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复杂场景下运动目标的实时跟踪，在完成对目标模式匹配，目标运动估计和石台控制处理的基础上，对三个模块力加以综合，实现对运动目标的实时跟踪。-sports complex scene and real-time tracking of the target, the completion of the target pattern matching, Target Motion estimation and control of Shitai, on the basis of three integ
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多目标检测，可用于视频监控，视觉目标跟踪，运动检测，及其它图像处理中的相关应用。-This code contains multiple object detection adaptable to visual surveillance, visual object tracking, motion estimation and other image processing applications.
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Yaakov Bar-Shalom, X.-Rong Li,Thiagalingam Kirubarajan - Estimation with Applications to Tracking and Navigation - DynaEst toolbox -Yaakov Bar-Shalom, X.-Rong Li,Thiagalingam Kirubarajan- Estimation with Applications to Tracking and Navigation- DynaE
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This paper studies the problem of tracking a ballistic object in
the reentry phase by processing radar measurements. A suitable
(highly nonlinear) model of target motion is developed and the
theoretical Cramer—Rao lower bounds (CRLB) of estimat
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This paper studies the problem of tracking a ballistic object in
the reentry phase by processing radar measurements. A suitable
(highly nonlinear) model of target motion is developed and the
theoretical Cramer—Rao lower bounds (CRLB) of estimat
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This paper studies the problem of tracking a ballistic object in
the reentry phase by processing radar measurements. A suitable
(highly nonlinear) model of target motion is developed and the
theoretical Cramer—Rao lower bounds (CRLB) of estimat
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Nonstationary Channel Estimation
using a Kalman Tracking Filter
卡尔曼滤波算法的一个一个用，可用作 efk学习之用-Nonstationary Channel Estimation using a Kalman Tracking Filter Kalman filter algorithm one by one, and can be used as a learning efk
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I need estimation channel MIMO-OFDM because I do synchronous CFO and SFO by tracking algorithm Obelix-I need estimation channel MIMO-OFDM because I do synchronous CFO and SFO by tracking algorithm Obelix
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This volume, in the ITECH Vision Systems series of books, reports recent advances in the
use of pattern recognition techniques for computer and robot vision. The sciences of pattern
recognition and computational vision have been inextricably inte
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接收端采用的算法和程序流程与发送端发送的OFDM符号的帧结构有关系。具体的帧结构，以及定时估计，频偏估计，剩余误差跟踪的算法可参考算法说明文档。-Receiver used algorithms and program flow with the sender sends the frame structure of OFDM symbols are. Concrete frame structure and timing estimates, frequency offset estimati
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在机动目标跟踪中，机动目标模型是机动目标跟踪的基本要素之一，一般希望机动目标模型能准确表征目标机动时的各种运动状态。比较常用的模型有匀速运动(CV)模型、匀加速运动(CA) 模型、时间相关模型（Singer）和机动目标“当前”统计模型。上述模型均采用机动频率表征目标的机动情况。在应用当中，通常采用固定的机动频率，这就表示机动目标的机动时间是一定的，而实际上机动目标的机动时间是不断变化的，也就是说机动频率是不断变化的，采用固定机动频率必然会带来误差。采样周期在0.5—2S时，机动频率越小跟踪精度越
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This method is used for tracking wavelet/optical flow-based
detection for automatic target recognition in the following paper:
Dessauer, M. and Dua S. “Wavelet-based optical flow object detection, motion estimation, and tracking on moving vehic
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对运动物体实现了运动估计和运动跟踪，使用非常方便-On the moving object implements motion estimation and motion tracking
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时延估计和波束形成方法，在声源跟踪方面有用-Time delay estimation and beamforming methods, useful for tracking the sound source
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adaptive beamformer using an FFT filter bank with/without DOA estimation and tracking
(frequency domain version of Frost beamformer)
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The goal of the HumanEva dataset is to develop new techniques, technology, and
algorithms for the automatic articulated pose estimation and tracking of humans. Brown University
is involved in an ongoing effort to develop this dataset of synchroni
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Introduction: The goal of the HumanEva dataset is to develop new techniques, technology, and
algorithms for the automatic articulated pose estimation and tracking of humans. Brown University
is involved in an ongoing effort to develop this datase
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Background subtraction matlab code for object motion estimation and tracking in video
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kalman目标估计与跟踪控制代码,涉及matlab下kalman，无忌卡尔曼以及扩展卡尔曼滤波估计与跟踪控制-kalman estimation and target tracking control code, involving matlab kalman, loudly Kalman and extended Kalman filter estimation and tracking control
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采用卡尔曼滤波完成对于目标状态的融合估计和跟踪，实现多传感器对移动目标的持续有效跟踪。(Calman filter is used to complete the fusion estimation and tracking of the target state, and the multi sensor continuous and effective tracking of moving target is realized.)
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