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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
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基于视频的运动跟踪检测，提供了一种实时动态的检测方法-Video-based motion tracking and detection, provides a dynamic real-time detection method
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This application detects motion in real time. A webcam could be used.
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matlab 程实 实现布朗运动 源程序-matlab source Brownian motion process to achieve real
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Real-time motion detection in video surveillance using a level
set-based energy functional
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本算法用matlab实现了实现实时视频中动态目标的跟踪，-The realization of dynamic target tracking in the real-time video
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Calculate the eigenvalues of many 3x3 real symmetric matrices.-Calculate the eigenvalues of many 3x3 real symmetric matrices. Computation is non-iterative, based on fully vectorized matlab matrix operations, and GPU computation is supported. It is fa
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Real time intrusion detection.It needs webcam to connect and Matlab 2010 with image acquisition toolbox.
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Real time Face Detection/motion detection in Matlab
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实现移动机器人匀速运动模型下，基于UKF方法的移动机器人状态实时估计。(Real time estimation of the state of the mobile robot based on UKF method is realized under the uniform motion model of the mobile robot.)
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3D点云重建 3D点云重建Berkeley SfM is a structure from motion library created to explore new solutions to challenging 3D reconstruction problems (large scale, indoors, incremental, homogeneously textured, etc.). It is developed by(Structrue From Motion for
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描述一个卡尔曼滤波问题需要两个模型，一个是描述系统的状态方程，一个是观测方程，观测量通过观测方程与状态变量建立联系，由观测量估计状态值。与其他频域滤波器不同，卡尔曼滤波器不需要观测和估计的历史记录，可以直接在时域进行设计和使用，是一个时域滤波器，适用于处理实时数据。
对于一个运动模型，建立卡尔曼滤波模型，进行仿真，设已知初始时刻运动目标的真实位置和速度，并已知卡尔曼滤波使用的初始状态值，对该问题给出仿真；进一步分析该问题的稳态卡尔曼解，直接使用稳态卡尔曼滤波（滤波器）仿真该问题。
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