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Description: A multi-target tracking toolbox based on the MTT Library of the InstantVision ISE with expanded functionality and tools for off-line design, analysis and testing. The toolbox contains the implementation of distance calculation methods (e.g. city-block based), data assignment and association strategies (e.g. ENN and JVC), state prediction filters (e.g. IMM) with video marking and debugging tools in order to support a complex multi-target tracking system design.
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Size: 1024 |
Author: Aka |
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Description: （交互式多模型算法）目标跟踪程序,java语言编写，包含了kalman滤波。这种方法的特点是在各模型之间“转换”，自动调节滤波带宽，和适合机动目标的跟踪。可以直接调用，附有示例代码-A multi-target tracking toolbox based on the MTT Library of the InstantVision ISE with expanded functionality and tools for off-line design, analysis and testing. The toolbox contains the implementation of distance calculation methods (e.g. city-block based), data assignment and association strategies (e.g. ENN and JVC), state prediction filters (e.g. IMM) with video marking and debugging tools in order to support a complex multi-target tracking system design.
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Size: 14336 |
Author: june |
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Description: Kalman 滤波和平滑工具箱，包括了
Kalman 滤波和平滑
EKF 和 平滑
CKF 和平滑
UKF 和平滑
GHQF 和平滑
IMM 滤波和平滑-EKF/UKF is an optimal filtering toolbox for Matlab. Optimal filtering is a frequently used term for a process, in which the state of a dynamic system is estimated through noisy and indirect measurements. This toolbox mainly consists of Kalman filters and smoothers, which are the most common methods used in stochastic state-space estimation. The purpose of the toolbox is not to provide highly optimized software package, but instead to provide a simple framework for building proof-of-concept implementations of optimal filters and smoothers to be used in practical applications.
Including:
1. Kalman filters and smoothers
2. Extended Kalman filters and smoothers
3. Unscented Kalman filters and smoothers
4. Gauss-Hermite Kalman filters and smoothers
5. Cubature Kalman filters and smoothers
6. Interacting Multiple Model (IMM) filters and smoothers
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Size: 150528 |
Author: yinchao |
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