onWorkspace Class Reference

Applies half-Gaussian model with premise that targets lie to one side of the distribution. More...

Inheritance diagram for onWorkspace:

Collaboration diagram for onWorkspace:

Public Member Functions
def	__init__ (self, bgCfg=None, processor=None, bgMod=None)
	Constructor for single Gaussian model background detector. More...
def	adapt (self)
	Update the Gaussian model based on recent measurement. More...
def	correct (self)
	Generate a correction to the model. More...
def	displayState (self)
def	displayState (self)
def	emptyDebug (self)
	Return empty debug state information. More...
def	emptyState (self)
	Return empty state. More...
def	estimateOutlierMaskRGBD (self, theStream, numLoop=0, tauRatio=0.75, incVis=False)
def	get (self)
def	getDebug (self)
	Return current/latest debug state information. More...
def	getState (self)
	Return current/latest state. More...
def	info (self)
	Provide information about the current class implementation. More...
def	measure (self, I)
	Takes image and generates the detection result. More...
def	predict (self)
	Predictive model of measurement. More...
def	process (self, I)
	Given a new measurement, apply entire BG modeling pipeline. More...
def	saveTo (self, fPtr)
	Save Gaussian model information to given HDF5 pointer. More...
def	set (self)
Public Member Functions inherited from bgGaussian
def	saveCfG (self, outFile)
	Save current instance to a configuration file. More...
Public Member Functions inherited from bgImage
def	__init__ (self, processor=None)
Public Member Functions inherited from Base
def	__init__ (self)
	Instantiate a detector Base activity class object. More...
def	detect (self, signal)
	Run detection only processing pipeline (no adaptation). More...
def	save (self, fileName)
	Outer method for saving to a file given as a string. More...

Static Public Member Functions
def	buildAndCalibrateFromConfig (theConfig, theStream, incVis=False)
def	buildFromCfg (theConfig, processor=None)
	Build an onWorkspace instance from an algorithm configuration node. More...
def	load (fileName)
def	loadFrom (fptr)
	Empty method for loading internal information from HDF5 file. More...
Static Public Member Functions inherited from bgGaussian
def	buildAndCalibrateFromConfigRGBD (theConfig, theProcessor, theStream, incVis=False)
Static Public Member Functions inherited from Base
def	load (fileName, relpath=None)
	Outer method for loading file given as a string (with path). More...

Public Attributes
	bgI
	measI
	mu
	state
Public Attributes inherited from bgGaussian
	bgI
	config
	errI
	improcessor
	imsize
	maxE
	measI
	mu
	nrmE
	sigma
	sqeI
Public Attributes inherited from inImage
	Ip
	processor
Public Attributes inherited from Base
	x
	Detection state. More...

Detailed Description

Applies half-Gaussian model with premise that targets lie to one side of the distribution.

Note

A note on the improcessor. If the basic version is used, then it performs pre-processing. If a triple version is used, then the mid-processor will perform operations on the detected part rather than the default operations. The mid-processor can be used to test out different options for cleaning up the binary data.

Constructor & Destructor Documentation

__init__()

def __init__	(		self,
			bgCfg = None,
			processor = None,
			bgMod = None
	)

Constructor for single Gaussian model background detector.

Parameters

[in]	bgMod	The model or parameters for the detector.
[in]	bgCfg	The model or parameters for the detector.

Reimplemented from bgGaussian.

Member Function Documentation

adapt()

def adapt

(

self

)

Update the Gaussian model based on recent measurement.

In this case, the mean and the variance are updated. Depending on the run-time options, all means/variances will be updated or only those classified as background. The latter avoids adapting to foreground elements while still permitting slow change of the background model.

Usually, during the model estimation phase (assuming an empty scene with background elements only) adaptation of all pixels should occur. During deployment, if adaptation is to be performed, then it is usually best to not apply model updating to foreground elements, which are interpreted as fast change elements of the scene.

Reimplemented from bgGaussian.

buildAndCalibrateFromConfig()

def buildAndCalibrateFromConfig (   theConfig,   theStream,   incVis = False  )

static

buildFromCfg()

def buildFromCfg (   theConfig,   processor = None  )

static

Build an onWorkspace instance from an algorithm configuration node.

Parameters

[out]

bgDet

Instantiated onWorkspace background model detector.

correct()

def correct

(

self

)

Generate a correction to the model.

In standard schemes, there are no corrections to the estimates. The classification result is presumed to be correct. Corrections would imply some sort of temporal regularization. Spatial regularization is usually done through image-based mid-processing.

Reimplemented from bgGaussian.

displayState() [1/2]

def displayState

(

self

)

Reimplemented from bgGaussian.

displayState() [2/2]

def displayState

(

self

)

Reimplemented from bgGaussian.

emptyDebug()

def emptyDebug

(

self

)

Return empty debug state information.

Useful if contents needed beforehand.

Reimplemented from bgGaussian.

emptyState()

def emptyState

(

self

)

Return empty state.

Useful if contents needed beforehand.

Reimplemented from bgGaussian.

estimateOutlierMaskRGBD()

def estimateOutlierMaskRGBD	(		self,
			theStream,
			numLoop = 0,
			tauRatio = 0.75,
			incVis = False
	)

get()

def get

(

self

)

Reimplemented from bgGaussian.

getDebug()

def getDebug

(

self

)

Return current/latest debug state information.

Usually the debug state consists of internally computed information that is useful for debugging purposes and can help to isolate problems within the implemented class or with downstream processing that may rely on assumptions built into this implemented class.

Reimplemented from bgGaussian.

getState()

def getState

(

self

)

Return current/latest state.

Reimplemented from bgGaussian.

info()

def info

(

self

)

Provide information about the current class implementation.

Exists for reproducibility purposes. Usually stores the factory information used to build the current class instance.

Reimplemented from bgGaussian.

load()

def load (   fileName )

static

Reimplemented from bgGaussian.

loadFrom()

def loadFrom (   fPtr )

static

Empty method for loading internal information from HDF5 file.

Load data from given HDF5 pointer. Assumes in root from current file pointer location.

Reimplemented from bgGaussian.

measure()

def measure	(		self,
			I
	)

Takes image and generates the detection result.

Parameters

[in]

I

Image to process.

Reimplemented from bgGaussian.

predict()

def predict

(

self

)

Predictive model of measurement.

In standard schemes, the expectation is that the background model is static (a constant state model). Thus, the default prediction is no update.

Reimplemented from bgGaussian.

process()

def process	(		self,
			I
	)

Given a new measurement, apply entire BG modeling pipeline.

Parameters

[in]

I

New image measurement.

Reimplemented from bgGaussian.

saveTo()

def saveTo	(		self,
			fPtr
	)

Save Gaussian model information to given HDF5 pointer.

Creates a custom group at the pointer root with the Gaussian background model information.

Parameters

[in]

fPtr

File pointer.

Reimplemented from bgGaussian.

set()

def set

(

self

)

Reimplemented from bgGaussian.

Member Data Documentation

bgI

bgI

measI

measI

mu

mu

state

state

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The documentation for this class was generated from the following file:

• /home/pvela/python/detector/detector/bgmodel/onWorkspace.py