Description: This contained BG/FG detection(simple version and adaptive background mixture models), blob tracking(connected component tracking and MSPF resolver, mean shift, particle filter), Kalman filter using OpenCV. It can be helpful who studying object detection and tracking algorithm. Also, It contain the video clip for testing algorithm.-This is contained BG/FG detection(simple version and adaptive background mixture models), blob tracking(connected component tracking and MSPF resolver, mean shift, particle filter), Kalman filter using OpenCV. It can be helpful who studying object detection and tracking algorithm. Also, It contain the video clip for testing algorithm. Platform: |
Size: 52594688 |
Author:byunghee |
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Description: 本次实验来源于opencv自带sample中的例子，该例子是用kalman来完成一个一维的跟踪，即跟踪一个不断变化的角度。在界面中表现为一个点在圆周上匀速跑，然后跟踪该点。看起来跟踪点是个二维的，其实转换成角度就是一维的了。
Kalman滤波理论主要应用在现实世界中个，并不是理想环境。主要是来跟踪的某一个变量的值，跟踪的依据是首先根据系统的运动方程来对该值做预测，比如说我们知道一个物体的运动速度，那么下面时刻它的位置按照道理是可以预测出来的，不过该预测肯定有误差，只能作为跟踪的依据。另一个依据是可以用测量手段来测量那个变量的值，当然该测量也是有误差的，也只能作为依据，不过这2个依据的权重比例不同。最后kalman滤波就是利用这两个依据进行一些列迭代进行目标跟踪的。-This experiment from the examples the opencv own sample, the example is to complete a one-dimensional tracking using kalman, ie, tracking a changing point of view. Performance in the interface as a point in the circle on steady running, then track the points. Looks like the tracking point is a two-dimensional, in fact, convert the angle is one-dimensional. The main application of the Kalman filter theory in the real world, not the ideal environment. Is the value of a variable to keep track of the basis for tracking the first according to the equation of motion of the system to the value forecast, for example, we know the velocity of an object, then the following moment of its location in accordance with the truth can be predicted , but the forecast is certainly a margin of error, only as a basis for tracking. Another is based on measurements to measure the value of that variable, Of course, this measurement error can only be used as the basis of these two basis weights the different pr Platform: |
Size: 339968 |
Author:wuwei |
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Description: 使用卡尔曼滤波器设计的运动物体跟踪。适用于背景也是动态变化的物体跟踪-Tracking moving objects using a Kalman filter design. Applies to the background also dynamic object tracking Platform: |
Size: 878592 |
Author:洪依 |
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Description: 运动目标跟踪在工业过程控制、医学研究、成像制导等领域具有重要的实用价值。目前的研究多基于背景静止的情况，对背景发生移动的情况研究较少。提出了一套完整的移动背景下的目标跟踪算法，首先使用基于互信息的方法配准序列图像的背景。然后使用差分的方法进行运动区域检测，并将其与图像分割技术相结合，得到目标跟踪模板。目标的跟踪基于Kalman滤波的预测，其匹配过程仍基于互信息理论，实验结果证明：该算法具有较高的计算效率和准确性，应用前景广泛。-it is of important practical value to
track moving objects in the fields of industrial process control，medical research，imaging guidance，etc．At present most research in this field are often based on static background，while those based on moving background
ale rather less．A complete algorithm
of object tracking in the moving background
was
proposed．Firstly，the
background
of
sequence images
were
registered by
using
the mutual
information．Secondly，a
differential method
was
used to detect
moving object in combination
with
image segmentation technology
to
get
the
object template．Object
tracking
was based on Kalman filter and the
object matching
was still based on the mutual information
theory．The experiments
show that
object tracking
is
rapid，accurate
and robust
by using
this
algorithm．
Computational efficiency
and
accuracy
of this new
tracking algorithm
is SO
high，and
its
application
prospect
will be broad． Platform: |
Size: 430080 |
Author:wenping |
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Description: 假设一物体围绕一圆周运动，角加速度是白噪声，观测噪声也是零均值的白噪声。编程使用卡尔曼滤波器实现运动物体的跟踪。-Suppose an object around a circular motion, the angular acceleration is white noise, measurement noise is zero mean white noise. Programming using a Kalman filter to achieve tracking moving objects. Platform: |
Size: 4096 |
Author:gxr |
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Search - OBJECT TRACKING USING KALMAN FILTER