detection. Using the a prior probability of the coded bit which is extrinsic of the outer decoder, we compute the threshold of grouping and determine the detection scheme symbol by symbol. Through the simulation results, it is shown that the proposed receiver obtains the superior performance to the MMSE detector and the lower complexity than the MAP detector.

Modern Methods of Text Analysis as an Effective Way to Combat Plagiarism

  • Myronenko, Serhii;Myronenko, Yelyzaveta
    • International Journal of Computer Science & Network Security
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    • v.22 no.8
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    • pp.242-248
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    • 2022
  • The article presents the analysis of modern methods of automatic comparison of original and unoriginal text to detect textual plagiarism. The study covers two types of plagiarism - literal, when plagiarists directly make exact copying of the text without changing anything, and intelligent, using more sophisticated techniques, which are harder to detect due to the text manipulation, like words and signs replacement. Standard techniques related to extrinsic detection are string-based, vector space and semantic-based. The first, most common and most successful target models for detecting literal plagiarism - N-gram and Vector Space are analyzed, and their advantages and disadvantages are evaluated. The most effective target models that allow detecting intelligent plagiarism, particularly identifying paraphrases by measuring the semantic similarity of short components of the text, are investigated. Models using neural network architecture and based on natural language sentence matching approaches such as Densely Interactive Inference Network (DIIN), Bilateral Multi-Perspective Matching (BiMPM) and Bidirectional Encoder Representations from Transformers (BERT) and its family of models are considered. The progress in improving plagiarism detection systems, techniques and related models is summarized. Relevant and urgent problems that remain unresolved in detecting intelligent plagiarism - effective recognition of unoriginal ideas and qualitatively paraphrased text - are outlined.

FATIGUE CRACK GROWTH MONITORING OF CRACKED ALUMINUM PLATE REPAIRED WITH COMPOSITE PATCH USING EMBEDDED OPTICAL FIBER SENSORS (광섬유센서를 이용한 복합재 패치수리된 알루미늄판의 균열관찰)

  • 서대철;이정주;김상훈
    • Proceedings of the Korean Society For Composite Materials Conference
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    • 2001.05a
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    • pp.250-253
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    • 2001
  • Recently, based on the smart structure concept, optical fiber sensors have been increasingly applied to monitor the various engineering and civil structural components. Repairs based on adhesively bonded fiber reinforce composite patches are more structurally efficient and much less damaging to the parent structure than standard repairs based on mechanically fastened metallic patches. As a result of the high reinforcing efficiency of bonded patches fatigue cracks can be successfully repaired. However, when such repairs are applied to primary structures, it is needed to demonstrate that its loss can be immediately detected. This approach is based on the "smart patch" concept in which the patch system monitors its own health. The objective of this study is to evaluate the potentiality of application of transmission-type extrinsic Fabry-Perot optical fiber sensor (TEFPI) to the monitoring of crack growth behavior of composite patch repaired structures. The sensing system of TEFPI and the data reduction principle for the detection of crack detection are presented. Finally, experimental results from the tests of center-cracked-tension aluminum specimens repaired with bonded composite patch is presented and discussed.

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Robust Elevator Door Recognition using LRF and Camera (LRF와 카메라를 이용한 강인한 엘리베이터 문 인식)

  • Ma, Seung-Wan;Cui, Xuenan;Lee, Hyung-Ho;Kim, Hyung-Rae;Lee, Jae-Hong;Kim, Hak-Il
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.6
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    • pp.601-607
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    • 2012
  • The recognition of elevator door is needed for mobile service robots to moving between floors in the building. This paper proposed the sensor fusion approach using LRF (Laser Range Finder) and camera to solve the problem. Using the laser scans by the LRF, we extract line segments and detect candidates as the elevator door. Using the image by the camera, the door candidates are verified and selected as real door of the elevator. The outliers are filtered through the verification process. Then, the door state detection is performed by depth analysis within the door. The proposed method uses extrinsic calibration to fuse the LRF and the camera. It gives better results of elevator door recognition compared to the method using LRF only.

Soft-Decision for Differential Amplify-and-Forward over Time-Varying Relaying Channel

  • Gao, Fengyue;Kong, Lei;Dong, Feihong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.3
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    • pp.1131-1143
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    • 2016
  • Differential detection schemes do not require any channel estimation, which can be employed under user mobility with low computational complexity. In this work, a soft-input soft-output (SISO) differential detection algorithm is proposed for amplify-and-forward (AF) over time-varying relaying channels based cooperative communications system. Furthermore, maximum-likelihood (ML) detector for M-ary differential Phase-shift keying (DPSK) is derived to calculate a posteriori probabilities (APP) of information bits. In addition, when the SISO is exploited in conjunction with channel decoding, iterative detection and decoding approach by exchanging extrinsic information with outer code is obtained. Finally, simulation results show that the proposed non-coherent approach improves detection performance significantly. In particular, the system can obtain greater performance gain under fast-fading channels.

SIMPLE EXTRINSIC FIBER OPTIC METHOD TO EVALUATE ABSORBANCE IN AQUEOUS NANOPARTICLE

  • Hanh, Nguyen Thi Kieu;Kulkarnib, Atul;Kim, T.
    • Proceedings of the KSME Conference
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    • 2008.11a
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    • pp.1723-1726
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    • 2008
  • In recent years, there has been a remarkable progress in the development of the fiber optic sensors for the detection of various chemicals. Fiber optic sensors have the advantages of very small size, flexibility and low cost. The fiber optic sensors employing different optical or spectroscopic phenomena have been reported such as bulk absorption, optical reflectance, fluoresces and energy transfer. In this study, the effect of nanoparticle concentration in liquid upon light absorption and scattering was studied using extrinsic fiber optic method. For the evaluation, we used Red (650 nm) and Blue (430 nm) light sources which are coupled through the standard cuvette using optical fiber to detector. The experiments are carried out with Polystyrene latex (400 - 800 nm), and Silicon (35 - 110 nm) nanoparticles suspended in Isopropanol. Differences in light absorption and scattering depending on nanoparticle concentration and type are discussed. This method may be useful to study nanoparticles properties for various application and research.

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A Probabilistic Detection Algorithm for Noiseless Group Testing (무잡음 그룹검사에 대한 확률적 검출 알고리즘)

  • Seong, Jin-Taek
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.10
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    • pp.1195-1200
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    • 2019
  • This paper proposes a detection algorithm for group testing. Group testing is a problem of finding a very small number of defect samples out of a large number of samples, which is similar to the problem of Compressed Sensing. In this paper, we define a noiseless group testing and propose a probabilistic algorithm for detection of defective samples. The proposed algorithm is constructed such that the extrinsic probabilities between the input and output signals exchange with each other so that the posterior probability of the output signal is maximized. Then, defective samples are found in the group testing problem through a simulation on the detection algorithm. The simulation results for this study are compared with the lower bound in the information theory to see how much difference in failure probability over the input and output signal sizes.