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Description: 吉布斯定轨法。
输入：轨道上任意三个点的位矢(R1,R2,R3)；
输出：质点在R2端点时的速度V2；ierr是个判断符号，返回的ierr是零的话，就说明‘R1,R2,R3’共面，如果ierr是1的话说明‘R1,R2,R3’不共面(正常情 况下，要构成轨道的话，‘R1,R2,R3’一定共面 ，即ierr是零，如果ierr是1的话说明输入的‘R1,R2,R3’不共面不能构成轨道。
此函数用于：任意给定三个空间共面的向量，可以确定质点在R2处的速度V2，也就得到了轨道上的一个状态向量(R2,V2),调用前面的函数就可以确定其轨道，及任意时刻的状态。-Gibbs set the track method. Input: track any three points of the bit vector (R1, R2, R3) output: particle at R2 endpoint speed V2, ierr is a judgment symbol, The ierr that is returned is zero, then, it means' of R1, R2,, R3, ' coplanar, if ierr is 1, then description' of R1, R2,, R3, ' not a total surface (under normal circumstances, you want to constitute a track, then,' of R1, R2, R3, ' a certain total surface, ierr is zero, if ierr is an instructions to enter the words ' of R1, R2, R3' coplanarity can not constitute a track. This function is used: for any given three space vector of the surface, can determine the particle at the speed V2, R2 also track a state vector (R2, V2), call the previous function can determine its orbit, and at any time of the state.
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Size: 1024 |
Author: cky001 |
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Description:
求解Lambert问题。
输入：轨道上两个点的位矢R1、R2，以及从R1到R2所用的时间t(缺点是脉冲太大)。
输出：质点在R1端点的速度V1，质点在R2端点的速度V2.
此函数用于：在给定轨道上两个点的位矢R1、R2，以及从R1到R2所用的时间t。求解V1、V2。再调用前面的函数就可以确定轨道根数，及任意时刻质点的状态。-To solve the Lambert problem. Input: track two-point position vector R1, R2, and R1 to R2 used in the time t (The disadvantage is that the pulse is too large). Output: particle R1 endpoint speed V1, the particle in the R2 endpoint speed V2. This function is used: two points in a given orbit position vector R1, R2, and from R1 to R2 with the time t. Solve the V1 and V2. And then call the previous function can determine the orbital elements, and any moment of the particle' s state.
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Size: 1024 |
Author: cky001 |
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Description: 粒子滤波（ParticleFilter）跟跟踪算法，能跟踪主动镜头下的目标，效果非常好！
-Particle filter (ParticleFilter) with the tracking algorithm can track the initiative target lens, very good!
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Size: 3072 |
Author: linguokai |
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Description: 该程序用粒子滤波的方法跟踪一个机器人并根据WiFii信号修改位置信息。-The program to track a robot with particle filter method WiFii signal to modify the location information.
Platform: |
Size: 30720 |
Author: 系统，结构 |
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Description: 在粒子滤波加颜色直方图实现了视频目标跟踪的基础上，加了遮挡处理。即当目标被遮遮挡的时候进行了特殊的处理，当目标重新出现的时候能够继续对目标进行跟踪，不失跟。
-Particle filter add color histogram on the basis of the video target tracking, plus a block. That is, when the target is obscured by cover the special treatment, be able to continue when the target re-emergence of the target track, losing with.
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Size: 7168 |
Author: zd |
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Description: 用opencv实现的粒子滤波跟踪程序序。需要手动选取跟踪物体-opencv
-Particle filter tracking with opencv program sequence. Need to manually select the track object-opencv
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Size: 3072 |
Author: didazff |
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Description: 用卡尔曼 滤波跟踪平面质点的运动，首先建立一个平面坐标系，则这个质点的运动要三个变量来描述-Kalman Kalman filter to track the movement of the plane particle
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Size: 1024 |
Author: chenlei |
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Description: particle filter algorithm to track object.
written in C++ and OpenCV
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Size: 5120 |
Author: dana |
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Description: particle filter algorithm to track multiple object
use C++ and OpenCV
Platform: |
Size: 3072 |
Author: dana |
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Description: Simple Tracker
*Tracking* , or particle linking, consist in re-building the trajectories
of one or several particles as they move along time. Their position is
reported at each frame, but their identity is yet unknown: we do not know
what particle in one frame corresponding to a particle in the previous
frame. Tracking algorithms aim at providing a solution for this problem.
-SIMPLETRACKER a simple particle tracking algorithm that can deal with gaps
*Tracking* , or particle linking, consist in re-building the trajectories
of one or several particles as they move along time. Their position is
reported at each frame, but their identity is yet unknown: we do not know
what particle in one frame corresponding to a particle in the previous
frame. Tracking algorithms aim at providing a solution for this problem.
|simpletracker.m| is- as the name says- a simple implementation of a
tracking algorithm, that can deal with gaps. A gap happens when one
particle that was detected in one frame is not detected in the subsequent
one. If not dealt with, this generates a track break, or a gap, in the
frame where the particle disappear, and a false new track in the frame
where it re-appear.
Platform: |
Size: 46080 |
Author: zfhou |
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Description: 颜色直方图粒子滤波器，并给出了英文参考文献；
运行方式：在前景窗口，按p键停止，在目标区域点击鼠标，让程序自动识别出目标轮廓，再次按p键，即可跟踪-The color histogram particle filter, given English references operation modes: in the foreground window, press p stop clicking the mouse in the target area, allowing the program to automatically identify the target contour, press p again, you can track
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Size: 12938240 |
Author: 金圣韬 |
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Description: 基于粒子滤波的自由落体运动跟踪，一个篮球从高处落下利用粒子滤波的方法跟踪其过程-The freefall motion tracking based on particle filter, a basketball falling from a height using the particle filter method to track its process
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Size: 232448 |
Author: gaowushuang |
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Description: 本文针对摄像机运动情况下的多目标跟踪问题，提出了基于粒子滤波的跟踪算法。在粒子滤波算法基础上，将二阶自回归过程作为系统状态转移模型，HSV 颜色直方图作为观测模型，对视频中多个目标的位置、大小进行跟踪。实验结果表明，该算法能实时正确地跟踪多个目标，并对局部遮挡有较好的鲁棒性，也能在目标短暂消失导致跟踪失败后，在目标重新出现后及时捕获并继续进行跟踪。-A tracking algorithm based on particle filter is proposed to deal with multi-target tracking in a camera motion situation. In the
proposed algorithm, the position and scale of targets in the video are tracked by using a second-order auto-regressive process as the transition
model and an HSV histogram as the observation model. Experimental results show that the proposed algorithm can track multitarget
correctly in real-time and is robust to the partial occlusion. In addition, it can recover from tracking failure due to the target out of camera for a while.
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Size: 405504 |
Author: wenping |
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Description: 本文提出了一种复杂条件下基于子空间梯度方向直方图跟踪的方法，通过大量样本的离线训练构建目标的投影子
空间，并用梯度方向直方图在子空间的投影作为新的目标描述特征．为了满足实时性的要求，采用积分直方图方法
提高粒子特征的计算速度；然后结合粒子滤波方法在子空间中计箅粒子与训练样本集之间的相似度，进而估计目标
的运动参数．实验结果表明，该方法能够在光照变化、噪声干扰、模糊、目标姿态和尺度改变，以及部分遮捎等恶劣条
件下实现准确跟踪，比传统的跟踪方法具有更高的跟踪精度和跟踪鲁棒性，能够满足地面侦察任务在多种复杂条件下对感兴趣目标进行准确跟踪的需求．-This paper presents a complex condition gradient orientation histogram based on subspace tracking methods, through a large number of samples offline training build target subspace projection and gradient orientation histogram in subspace projection as a new target descriptive characteristics. In order to meet the requirements of real-time, using integral histogram method improves the computing speed of the particle characteristics then combined with particle filter in subspace meter grate particles and the similarity between the training sample set, and then estimate the target motion parameters. Experimental results show that this method can change in the light, noise, blur, target attitude and scale changes, and take along some cover in bad condition for accurate tracking, than the traditional tracking method has higher tracking accuracy and robustness to meet the ground reconnaissance missions in a variety of complex conditions accurately track targets of interest requirements.
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Size: 555008 |
Author: wenping |
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Description: 本文主要研究海面运动船只的识别与跟踪技术。首先概述了海上运动目标检测和跟踪的研究现状；对目前主要的显著区域提取、运动目标识别和跟踪方法进行了简要概述；提出了基于视觉注意和HOG特征相融合的海上船只目标检测方法；利用多特征融合的粒子滤波算法对运动目标进行了跟踪。-This paper studies the sea sport vessel identification and tracking technology. First, an overview of maritime moving target detection and tracking research status right now the main salient region extraction, moving target identification and tracking methods are briefly outlined proposed based on visual attention and HOG feature fusion of sea vessels target detection method utilization multi-feature fusion particle filter algorithm to track the moving target.
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Size: 5353472 |
Author: wenping |
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Description: 了适应跟踪过程中目标光照条件的变化，并对目标特征进行在线更新，提出一种将局部二元模式(LBP)
特征与图像灰度信息相融合，同时结合增量线性判别分析对目标进行跟踪的算法．跟踪开始前，为了获得比较准确的目标描述，使用混合高斯模型和期望最大化算法对目标进行分割；跟踪过程中，通过蒙特卡罗方法对目标区域和背景区域进行采样，并更新特征空间参数．得到目标和背景的最优分类面；最后使用粒子滤波器结合最优分类面对目标状态进行预测．通过光照变化的仿真视频和自然场景视频的跟踪实验，验证了文中算法的有效性．-Tracking process to adapt to changes in the target lighting conditions, and the target feature for online updates, proposes a local binary pattern (LBP) features and image intensity information integration, combined with incremental linear discriminant analysis for target tracking algorithms. Track begins, in order to obtain a more accurate description of the objectives, the use of Gaussian mixture models and expectation maximization algorithm for target segmentation tracking process, through the Monte Carlo method of the target area and the background area sampled and updated feature space parameters. Get the optimal target and background classification surface finally Using Particle Filter optimal classification predict the state of the face of goal. By varying illumination simulation video and natural scenes video tracking experiment to verify the effectiveness of the proposed algorithm.
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Size: 608256 |
Author: wenping |
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Description: 颗粒跟踪’建立一个或多个颗粒随时间变化而形成的轨迹。跟踪算法记录下颗粒在每帧数据中的位置。本算法的亮点是间断处理。间断是指一个颗粒在一帧中出现而在下一帧中消失。如果不做处理，当该颗粒在后续帧中重现时，将产生新的虚假跟踪。-Particle tracking to create one or a plurality of particles with time and the formation of the track. Particle tracking algorithm recorded in the data in each frame position. The highlight of this algorithm is intermittent treatment. Discontinuity refers to a particle in a frame appears and disappear in the next frame. If not treated, when the particles are reproduced in subsequent frames, it will generate a new false tracking.
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Size: 98304 |
Author: 李时针 |
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Description: 该代码是粒子滤波实现弱小目标的检测前跟踪。-The code is particle filter to implementation the weak target track before detection.
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Size: 2048 |
Author: liaoliangxiong |
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Description: 3D Head Trajectory using a Single Camera
Video surveillance applications need tools to track people trajectories. We present here a
new method to extract the 3D head trajectory of a person in a room using only one calibrated
camera. A 3D ellipsoid representing the head is used to track the person with a hierarchical
particle filter. This method can run in quasi-real-time providing reasonable 3D errors for a
monocular system.
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Size: 382976 |
Author: kaw |
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Description: This thesis proposes a novel algorithm for integrated face detection and face tracking
based on the synthesis of an adaptive particle filtering algorithm and an AdaBoost face detection
algorithm. A novel Adaptive Particle Filter (APF), based on a new sampling technique, is
proposed to obtain accurate estimation of the proposal distribution and the posterior distribution
for accurate tracking in video sequences. The proposed scheme, termed a Boosted Adaptive
Particle Filter (BAPF), combines the APF with the AdaBoost algorithm. The AdaBoost
algorithm is used to detect faces in input image frames, while the APF algorithm is designed to
track faces in video sequences. The proposed BAPF algorithm is employed for face detection,
face verification, and face tracking in video sequences. Experimental results confirm that the
proposed BAPF algorithm provides a means for robust face detection and accurate face tracking
under various tracking scenarios.
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Size: 1057792 |
Author: Trabelsi |
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