cv.MotionSaliencyBinWangApr2014

A Fast Self-tuning Background Subtraction Algorithm for Motion Saliency

Implementation of MotionSaliencyBinWangApr2014 for Motion Saliency.

Saliency API

Many computer vision applications may benefit from understanding where humans focus given a scene. Other than cognitively understanding the way human perceive images and scenes, finding salient regions and objects in the images helps various tasks such as speeding up object detection, object recognition, object tracking and content-aware image editing.

About the saliency, there is a rich literature but the development is very fragmented. The principal purpose of this API is to give a unique interface, a unique framework for use and plug sever saliency algorithms, also with very different nature and methodology, but they share the same purpose, organizing algorithms into three main categories:

Static Saliency
Motion Saliency
Objectness

Saliency UML diagram:

To see how API works, try tracker demo: computeSaliency_demo.m.

Motion Saliency Algorithms

Algorithms belonging to this category, are particularly focused to detect salient objects over time (hence also over frame), then there is a temporal component sealing cosider that allows to detect "moving" objects as salient, meaning therefore also the more general sense of detection the changes in the scene.

Presently, the Fast Self-tuning Background Subtraction Algorithm [BinWangApr2014] has been implemented.

References

[BinWangApr2014]:

Bin Wang and Piotr Dudek. "A Fast Self-tuning Background Subtraction Algorithm". In Computer Vision and Pattern Recognition Workshops (CVPRW), 2014 IEEE Conference on, pages 401-404. IEEE, 2014.

Superclasses	handle
Sealed	false
Construct on load	false

ImageHeight	Height of input image.
ImageWidth	Width of input image.
id	Object ID

	addlistener	Add listener for event.
	clear	Clears the algorithm state
	computeSaliency	Compute the saliency
	delete	Destructor
	empty	Checks if detector object is empty
	eq	== (EQ) Test handle equality.
	findobj	Find objects matching specified conditions.
	findprop	Find property of MATLAB handle object.
	ge	>= (GE) Greater than or equal relation for handles.
	getDefaultName	Returns the algorithm string identifier
	gt	> (GT) Greater than relation for handles.
	init	This function allows the correct initialization of all data structures that will be used by the algorithm
Sealed	isvalid	Test handle validity.
	le	<= (LE) Less than or equal relation for handles.
	listener	Add listener for event without binding the listener to the source object.
	load	Loads algorithm from a file or a string
	lt	< (LT) Less than relation for handles.
	ne	~= (NE) Not equal relation for handles.
	notify	Notify listeners of event.
	save	Saves the algorithm parameters to a file
	setImagesize	This is a utility function that allows to set the correct size (taken from the input image) in the corresponding variables that will be used to size the data structures of the algorithm