Represents a modality operating over an image pyramid. More...

Classes
struct	Candidate
	Candidate feature with a score. More...
Public Member Functions
virtual	~QuantizedPyramid ()
virtual void	quantize (Mat &dst) const =0
	Compute quantized image at current pyramid level for online detection.
virtual bool	extractTemplate (Template &templ) const =0
	Extract most discriminant features at current pyramid level to form a new template.
virtual void	pyrDown ()=0
	Go to the next pyramid level.
Static Protected Member Functions
static void	selectScatteredFeatures (const std::vector< Candidate > &candidates, std::vector< Feature > &features, size_t num_features, float distance)
	Choose candidate features so that they are not bunched together.

Detailed Description

Represents a modality operating over an image pyramid.

Constructor & Destructor Documentation

virtual cv::linemod::QuantizedPyramid::~QuantizedPyramid ( ) [virtual]

virtual void cv::linemod::QuantizedPyramid::quantize ( Mat & dst ) const [pure virtual]

Compute quantized image at current pyramid level for online detection.

Parameters:

[out] dst The destination 8-bit image. For each pixel at most one bit is set, representing its classification.

virtual bool cv::linemod::QuantizedPyramid::extractTemplate ( Template & templ ) const [pure virtual]

Extract most discriminant features at current pyramid level to form a new template.

Parameters:

[out] templ The new template.

virtual void cv::linemod::QuantizedPyramid::pyrDown ( ) [pure virtual]

Go to the next pyramid level.

static void cv::linemod::QuantizedPyramid::selectScatteredFeatures	(	const std::vector< Candidate > &	candidates,
		std::vector< Feature > &	features,
		size_t	num_features,
		float	distance
	)		`[static, protected]`

Choose candidate features so that they are not bunched together.

Parameters:

[in]	candidates	Candidate features sorted by score.
[out]	features	Destination vector of selected features.
[in]	num_features	Number of candidates to select.
[in]	distance	Hint for desired distance between features.

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