vision.ForegroundDetector
Foreground detection using Gaussian mixture models
Description
TheForegroundDetector
compares a color or grayscale video frame to a background model to determine whether individual pixels are part of the background or the foreground. It then computes a foreground mask. By using background subtraction, you can detect foreground objects in an image taken from a stationary camera.
To detect foreground in an image :
Create the
vision.ForegroundDetector
object and set its properties.Call the object with arguments, as if it were a function.
To learn more about how System objects work, seeWhat Are System Objects?
Creation
Description
computes and returns a foreground mask using the Gaussian mixture model (GMM).detector
= vision.ForegroundDetector
sets properties using one or more name-value pairs. Enclose each property name in quotes. For example,detector
= vision.ForegroundDetector(Name,Value
)detector = vision.ForegroundDetector('LearningRate',0.005)
Properties
Usage
Description
computes the foreground mask for input imageforegroundMask
= detector(I
)I
, and returns a logical mask. Values of1
in the mask correspond to foreground pixels.
computes the foreground mask using theforegroundMask
= detector(I
,learningRate
)LearningRate
.
Input Arguments
Output Arguments
Object Functions
To use an object function, specify the System object™ as the first input argument. For example, to release system resources of a System object namedobj
, use this syntax:
release(obj)
Examples
References
[1] Kaewtrakulpong, P. and R. Bowden.An Improved Adaptive Background Mixture Model for Realtime Tracking with Shadow Detection. In Proc. 2nd European Workshop on Advanced Video Based Surveillance Systems, AVBS01, VIDEO BASED SURVEILLANCE SYSTEMS: Computer Vision and Distributed Processing (September 2001)
[2] Stauffer, C. and W.E.L. Grimson.混合自适应背景模型实时Tracking, Computer Vision and Pattern Recognition, IEEE Computer Society Conference on, Vol. 2 (06 August 1999), pp. 2246-252 Vol. 2.