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Description: 一． 追踪模型
以(x , y)代表飞机的坐标，v代表飞机的速度；以（X ,Y）代表导弹的坐标，u代表导弹的速度。
由于导弹时刻指向飞机，故有
dY/dX=(y-Y)/(x-X)
记k=u/sqrt((y-Y)*(y-Y)+(x-X)*(x-X))
则有
dY/dt=k(y-Y) dX/dt=k(x-X)
故有叠代方程
Y=Y+k*(y-Y)*dt
X=X+k*(x-X)*dt (程序中以t代dt)
程序中第一个for循环代表发射导弹打飞机，第二个for代表飞机发现导弹后做正弦运动试图逃跑。
小结：
追踪模型中关键是利用叠代方程 Y=Y+k*(y-Y)*dt 确定追踪者的运动坐标，这样，不
X=X+k*(x-X)*dt
论被追踪者做何种运动，都可利用该叠代方程找出追踪者的运动轨迹（注意追踪者的速度应大于被追踪者的速度）。
-one. Track model (x, y) coordinates of the aircraft representatives, representatives v the speed of aircraft; A (X, Y), on behalf of the coordinates of missile, u representative of the speed of the missile. As the aircraft missile at times, it is dY / dX = (y-Y) / (x-X) recorded k = u / sqrt ((y-Y) * (y-Y) (x-x) * (x-X) ) have curves / dt = k (y-Y) dX / dt = k (x-X) there is an iterative equation Y Y = k * (y-Y) * dt X = X * k (x-x) * dt ( proceedings t substituting dt) procedures for the first cycle of a representative aircraft fired a missile, the second for representatives of aircraft missiles found after doing sinusoidal movement to try to escape. Summary : key tracking model is to use iterative equation Y Y = k * (y-Y) * dt tracers to determine the coordinates of movement, and X = X *
Platform: |
Size: 803 |
Author: 白小欣 |
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Description: Most motion-based tracking algorithms assume that objects undergo rigid motion, which is most likely disobeyed in real world. In this paper, we present a novel motion-based tracking framework which makes no such assumptions. Object is represented by a set of local invariant features, whose motions are observed by a feature correspon-
dence process. A generative model is proposed to depict
the relationship between local feature motions and object
global motion, whose parameters are learned efciently by
an on-line EM algorithm. And the object global motion is estimated in term of maximum likelihood of observations.Then an updating mechanism is employed to adapt object representation. Experiments show that our framework is
exible and robust in dealing with appearance changes,background clutter, illumination changes and occlusion
Platform: |
Size: 424705 |
Author: chenjieke |
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Description: 一． 追踪模型
以(x , y)代表飞机的坐标，v代表飞机的速度；以（X ,Y）代表导弹的坐标，u代表导弹的速度。
由于导弹时刻指向飞机，故有
dY/dX=(y-Y)/(x-X)
记k=u/sqrt((y-Y)*(y-Y)+(x-X)*(x-X))
则有
dY/dt=k(y-Y) dX/dt=k(x-X)
故有叠代方程
Y=Y+k*(y-Y)*dt
X=X+k*(x-X)*dt (程序中以t代dt)
程序中第一个for循环代表发射导弹打飞机，第二个for代表飞机发现导弹后做正弦运动试图逃跑。
小结：
追踪模型中关键是利用叠代方程 Y=Y+k*(y-Y)*dt 确定追踪者的运动坐标，这样，不
X=X+k*(x-X)*dt
论被追踪者做何种运动，都可利用该叠代方程找出追踪者的运动轨迹（注意追踪者的速度应大于被追踪者的速度）。
-one. Track model (x, y) coordinates of the aircraft representatives, representatives v the speed of aircraft; A (X, Y), on behalf of the coordinates of missile, u representative of the speed of the missile. As the aircraft missile at times, it is dY/dX = (y-Y)/(x-X) recorded k = u/sqrt ((y-Y)* (y-Y) (x-x)* (x-X) ) have curves/dt = k (y-Y) dX/dt = k (x-X) there is an iterative equation Y Y = k* (y-Y)* dt X = X* k (x-x)* dt ( proceedings t substituting dt) procedures for the first cycle of a representative aircraft fired a missile, the second for representatives of aircraft missiles found after doing sinusoidal movement to try to escape. Summary : key tracking model is to use iterative equation Y Y = k* (y-Y)* dt tracers to determine the coordinates of movement, and X = X*
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Size: 1024 |
Author: 白小欣 |
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Description: 人头跟踪算法，采用均值漂移和形状约束模型。-poll tracking algorithm using mean drift and shape the model.
Platform: |
Size: 36864 |
Author: 向慧 |
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Description: 上传的为imm交互多模型跟踪算法的源程序，希望和作目标跟踪的朋友多交流。-uploaded to imm interactive multi-model tracking algorithm of the source, and hopes for target tracking friends more exchanges.
Platform: |
Size: 6144 |
Author: 石鸿逸 |
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Description: 人脸检测和跟踪学位论文；人脸检测定位：运动区域检测预处理， 肤色区域的分割和利用二值形态学等操作的人脸粗检，利用眼、嘴特征的彩色信息检测的人脸细检，利用投影法检测眼睛和嘴巴亮块的人脸定位。提出了一种基于自适应肤色模型匹配与验证的方法对人脸进行跟踪-Face detection and tracking dissertation Face Detection positioning: Sports regional detection pretreatment, color region segmentation and the use of binary morphological operations, such as human faces rough seizure, the use of eyes, mouth features detection of color information Face Fine Frederick, using projection method bright eyes and mouth block face positioning. A model based on adaptive color matching and validation of the method of face tracking
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Size: 3622912 |
Author: 田卉 |
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Description: this program is a model-based predictive control to track a sinusoidal target.
Platform: |
Size: 2048 |
Author: Mehran Ahmadlou |
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Description: this program is an m-file of Model-based Predictive Control to track a sinusoidal target in various cases of mismatching and delay.
Platform: |
Size: 3072 |
Author: Mehran Ahmadlou |
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Description: this 3d tr model for airplane target tracking-this is 3d tr model for airplane target tracking
Platform: |
Size: 2048 |
Author: haleh |
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Description: This paper proposes a new method of extracting and tracking
a nonrigid object moving while allowing camera movement. For object
extraction we first detect an object using watershed segmentation
technique and then extract its contour points by approximating the
boundary using the idea of feature point weighting. For object tracking
we take the contour to estimate its motion in the next frame by the
maximum likelihood method. The position of the object is estimated using
a probabilistic Hausdorff measurement while the shape variation is
modelled using a modified active contour model. The proposed method is
highly tolerant to occlusion. Because the tracking result is stable unless
an object is fully occluded during tracking, the proposed method can be
applied to various applications.
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Size: 2163712 |
Author: sacoura31 |
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Description: Kalman e ConDensation in video-tracking
Model based tracking
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Size: 915456 |
Author: bashar Rjoub |
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Description: This paper presents the simulation of a simple First Order plus Delay Time (FOPDT) process model using
advanced control algorithms. Specifically, these advanced algorithms are the IMC-based PID controller, the Model
Predictive Controller (MPC) and the Proportional-Integral-Plus Controller (PIP) and their performance is compared
with the conventional Proportional – Integral – Derivative (PID) algorithm. The simulations took place using the
Matlab/Simulink™ software.-This paper presents the simulation of a simple First Order plus Delay Time (FOPDT) process model using
advanced control algorithms. Specifically, these advanced algorithms are the IMC-based PID controller, the Model
Predictive Controller (MPC) and the Proportional-Integral-Plus Controller (PIP) and their performance is compared
with the conventional Proportional – Integral – Derivative (PID) algorithm. The simulations took place using the
Matlab/Simulink™ software.
Platform: |
Size: 433152 |
Author: chris kasta |
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Description: 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高[1]，但机动频率仍然是固定值。本文提出的基于神经网络的机动频率自适应调整方法可以使机动频率随机动而变化，从而提高状态估计的准确性，提高跟踪精度。本文将小波神经网络用于机动目标跟踪中机动频率的自适应调整，该算法对机动目标“当前”统计模型中的机动频率进行实时修改, 从而自适应的改变机动频率,使跟踪算法与目标的真实状态更接近。该算法采用小波神经网络的离线训练，实时性好。-The maneuver of the maneuvering target is uncertain. The maneuvering frequency is constantly changeable, but traditionally it is beforehand determined as a constant based on the target state estimation in the state model of the maneuvering target. The maneuver of the maneuvering target makes the kinematics equation of the target model mismatch with the practical motion model and the tracking error will be increased. Based on the advantages of the self-learning, the rapid convergence rate and the nonlinear approximation ability of the wavelet neural network, it was put forward to be used in the field of target tracking in the paper. The new residual is used as the input of the wavelet neural network, the output of the network is used to adjust adaptively the maneuvering frequency of the CS model. The algorithm is more close to the real state of the target. The simulation results showed that tracking error can be reduced and the tracking accuracy can be improved.
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Size: 4096 |
Author: 李隆基 |
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Description: bayesian network is a probablistic model,used for various applications like satellite tracking,missile tracking and so on.
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Size: 3739648 |
Author: schumacher |
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Description: 灰色系统理论中的灰色预测模型，多元灰色预测模型的构建，可用于系统建模，控制系统，模型设计，预测控制，视觉目标跟踪中的运动预测等应用。-Grey prediction model in Grey System Theory can be applied in system modeling, control system, model design, prediction control and motion estimation in visual object tracking, etc.
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Size: 355328 |
Author: 朱亮亮 |
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Description: Matlap model of Photovoltaic Systems Maximum Power
Point Tracking
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Size: 19456 |
Author: cong |
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Description: 用采取CT模型，利用matlab实现机动目标跟踪，-With the CT model to use matlab to achieve maneuvering target tracking,
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Size: 122880 |
Author: 633 |
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Description: 该代码用于实现视觉目标跟踪研究中的协方差跟踪，能够把多种时空特征融合于统一的模型中，在实现视觉目标跟踪时具有较好的鲁棒性，而且其维数等于使用特征的数量，与各个特征的维数无关，因此，其计算复杂度较小，实时性较好。-This code is used to realize covariance tracking in the research field of visual object tracking of computer vision. It enables fusion of various spatial-temporal features into an unified object feature model, hence robust to noise. In addition, its dimension is equal to the number of the features used and independent of the dimensions of the features used. Therefore, it satisfies the requirement of real-time application due to its low computation cost.
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Size: 133120 |
Author: 朱亮亮 |
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Description: 机动目标跟踪中常用的一种跟踪模型—当前统计模型。另外附上一些儿文档及卡尔曼滤波的代码-Maneuvering target tracking commonly used as a tracking model- current statistical model. Some children attach additional documents and Kalman filter code
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Size: 10940416 |
Author: 岳雨豪 |
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Description: This article introduces the concept of maneuver strategy and its transition probability matrix, and then builds a target tracking
model with multi-motion and multi-maneuver strategy model based on these concepts in order to resolve the problem of
undesired tracking performance especially when unexpected maneuver strategy changes of target occurs. To achieve further
improvements in tracking accuracy, a self-adaptive algorithm for maneuver strategy transition probability matrix is proposed in
this article, by utilizing the compression ratio of the maneuver strategy error. Besides, considering that most of the observation
platforms are already able to provide multi-group measurements different sensors, information filtering is combined in this
article to fuse and integrate multi-group measurements, thus effectively improving estimation stability and ameliorating the
inevitable soaring estimation error through target’s unexpected changes of maneuver strategy-This article introduces the concept of maneuver strategy and its transition probability matrix, and then builds a target tracking
model with multi-motion and multi-maneuver strategy model based on these concepts in order to resolve the problem of
undesired tracking performance especially when unexpected maneuver strategy changes of target occurs. To achieve further
improvements in tracking accuracy, a self-adaptive algorithm for maneuver strategy transition probability matrix is proposed in
this article, by utilizing the compression ratio of the maneuver strategy error. Besides, considering that most of the observation
platforms are already able to provide multi-group measurements different sensors, information filtering is combined in this
article to fuse and integrate multi-group measurements, thus effectively improving estimation stability and ameliorating the
inevitable soaring estimation error through target’s unexpected changes of maneuver strategy
Platform: |
Size: 483328 |
Author: Gomaa Haroun |
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