• 제목/요약/키워드: Target Information

검색결과 6,192건 처리시간 0.027초

Object tracking based on adaptive updating of a spatial-temporal context model

  • Feng, Wanli;Cen, Yigang;Zeng, Xianyou;Li, Zhetao;Zeng, Ming;Voronin, Viacheslav
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권11호
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    • pp.5459-5473
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    • 2017
  • Recently, a tracking algorithm called the spatial-temporal context model has been proposed to locate a target by using the contextual information around the target. This model has achieved excellent results when the target undergoes slight occlusion and appearance changes. However, the target location in the current frame is based on the location in the previous frame, which will lead to failure in the presence of fast motion because of the lack of a prediction mechanism. In addition, the spatial context model is updated frame by frame, which will undoubtedly result in drift once the target is occluded continuously. This paper proposes two improvements to solve the above two problems: First, four possible positions of the target in the current frame are predicted based on the displacement between the previous two frames, and then, we calculate four confidence maps at these four positions; the target position is located at the position that corresponds to the maximum value. Second, we propose a target reliability criterion and design an adaptive threshold to regulate the updating speed of the model. Specifically, we stop updating the model when the reliability is lower than the threshold. Experimental results show that the proposed algorithm achieves better tracking results than traditional STC and other algorithms.

Extraction of Infrared Target based on Gaussian Mixture Model

  • Shin, Do Kyung;Moon, Young Shik
    • IEIE Transactions on Smart Processing and Computing
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    • 제2권6호
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    • pp.332-338
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    • 2013
  • We propose a method for target detection in Infrared images. In order to effectively detect a target region from an image with noises and clutters, spatial information of the target is first considered by analyzing pixel distributions of projections in horizontal and vertical directions. These distributions are represented as Gaussian distributions, and Gaussian Mixture Model is created from these distributions in order to find thresholding points of the target region. Through analyzing the calculated Gaussian Mixture Model, the target region is detected by eliminating various backgrounds such as noises and clutters. This is performed by using a novel thresholding method which can effectively detect the target region. As experimental results, the proposed method has achieved better performance than existing methods.

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Robust Target Model Update for Mean-shift Tracking with Background Weighted Histogram

  • Jang, Yong-Hyun;Suh, Jung-Keun;Kim, Ku-Jin;Choi, Yoo-Joo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권3호
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    • pp.1377-1389
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    • 2016
  • This paper presents a target model update scheme for the mean-shift tracking with background weighted histogram. In the scheme, the target candidate histogram is corrected by considering the back-projection weight of each pixel in the kernel after the best target candidate in the current frame image is chosen. In each frame, the target model is updated by the weighted average of the current target model and the corrected target candidate. We compared our target model update scheme with the previous ones by applying several test sequences. The experimental results showed that the object tracking accuracy was greatly improved by using the proposed scheme.

표적 크기추정 기술 기반의 CCD 영상 표적 정밀 요격 성능 개선 연구 (A Study on the Target Precision Intercept Algorithm based on the Target Size Estimation at CCD Image Sequence)

  • 정윤식;노신백
    • 제어로봇시스템학회논문지
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    • 제21권1호
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    • pp.52-58
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    • 2015
  • In this paper, The ET-MBEF algorithm is presented for CCD imaging seeker. At the imaging seeker, target size information is important factor for accurate tracking. The MBEF algorithm was proposed to estimate target size at IIR seeker. However, the MBEF algorithm can't be applied at CCD imaginary target size estimation. In order to overcome the problem, we propose ET-MBEF algorithm which based on ET (Edge Template) and MBEF algorithm. The performance of proposed method is tested at target intercept scenario. The experiment results show that the proposed algorithm has the accurate target intercept performance.

지상전투차량에서 표적정보 처리 및 공유 방안 구현 (An Implementation of Target Information Management and its Sharing Process among Ground Fighting Vehicles)

  • 최일호;노해환;손원기
    • 한국군사과학기술학회지
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    • 제23권1호
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    • pp.66-75
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    • 2020
  • Enemy information has significant value when it comes to the process of military actions in battle field. Our Army now uses Battlefield Management Systems(BMSs) equipped in Ground Fighting Vehicles(GFVs) and we need to make research on what kind of role enemy information can play in such systems. Also, enemy information can be shared among GFVs and target information shall be extracted from it in view of KVMF scheme. Because KVMF becomes requisite standard in modern BMSs, we need to implement target information handling process in KVMF standard. In this article, we will focus on how target information and its sharing process can be managed efficiently without information conflicts. Also, situation map produced by it will be noted.

Time-Matching Poisson Multi-Bernoulli Mixture Filter For Multi-Target Tracking In Sensor Scanning Mode

  • Xingchen Lu;Dahai Jing;Defu Jiang;Ming Liu;Yiyue Gao;Chenyong Tian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권6호
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    • pp.1635-1656
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    • 2023
  • In Bayesian multi-target tracking, the Poisson multi-Bernoulli mixture (PMBM) filter is a state-of-the-art filter based on the methodology of random finite set which is a conjugate prior composed of Poisson point process (PPP) and multi-Bernoulli mixture (MBM). In order to improve the random finite set-based filter utilized in multi-target tracking of sensor scanning, this paper introduces the Poisson multi-Bernoulli mixture filter into time-matching Bayesian filtering framework and derive a tractable and principled method, namely: the time-matching Poisson multi-Bernoulli mixture (TM-PMBM) filter. We also provide the Gaussian mixture implementation of the TM-PMBM filter for linear-Gaussian dynamic and measurement models. Subsequently, we compare the performance of the TM-PMBM filter with other RFS filters based on time-matching method with different birth models under directional continuous scanning and out-of-order discontinuous scanning. The results of simulation demonstrate that the proposed filter not only can effectively reduce the influence of sampling time diversity, but also improve the estimated accuracy of target state along with cardinality.

다중센서 환경에서의 잠수함 표적기동분석에 적합한 필터구조 연구 (The Study of a Suitable for TMA Filter Architecture for the Submarine with Multiple Sensors)

  • 임영택
    • 한국군사과학기술학회지
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    • 제15권4호
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    • pp.404-409
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    • 2012
  • In order to detect and track target, submarine gather the target information(bearing, range, frequency and so on) with using multiple sensors. And submarine can estimate target states with target information. In this paper, we suggest the target motion analysis(TMA) filter architecture of submarine and the proposed TMA filter architecture is tested by a series of computer simulation runs and the results are analyzed and verified.

SVM을 사용한 약물 표적 단백질 예측 (Drug Target Protein Prediction using SVM)

  • 정휘성;현보라;정석훈;장우혁;한동수
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2007년도 가을 학술발표논문집 Vol.34 No.2 (B)
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    • pp.17-21
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    • 2007
  • Drug discovery is a long process with a low rate of successful new therapeutic discovery regardless of the advances in information technologies. Identification of candidate proteins is an essential step for the drug discovery and it usually requires considerable time and efforts in the drug discovery. The drug discovery is not a logical, but a fortuitous process. Nevertheless, considerable amount of information on drugs are accumulated in UniProt, NCBI, or DrugBank. As a result, it has become possible to try to devise new computational methods classifying drug target candidates extracting the common features of known drug target proteins. In this paper, we devise a method for drug target protein classification by using weighted feature summation and Support Vector Machine. According to our evaluation, the method is revealed to show moderate accuracy $85{\sim}90%$. This indicates that if the devised method is used appropriately, it can contribute in reducing the time and cost of the drug discovery process, particularly in identifying new drug target proteins.

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스테레오 추적 시스템을 이용한 보행자 높이 및 3차원 위치 추정 기법 (Estimation of Person Height and 3D Location using Stereo Tracking System)

  • 고정환;안성수
    • 디지털산업정보학회논문지
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    • 제8권2호
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    • pp.95-104
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    • 2012
  • In this paper, an estimation of person height and 3D location of a moving person by using the pan/tilt-embedded stereo tracking system is suggested and implemented. In the proposed system, face coordinates of a target person is detected from the sequential input stereo image pairs by using the YCbCr color model and phase-type correlation methods and then, using this data as well as the geometric information of the stereo tracking system, distance to the target from the stereo camera and 3-dimensional location information of a target person are extracted. Basing on these extracted data the pan/tilt system embedded in the stereo camera is controlled to adaptively track a moving person and as a result, moving trajectory of a target person can be obtained. From some experiments using 780 frames of the sequential stereo image pairs, it is analyzed that standard deviation of the position displacement of the target in the horizontal and vertical directions after tracking is kept to be very low value of 1.5, 0.42 for 780 frames on average, and error ratio between the measured and computed 3D coordinate values of the target is also kept to be very low value of 0.5% on average. These good experimental results suggest a possibility of implementation of a new stereo target tracking system having a high degree of accuracy and a very fast response time with this proposed algorithm.

A Signal Detection of Minimum Variance Algorithm on Linear Constraints

  • Kwan Hyeong Lee
    • International Journal of Internet, Broadcasting and Communication
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    • 제15권3호
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    • pp.8-13
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    • 2023
  • We propose a method for removing interference and noise to estimate target information. In wireless channels, information signals are subject to interference and noise, making it is difficult to accurately estimate the desired signal. To estimate the desired information signal, it is essential to remove the noise and interference from the received signal, extracting only the desired signal. If the received signal noise and interference are not removed, the estimated information signal will have a large error in distance and direction, and the exact location of the target cannot be estimated. This study aims to accurately estimate the desired target in space. The objective is to achieve more presice target estimation than existing methods and enhance target resolution.An estimation method is proposed to improve the accuracy of target estimation. The proposed target estimation method obtains optimal weights using linear constraints and the minimum variance method. Through simulation, the performance of the proposed method and the existing method is analyzed. The proposed method successfully estimated all four targets, while the existing method only estimated two targets. The results show that the proposed method has better resolutiopn and superior estimation capability than the existing method.