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Football match intelligent editing system based on deep learning

  • Wang, Bin;Shen, Wei;Chen, FanSheng;Zeng, Dan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.10
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    • pp.5130-5143
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    • 2019
  • Football (soccer) is one of the most popular sports in the world. A huge number of people watch live football matches by TV or Internet. A football match takes 90 minutes, but viewers may only want to watch a few highlights to save their time. As far as we know, there is no such a product that can be put into use to achieve intelligent highlight extraction from live football matches. In this paper, we propose an intelligent editing system for live football matches. Our system can automatically extract a series of highlights, such as goal, shoot, corner kick, red yellow card and the appearance of star players, from the live stream of a football match. Our system has been integrated into live streaming platforms during the 2018 FIFA World Cup and performed fairly well.

Stereoscopic Video Conversion Based on Image Motion Classification and Key-Motion Detection from a Two-Dimensional Image Sequence (영상 운동 분류와 키 운동 검출에 기반한 2차원 동영상의 입체 변환)

  • Lee, Kwan-Wook;Kim, Je-Dong;Kim, Man-Bae
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.10B
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    • pp.1086-1092
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    • 2009
  • Stereoscopic conversion has been an important and challenging issue for many 3-D video applications. Usually, there are two different stereoscopic conversion approaches, i.e., image motion-based conversion that uses motion information and object-based conversion that partitions an image into moving or static foreground object(s) and background and then converts the foreground in a stereoscopic object. As well, since the input sequence is MPEG-1/2 compressed video, motion data stored in compressed bitstream are often unreliable and thus the image motion-based conversion might fail. To solve this problem, we present the utilization of key-motion that has the better accuracy of estimated or extracted motion information. To deal with diverse motion types, a transform space produced from motion vectors and color differences is introduced. A key-motion is determined from the transform space and its associated stereoscopic image is generated. Experimental results validate effectiveness and robustness of the proposed method.

Feature Based Multi-Resolution Registration of Blurred Images for Image Mosaic

  • Fang, Xianyong;Luo, Bin;He, Biao;Wu, Hao
    • International Journal of CAD/CAM
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    • v.9 no.1
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    • pp.37-46
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    • 2010
  • Existing methods for the registration of blurred images are efficient for the artificially blurred images or a planar registration, but not suitable for the naturally blurred images existing in the real image mosaic process. In this paper, we attempt to resolve this problem and propose a method for a distortion-free stitching of naturally blurred images for image mosaic. It adopts a multi-resolution and robust feature based inter-layer mosaic together. In each layer, Harris corner detector is chosen to effectively detect features and RANSAC is used to find reliable matches for further calibration as well as an initial homography as the initial motion of next layer. Simplex and subspace trust region methods are used consequently to estimate the stable focal length and rotation matrix through the transformation property of feature matches. In order to stitch multiple images together, an iterative registration strategy is also adopted to estimate the focal length of each image. Experimental results demonstrate the performance of the proposed method.

Robust Transmission Waveform Design for Distributed Multiple-Radar Systems Based on Low Probability of Intercept

  • Shi, Chenguang;Wang, Fei;Sellathurai, Mathini;Zhou, Jianjiang;Zhang, Huan
    • ETRI Journal
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    • v.38 no.1
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    • pp.70-80
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    • 2016
  • This paper addresses the problem of robust waveform design for distributed multiple-radar systems (DMRSs) based on low probability of intercept (LPI), where signal-to-interference-plus-noise ratio (SINR) and mutual information (MI) are utilized as the metrics for target detection and information extraction, respectively. Recognizing that a precise characterization of a target spectrum is impossible to capture in practice, we consider that a target spectrum lies in an uncertainty class bounded by known upper and lower bounds. Based on this model, robust waveform design approaches for the DMRS are developed based on LPI-SINR and LPI-MI criteria, where the total transmitting energy is minimized for a given system performance. Numerical results show the effectiveness of the proposed approaches.

Interface monitoring of steel-concrete-steel sandwich structures using piezoelectric transducers

  • Yan, Jiachuan;Zhou, Wensong;Zhang, Xin;Lin, Youzhu
    • Nuclear Engineering and Technology
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    • v.51 no.4
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    • pp.1132-1141
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    • 2019
  • Steel-concrete-steel (SCS) sandwich structures have important advantages over conventional concrete structures, however, bond-slip between the steel plate and concrete may lead to a loss of composite action, resulting in a reduction of stiffness and fatigue life of SCS sandwich structures. Due to the inaccessibility and invisibility of the interface, the interfacial performance monitoring and debonding detection using traditional measurement methods, such as relative displacement between the steel plate and core concrete, have proved challenging. In this work, two methods using piezoelectric transducers are proposed to detect the bond-slip between steel plate and core concrete during the test of the beam. The first one is acoustic emission (AE) method, which can detect the dynamic process of bond-slip. AE signals can be detected when initial micro cracks form and indicate the damage severity, types and locations. The second is electromechanical impedance (EMI) method, which can be used to evaluate the damage due to bond-slip through comparing with the reference data in static state, even if the bond-slip is invisible and suspends. In this work, the experiment is implemented to demonstrate the bond-slip monitoring using above methods. Experimental results and further analysis show the validity and unique advantage of the proposed methods.

A Multi-level Perception Security Model Using Virtualization

  • Lou, Rui;Jiang, Liehui;Chang, Rui;Wang, Yisen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.11
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    • pp.5588-5613
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    • 2018
  • Virtualization technology has been widely applied in the area of computer security research that provides a new method for system protection. It has been a hotspot in system security research at present. Virtualization technology brings new risk as well as progress to computer operating system (OS). A multi-level perception security model using virtualization is proposed to deal with the problems of over-simplification of risk models, unreliable assumption of secure virtual machine monitor (VMM) and insufficient integration with virtualization technology in security design. Adopting the enhanced isolation mechanism of address space, the security perception units can be protected from risk environment. Based on parallel perceiving by the secure domain possessing with the same privilege level as VMM, a mechanism is established to ensure the security of VMM. In addition, a special pathway is set up to strengthen the ability of information interaction in the light of making reverse use of the method of covert channel. The evaluation results show that the proposed model is able to obtain the valuable risk information of system while ensuring the integrity of security perception units, and it can effectively identify the abnormal state of target system without significantly increasing the extra overhead.

Experimental Investigation of a High-repetition-rate Pr3+:YLF Laser with Single-frequency Oscillation

  • Dai, Weicheng;Jin, Long;Dong, Yuan;Jin, Guangyong
    • Current Optics and Photonics
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    • v.5 no.6
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    • pp.721-729
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    • 2021
  • We demonstrate a Pr3+:YLF 639.7-nm laser with single-frequency output based on the Q-switched pre-lase technology, pumped by a fiber-coupled GaN blue laser diode. The pre-lase technology is realized by the step-type loss of the acousto-optical Q-switched device. The conclusions of the theoretical research are verified experimentally. The mode-suppression ratio was 44 dB at the single-frequency laser output. Detection by interferometer verified the realization of the stable single-frequency laser. In addition, the emission spectrum had a linewidth of 139.9 MHz, measured by Fabry-Perot interferometer. The single-frequency laser's single-peak power was over 19.7 W with 98.8-ns pulse duration, obtained under an absorption power of 1.74 W.

A Energy Efficient Misused Key Detection in Wireless Sensor Networks (무선 센서 네트워크에서 에너지 효율적인 오용키 탐지 방법)

  • Park, Min-Woo;Kim, Jong-Myoung;Han, Young-Ju;Chung, Tai-Myoung
    • Annual Conference of KIPS
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    • 2009.04a
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    • pp.1214-1217
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    • 2009
  • 무선 센서 네트워크에서 각각의 센서 노드들은 무선 통신을 통해 서로 간에 통신을 수행한다. 과거에는 이러한 센서 노드간의 통신을 제 3 자로부터 안전하게 지키는 것이 중요한 보안 이슈였다. 특히 보안 서비스를 제공 하기 위한 키 관리 기법들이 주요 연구방향이었다. 하지만 안전하게 만들어진 확률론적 키(key)를 기반으로 하는 키 사전분배 방법은 공격받은 다른 노드로 인해 자신의 키가 노출 될 수 있다. 공격자는 노출된 공유키(shared key)를 통해 노출되지 않은 정상 노드(non-compromised node) 사이의 대칭키(pairwise key)를 얻을 수 있으며, 공격자는 네트워크에 심각한 영향을 줄 수 있는 메시지 삽입 및 수정 공격을 감행할 수 있다. 이와 같은 오용된 키를 폐기하고 메시지 삽입 및 수정 공격을 막기 위해 Liu and Dong 은 오용키 탐지 방법을 제안하였다. 하지만 이들의 방법에는 한계점이 있어 이를 보완하기 위한 에너지 효율적인 오용키 탐지 기법을 제안한다.

MRU-Net: A remote sensing image segmentation network for enhanced edge contour Detection

  • Jing Han;Weiyu Wang;Yuqi Lin;Xueqiang LYU
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.12
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    • pp.3364-3382
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    • 2023
  • Remote sensing image segmentation plays an important role in realizing intelligent city construction. The current mainstream segmentation networks effectively improve the segmentation effect of remote sensing images by deeply mining the rich texture and semantic features of images. But there are still some problems such as rough results of small target region segmentation and poor edge contour segmentation. To overcome these three challenges, we propose an improved semantic segmentation model, referred to as MRU-Net, which adopts the U-Net architecture as its backbone. Firstly, the convolutional layer is replaced by BasicBlock structure in U-Net network to extract features, then the activation function is replaced to reduce the computational load of model in the network. Secondly, a hybrid multi-scale recognition module is added in the encoder to improve the accuracy of image segmentation of small targets and edge parts. Finally, test on Massachusetts Buildings Dataset and WHU Dataset the experimental results show that compared with the original network the ACC, mIoU and F1 value are improved, and the imposed network shows good robustness and portability in different datasets.

EEG-based Subjects' Response Time Detection for Brain-Computer-Interface (뇌-컴퓨터-인터페이스를 위한 EEG 기반의 피험자 반응시간 감지)

  • 신승철;류창수;송윤선;남승훈
    • Journal of KIISE:Software and Applications
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    • v.29 no.11
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    • pp.837-850
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    • 2002
  • In this paper, we propose an EEG-based response time prediction method during a yes/no cognitive decision task. In the experimental task, a subject goes through responding of visual stimulus, understanding the given problem, controlling hand motions, and hitting a key. Considering the subject's varying brain activities, we model subjects' mental states with defining CT (cut time), ST (selection time), and RP (repeated period). Based on the assumption between ST and RT in the mental model, we predict subjects' response time by detection of selection time. To recognize the subjects' selection time ST, we extract 3 types of feature from the filtered brain waves at frequency bands of $\alpha$, $\beta$, ${\gamma}$ waves in 4 electrode pairs combined by spatial relationships. From the extracted features, we construct specific rules for each subject and meta rules including common factors in all subjects. Applying the ST detection rules to 8 subjects gives 83% success rates and also shows that the subjects will hit a key in 0.73 seconds after ST detected. To validate the detection rules and parameters, we test the rules for 2 subjects among 8 and discuss about the experimental results. We expect that the proposed detection method can be a basic technology for brain-computer-interface by combining with left/right hand movement or yes/no discrimination methods.