搜索资源列表
targets-detection-and-tracking
- 基于vc++6.0+opencv的运动目标的检测与跟踪，包括一个小车视频，主要功能是在噪声、静止背景下实现运动目标的检测-Vc++6.0+ opencv-based moving target detection and tracking, including a car video, the main function is in the noise, static background detection of moving objects
pll
- 数字通信中的锁相环（PLL）完整程序，包括噪声处理，可用于GPS的的跟踪和捕获-the matlab code of PLL ,including how to deal with the noise ,which can be used to acquiring and tracking on GPS
thermal_DLL
- gps延迟锁定环中对热噪声的模拟，考虑了热噪声对跟踪精度的影响，很不错的-gps delay locked loop in the thermal noise of the simulation, taking into account thermal noise on the impact of tracking accuracy, very good
cafilter
- 本程序是利用kalman filter实现人体关节点跟踪的程序，运用的是CA模型，噪声是白噪声！一起学习-This procedure is to use the realization of human joints kalman filter tracking procedures, the use of the CA model, the noise is white noise! Learning together
Particle_Filter
- 粒子滤波程序，仿真实现自由度机器人对目标的跟踪，使用kalman滤波估计总雅可比矩阵J，噪声为非高斯噪声-Particle filter procedure, simulation robot tracking of targets, the use of kalman filter estimated total Jacobian matrix J, the noise of non-Gaussian noise
Tracking
- 提出一种新的目标表示和定位方法,该方法是非刚体跟踪的核心技术.利用均质空间掩膜规范基于特征直方图的目标表示,该掩膜引入了适合于梯度优化的空间平滑相似函数,所以可以将目标定位问题转换为局部极大值求解问题.我们利用从Bhattacharyya系数倒出的规则作为相似度量,利用mean shift procedure完成优化求解.在给出的测试用例中, 本文方法成功解决了相机移动,阴影,以及其他的图象噪声干扰.文章对运动滤波和数据关联技术的集成也进行了讨论.-A new objective and pos
biye
- 基于投票算法的目标跟踪,基于二阶非线性投票的多目标跟踪算法。该算法通过目标匹配得到同一目标在不同帧中的位置，同时利用特征监测来处理目标的遮挡、分裂问题，并实现目标特征的实时更新。在目标匹配过程中，通过对目标前一帧与当前帧的特征相似性进行投票，得到匹配目标。利用视频图像进行实验，结果表明：该方法对噪声、阴影、遮挡、分裂等具有良好的鲁棒性，较好地实现了多目标的跟踪。-The method used object matching to get objects’ position in differe
Vehicle_Tracker_with_background_subtraction_and_k
- Vehicle Tracking using a background subtraction based on mixture of Gaussians, and Kalman filtering to remove noise. Require OpenCV to be installed. By Jonathan Gagne University of Waterloo jgagne@uwaterloo.ca
motion
- This project deals with the tracking and following of single object in a sequence of frames and the velocity of the object is determined. Algorithms are developed for improving the image quality, segmentation, feature extraction and for deterring
ADPF
- 基于统计决策规则提出自适应采样数粒子滤波算法, 在定义综合性能风险函数的基础, 推导出粒子数与滤波误差方差之间的关系式, 使得在跟踪过程中, 可以根据目标的机动情况在线调节粒子数, 以使跟踪性能 达到最优。在Matlab仿真平台下进行了闪烁噪声下的机动目标跟踪实验, 结果表明, 自适应采样数粒子滤波算法是一种有效的机动目标跟踪方法, 跟踪性能较基本粒子滤波算法提高了3.17倍。-Based on statistical decision rules of the number of adap
xtouying
- 背景差和帧差法实现运动人体的跟踪，具有搞噪声和消除大部分阴影功能-Background difference and frame difference method to achieve motion tracking of the human body, has engaged in the shadow of the noise and the elimination of most of the functionality
loop-gainKalmanfiltersourcecodepackage
- 自己编写的一个循环增益卡尔曼滤波程序包，用于对机动目标进行检测和跟踪的滤波算法，给出目标数学模型和噪声模型，仿真后给出平均观测误差。程序里相应位置有标有注释。供做雷达机动目标检测和跟踪方面研究的人员参考。-I have written a loop-gain Kalman filter package, used for maneuvering target detection and tracking of the filter algorithm, given objective mathe
as
- To improve the boiler drum level control system of a power plant, the three challenging issues encountered include (1) effect of ‘‘false water level’’, (2) controller parameter mismatches due to variant working conditions and (3) signal noise cau
noisetracking
- 包含M文件，培训和跟踪落实的噪音中描述的算法： [1] J.S.厄克伦斯和R. Heusdens，“非平稳噪声跟踪基于数据驱动的递归噪声功率的估计”，IEEE期刊。音频，语音卷。 16，第6页。1112年至1123年，2008年8月。 见Descr iption.doc在zip文件。-Contains m-files to train and implement the noise tracking algorithm described in:
Noise_Tracking
- 根据” J.S. Erkelens and R. Heusdens, "Tracking of nonstationary noise based on data-driven recursive noise power estimation”所开发的源码-noisetracker based on data-driven recursive noise power estimation
noisetracking
- noise tracking techniqe
target-tracking
- 考虑两辆车在道路上同向行驶，在O-16s时，两车均保持匀速直线运动，由安装在后车上的车载毫米波雷达检测出与前车的距离为150m，相对速度为-3m/s，方位角 。在16-20s时，前车向右偏转，与后车的相对角加速度为 。后车加速，与前车的纵向相对加速度为 。雷达的扫描周期为T=0.1s，系统噪声为 ， 。量测误差为 。-Consider the two cars traveling the same direction on the road, in the O-16s, the two vehi
covariance-tracking
- 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 variou
Two-variables-Kalman-tracking-state
- 两变量卡尔曼跟踪状态 只有一个观测结果，可同时获得多个状态变量 噪音可以是时变的，同时改变R Q看结果的不同-Two variables Kalman tracking state is only one observation can also get more state variable noise can be time-varying, while changing the RQ to see the results of different
Noisetracking
- Tracking of Nonstationary Noise Based on Data-Driven Recursive Noise Power Estimation的code(Tracking of Nonstationary Noise Based on Data-Driven Recursive Noise Power Estimation matlab code)