Detailed Description

Defines 2D-based feature detection.

Data Structures
struct	dwFeature2DDetectorConfig
	Holds configuration parameters for a feature detector. More...

Typedefs
typedef struct dwFeature2DDetectorObject const *	dwConstFeature2DDetectorHandle_t
	Handle representing a const feature detector. More...

typedef struct dwFeature2DDetectorObject *	dwFeature2DDetectorHandle_t
	Handle representing a feature detector. More...

Enumerations
enum	dwFeature2DDetectorType { DW_FEATURE2D_DETECTOR_TYPE_STD = 0 , DW_FEATURE2D_DETECTOR_TYPE_EX , DW_FEATURE2D_DETECTOR_TYPE_FAST9 , DW_FEATURE2D_DETECTOR_TYPE_COUNT }
	Defines different KLT tracking algorithms. More...

enum	dwFeature2DSelectionMaskType { DW_FEATURE2D_SELECTION_MASK_TYPE_UNIFORM = 0 , DW_FEATURE2D_SELECTION_MASK_TYPE_GAUSSIAN , DW_FEATURE2D_SELECTION_MASK_TYPE_COUNT }
	Feature distribution mask for extended detector. More...

Functions
DW_API_PUBLIC dwStatus	dwFeature2DDetector_detectFromImage (dwFeatureArray outputDetections, dwImageHandle_t image, dwFeatureArray preTrackedFeatures, const float32_t *d_normalizedCrossCorrelation, dwFeature2DDetectorHandle_t obj)
	Detects new features and append them after old tracked features. More...

DW_API_PUBLIC dwStatus	dwFeature2DDetector_detectFromPyramid (dwFeatureArray outputDetections, const dwPyramidImage pyramid, dwFeatureArray preTrackedFeatures, const float32_t d_normalizedCrossCorrelation, dwFeature2DDetectorHandle_t obj)
	Detects new features and append them after old tracked features. More...

DW_API_PUBLIC dwStatus	dwFeature2DDetector_getCUDAStream (cudaStream_t *stream, dwFeature2DDetectorHandle_t obj)
	Gets the CUDA stream used by the feature Detector. More...

DW_API_PUBLIC dwStatus	dwFeature2DDetector_getPVAStream (cupvaStream_t *stream, dwFeature2DDetectorHandle_t obj)
	Gets the CUPVA stream used by the feature Detector. More...

DW_API_PUBLIC dwStatus	dwFeature2DDetector_getValidTrackedCount (const uint32_t **d_validTrackedCount, dwFeature2DDetectorHandle_t obj)
	dwFeature2DDetector_getValidTrackedCount More...

DW_API_PUBLIC dwStatus	dwFeature2DDetector_initDefaultParams (dwFeature2DDetectorConfig *params)
	Initializes dwFeature2DDetector parameters with default values. More...

DW_API_PUBLIC dwStatus	dwFeature2DDetector_initDefaultParamsForCamera (dwFeature2DDetectorConfig params, const dwTransformation3f cameraToRig, dwConstCameraModelHandle_t cameraHandle)
	Initializes dwFeature2DDetector parameters with values best suited for the given camera using camera extrinsic (dwTransformation3f* cameraToRig) and camera intrinsic (dwConstCameraModelHandle_t cameraHandle) More...

DW_API_PUBLIC dwStatus	dwFeature2DDetector_initialize (dwFeature2DDetectorHandle_t obj, const dwFeature2DDetectorConfig config, cudaStream_t cudaStream, dwContextHandle_t context)
	Creates and initializes a feature Detector. More...

DW_API_PUBLIC dwStatus	dwFeature2DDetector_release (dwFeature2DDetectorHandle_t obj)
	Releases the feature Detector. More...

DW_API_PUBLIC dwStatus	dwFeature2DDetector_reset (dwFeature2DDetectorHandle_t obj)
	Resets a feature Detector. More...

DW_API_PUBLIC dwStatus	dwFeature2DDetector_setCUDAStream (cudaStream_t stream, dwFeature2DDetectorHandle_t obj)
	Sets the CUDA stream for CUDA related operations. More...

DW_API_PUBLIC dwStatus	dwFeature2DDetector_setMask (const uint8_t *d_mask, const uint32_t maskStrideBytes, const uint32_t maskWidth, const uint32_t maskHeight, dwFeature2DDetectorHandle_t obj)
	Sets a mask to ignore areas of the image. More...

DW_API_PUBLIC dwStatus	dwFeature2DDetector_setPVAStream (cupvaStream_t stream, dwFeature2DDetectorHandle_t obj)
	Sets the CUPVA stream for PVA related operations. More...

Variables
const uint32_t	DW_FEATURES2D_DETECTOR_MAX_CELL_SIZE = 128

Data Structure Documentation

◆ dwFeature2DDetectorConfig

struct dwFeature2DDetectorConfig

Data Fields
bool	autoGenerateFeatureID	Determines whether the detector generates unique feature ids for new detections automatically. If set to true, each new detected features will be assigned with a unique feature id. If set to false, dwFeatureArray::ids will be kept. Default is true.
uint32_t	blockSize	for DW_PROCESSOR_TYPE_PVA_0 or DW_PROCESSOR_TYPE_PVA_1 only Block window size used to compute the Harris Corner score. Must be 3, 5 or 7.
uint32_t	cellSize	Cell size in pixel to split the image into cells. Must be an integer multiplicaiton of 4
float32_t	detailThreshold	for DW_FEATURE2D_DETECTOR_TYPE_STD only features in the cell that have scores higher than this value will be considered as high frequency point and will always be outputed. If set it <= detectorScoreThreshold, all features detected are high frequency and the next numEvenDistributionPerCell will be invalid
uint32_t	detectionLevel	for DW_FEATURE2D_DETECTOR_TYPE_EX only STD detector always detects on level 0 pyramid image. Level at which features are detected Default to one (half of original image resolution)
float32_t	gaussianMaskCenterX	for DW_FEATURE2D_DETECTOR_TYPE_EX only Ignored when not using DW_FEATURE2D_SELECTION_MASK_TYPE_GAUSSIAN The center X of the Gaussian mask, range: [0.0f, 1.0f]
float32_t	gaussianMaskCenterY	for DW_FEATURE2D_DETECTOR_TYPE_EX only Ignored when not using DW_FEATURE2D_SELECTION_MASK_TYPE_GAUSSIAN The center Y of the Gaussian mask, range: [0.0f, 1.0f]
float32_t	gaussianMaskStDevX	for DW_FEATURE2D_DETECTOR_TYPE_EX only Ignored when not using DW_FEATURE2D_SELECTION_MASK_TYPE_GAUSSIAN The standard deviation in X of the Gaussian mask 1.0 means the standard deviation equals to the width of the image
float32_t	gaussianMaskStDevY	for DW_FEATURE2D_DETECTOR_TYPE_EX only Ignored when not using DW_FEATURE2D_SELECTION_MASK_TYPE_GAUSSIAN The standard deviation in Y of the Gaussian mask 1.0 means the standard deviation equals to the height of the image
uint32_t	gradientSize	for DW_PROCESSOR_TYPE_PVA_0 or DW_PROCESSOR_TYPE_PVA_1 only Gradient window size. Must be 3, 5 or 7.
float32_t	harrisK	Weigting K of the harris corner score defined as det(M) - K * trace(M) * trace(M), where M is the structural matrix 0.04 - 0.06 is used typically If set to zero the default value (5e-2) will be used.
uint32_t	harrisRadius	for DW_FEATURE2D_DETECTOR_TYPE_EX only STD detector use fixed harrisRadius = 1. Radius of detector harris averaging window If set to zero the default value (1) will be used
uint32_t	imageHeight	Height of the images that the Detector runs on. When PVA fast9 detector is used, the height should be in range of [65, 2448]
uint32_t	imageWidth	Width of the images that the Detector runs on. When PVA fast9 detector is used, the width should be in range of [65, 3264]
bool	isMaskAdjustmentEnabled	for DW_FEATURE2D_DETECTOR_TYPE_EX only Switch to use mask adjusment
dwFeature2DSelectionMaskType	maskType	for DW_FEATURE2D_DETECTOR_TYPE_EX only STD detector always output UNIFORM distribution. The type of feature selection mask
uint32_t	maxFeatureCount	Upper bound on number of features handled. When using EX detector, maxFeatureCount must be no less than the amount of cells, i.e., maxFeatureCount >= ceil(imageWidth / cellSize) * ceil(imageHeight / cellSize).
uint32_t	NMSRadius	for DW_FEATURE2D_DETECTOR_TYPE_EX and DW_FEATURE2D_DETECTOR_TYPE_FAST9 STD detector use fixed NMSRadius = 3. Radius of detector non-maximum suppression For EX detector, if it is set to zero the default value (1) will be used As for FAST9 detector, nonmax suppression will be enabled for non-zero value and will be disabled for zero
uint32_t	numEvenDistributionPerCell	for DW_FEATURE2D_DETECTOR_TYPE_STD only Number of features to be appended after high frequency points, they have second highest scores but are less than detectorDetailThreshold. During detection, the input image will be splitted into cellSize x cellSize small tiles, there'll be at most numEvenDistributionPerCell second-highest-score features in each cell. Larger numEvenDistributionPerCell will output an evener distributed feature map Smaller numEvenDistributionPerCell will have more features in high frequence points (score >= detectorDetailThreshold) and a less evener distributed feature map. Invalid if = 0, in that case, only detectorDetailThreshold takes effect.
dwProcessorType	processorType	for DW_FEATURE2D_DETECTOR_TYPE_STD only set to DW_PROCESSOR_TYPE_PVA_0 or DW_PROCESSOR_TYPE_PVA_1 to call PVA harris detector.
float32_t	scoreThreshold	Threshold to filter out low latency points. All points whose scores are less than detectorScoreThreshold will be considered as a non-feature point. Lower value will output more features, higher value will only keep the high frequency points. If set to zero the default value will be used.
dwFeature2DDetectorType	type	Detecting algorithm defined by `dwFeature2DDetectorType`
bool	useHalf	for DW_FEATURE2D_DETECTOR_TYPE_EX only use half-precision floating point to calculate harris corner score
bool	useNewToOldMapFromPreTracked	Determines whether the detector uses `dwFeatureArray::newToOldMap` directly from input `preTrackedFeatures` in `dwFeature2DDetector_detectFromImage` and `dwFeature2DDetector_detectFromPyramid`. If set to true, the output `outputDetections::newToOldMap` represents the mapping of output detections to frame(N-1) tracking If set to false, the output `outputDetections::newToOldMap` represents the mapping of output detections to frame(N) tracking Default is true.

Typedef Documentation

◆ dwConstFeature2DDetectorHandle_t

typedef struct dwFeature2DDetectorObject const* dwConstFeature2DDetectorHandle_t

Handle representing a const feature detector.

Definition at line 66 of file FeatureDetector.h.

◆ dwFeature2DDetectorHandle_t

typedef struct dwFeature2DDetectorObject* dwFeature2DDetectorHandle_t

Handle representing a feature detector.

Definition at line 63 of file FeatureDetector.h.

Enumeration Type Documentation

◆ dwFeature2DDetectorType

enum dwFeature2DDetectorType

Defines different KLT tracking algorithms.

Enumerator
DW_FEATURE2D_DETECTOR_TYPE_STD	Standard Harris Corner detector with fixed parameters, quicker.
DW_FEATURE2D_DETECTOR_TYPE_EX	Extended Harris Corner detector with more configurable parameters, more flexible, better quality but slower.
DW_FEATURE2D_DETECTOR_TYPE_FAST9	Fast corner detector, quicker. This algorithm was introduced by Edward Rosten and Tom Drummond in their paper "Machine learning for high-speed corner detection" in 2006
DW_FEATURE2D_DETECTOR_TYPE_COUNT

Definition at line 71 of file FeatureDetector.h.

◆ dwFeature2DSelectionMaskType

enum dwFeature2DSelectionMaskType

Feature distribution mask for extended detector.

Enumerator
DW_FEATURE2D_SELECTION_MASK_TYPE_UNIFORM	output feature in uniform distribution
DW_FEATURE2D_SELECTION_MASK_TYPE_GAUSSIAN	output feature in 2D gaussian distribution which has more features in center area and less ones in boundary
DW_FEATURE2D_SELECTION_MASK_TYPE_COUNT

Definition at line 87 of file FeatureDetector.h.

Function Documentation

◆ dwFeature2DDetector_detectFromImage()

DW_API_PUBLIC dwStatus dwFeature2DDetector_detectFromImage	(	dwFeatureArray *	outputDetections,
		dwImageHandle_t	image,
		dwFeatureArray *	preTrackedFeatures,
		const float32_t *	d_normalizedCrossCorrelation,
		dwFeature2DDetectorHandle_t	obj
	)

Detects new features and append them after old tracked features.

Features are added only in areas where the mask == 0xff means valid area, any pixel whose mask value != 0xff will be ignored during tracking.

Parameters

[out]	outputDetections	Detected features, composed of old tracked features and new detections, new detections are appended after old features. Must be created by `dwFeatureArray_createNew()` with DW_PROCESSOR_TYPE_GPU flag and the same maxFeatureCount when initializing detector
[in]	image	Specifies the image on which feature detection takes place, must be a CUDA image.
[in,out]	preTrackedFeatures	Previous tracked features, if detector type is `DW_FEATURE2D_DETECTOR_TYPE_EX`, some of old features will be marked as `DW_FEATURE2D_STATUS_INVALID` during detection. The `dwFeatureArray` can either be an empty array allocated by `dwFeatureArray_createNew` or a slice from feature history by `dwFeatureHistoryArray_getXXX`
[in]	d_normalizedCrossCorrelation	GPU pointer to nccScores of each feature, will be ignored if it's NULL. If the feature detector is connected to a tracker, d_normalizedCrossCorrelation can be filled by `dwFeature2DTracker_trackFeatures`.
[in]	obj	Specifies the feature detector handle.

Returns: DW_INVALID_ARGUMENT if detector handle, preTrackedFeatures or image are NULL.
DW_INVALID_ARGUMENT if preTrackedFeatures are not allocated on GPU.
DW_INVALID_HANDLE if image is not a CUDA image.
DW_SUCCESS otherwise.

Note: If there're N features in preTrackedFeatures, for DW_FEATURE2D_DETECTOR_TYPE_STD, the first N features in detectedFeatures are from preTrackedFeaturs, new detections are appended after old ones. for DW_FEATURE2D_DETECTOR_TYPE_EX, the first M(M <= N) features in detectedFeatures are from preTrackedFeaturs new detections are appended after old ones. The reason that M <= N is that some features in preTrackedFeatures will be marked as invalid to meet the restriction of uniform/gaussian distribution.

◆ dwFeature2DDetector_detectFromPyramid()

DW_API_PUBLIC dwStatus dwFeature2DDetector_detectFromPyramid	(	dwFeatureArray *	outputDetections,
		const dwPyramidImage *	pyramid,
		dwFeatureArray *	preTrackedFeatures,
		const float32_t *	d_normalizedCrossCorrelation,
		dwFeature2DDetectorHandle_t	obj
	)

Detects new features and append them after old tracked features.

Features are added only in areas where the mask == 0xff means valid area, any pixel whose mask value != 0xff will be ignored during tracking.

Parameters

[out]	outputDetections	Detected features, composed of old tracked features and new detections, new detections are appended after old features. Must be created by `dwFeatureArray_createNew()` with DW_PROCESSOR_TYPE_GPU flag and the same maxFeatureCount when initializing detector
[in]	pyramid	Specifies the pyramid on which feature detection takes place.
[in,out]	preTrackedFeatures	Previous tracked features, if detector type is `DW_FEATURE2D_DETECTOR_TYPE_EX`, some of old features will be marked as `DW_FEATURE2D_STATUS_INVALID` during detection. The `dwFeatureArray` can either be an empty array allocated by `dwFeatureArray_createNew` or a slice from feature history by `dwFeatureHistoryArray_getXXX` *
[in]	d_normalizedCrossCorrelation	GPU pointer to nccScores of each feature, will be ignored if it's NULL. If the feature detector is connected to a tracker, d_normalizedCrossCorrelation can be filled by `dwFeature2DTracker_trackFeatures`.
[in]	obj	Specifies the feature detector handle.

Returns: DW_INVALID_ARGUMENT if detector handle, preTrackedFeatures or image are NULL.
DW_INVALID_ARGUMENT if preTrackedFeatures are not allocated on GPU.
DW_SUCCESS otherwise.

Note: If there're N features in preTrackedFeatures, for DW_FEATURE2D_DETECTOR_TYPE_STD, the first N features in detectedFeatures are from preTrackedFeaturs, new detections are appended after old ones. for DW_FEATURE2D_DETECTOR_TYPE_EX, the first M(M <= N) features in detectedFeatures are from preTrackedFeaturs new detections are appended after old ones. The reason that M <= N is that some features in preTrackedFeatures will be marked as invalid to meet the restriction of uniform/gaussian distribution.

◆ dwFeature2DDetector_getCUDAStream()

DW_API_PUBLIC dwStatus dwFeature2DDetector_getCUDAStream	(	cudaStream_t *	stream,
		dwFeature2DDetectorHandle_t	obj
	)

Gets the CUDA stream used by the feature Detector.

Parameters

[out]	stream	The CUDA stream currently used.
[in]	obj	A handle to the feature Detector module.

Returns: DW_INVALID_ARGUMENT if feature Detector handle or stream are NULL.
DW_SUCCESS otherwise.

◆ dwFeature2DDetector_getPVAStream()

DW_API_PUBLIC dwStatus dwFeature2DDetector_getPVAStream	(	cupvaStream_t *	stream,
		dwFeature2DDetectorHandle_t	obj
	)

Gets the CUPVA stream used by the feature Detector.

Parameters

[out]	stream	The CUPVA stream currently used.
[in]	obj	A handle to the feature Detector module.

Returns: DW_INVALID_ARGUMENT if feature Detector handle or stream are NULL.
DW_SUCCESS otherwise.

◆ dwFeature2DDetector_getValidTrackedCount()

DW_API_PUBLIC dwStatus dwFeature2DDetector_getValidTrackedCount	(	const uint32_t **	d_validTrackedCount,
		dwFeature2DDetectorHandle_t	obj
	)

dwFeature2DDetector_getValidTrackedCount

Parameters

d_validTrackedCount
obj

Returns

◆ dwFeature2DDetector_initDefaultParams()

DW_API_PUBLIC dwStatus dwFeature2DDetector_initDefaultParams ( dwFeature2DDetectorConfig * params )

Initializes dwFeature2DDetector parameters with default values.

Parameters

[in,out] params dwFeature2DDetector parameters; user can optionally set imageWidth/imageHeight before the API call to obtain the default parameters for the resolution

Returns: DW_INVALID_ARGUMENT if params is NULL.
DW_SUCCESS otherwise.

◆ dwFeature2DDetector_initDefaultParamsForCamera()

DW_API_PUBLIC dwStatus dwFeature2DDetector_initDefaultParamsForCamera	(	dwFeature2DDetectorConfig *	params,
		const dwTransformation3f *	cameraToRig,
		dwConstCameraModelHandle_t	cameraHandle
	)

Initializes dwFeature2DDetector parameters with values best suited for the given camera using camera extrinsic (dwTransformation3f* cameraToRig) and camera intrinsic (dwConstCameraModelHandle_t cameraHandle)

Parameters

[out]	params	dwFeature2DDetector parameters
[in]	cameraToRig	transformed camera extrinsic parameters with respect to rig
[in]	cameraHandle	holds camera intrinsic information

Returns: DW_INVALID_ARGUMENT if any parameter is NULL.
DW_SUCCESS otherwise.

◆ dwFeature2DDetector_initialize()

DW_API_PUBLIC dwStatus dwFeature2DDetector_initialize	(	dwFeature2DDetectorHandle_t *	obj,
		const dwFeature2DDetectorConfig *	config,
		cudaStream_t	cudaStream,
		dwContextHandle_t	context
	)

Creates and initializes a feature Detector.

Parameters

[out]	obj	A pointer to the feature Detector handle is returned here.
[in]	config	Specifies the configuration parameters.
[in]	cudaStream	Specifies the CUDA stream to use for Detector operations.
[in]	context	Specifies the handle to the context under which it is created.

Returns: DW_INVALID_ARGUMENT if feature Detector handle or context are NULL or config is invalid.
DW_SUCCESS otherwise.

◆ dwFeature2DDetector_release()

DW_API_PUBLIC dwStatus dwFeature2DDetector_release ( dwFeature2DDetectorHandle_t obj )

Releases the feature Detector.

This method releases all resources associated with a feature Detector.

Note: This method renders the handle unusable.

Parameters

[in] obj The feature detector handle to be released.

Returns: DW_INVALID_ARGUMENT if feature Detector handle is NULL.
DW_SUCCESS otherwise.

◆ dwFeature2DDetector_reset()

DW_API_PUBLIC dwStatus dwFeature2DDetector_reset ( dwFeature2DDetectorHandle_t obj )

Resets a feature Detector.

Parameters

[in] obj Specifies the feature Detector handle to be reset.

Returns: DW_INVALID_ARGUMENT if feature Detector handle is NULL.
DW_SUCCESS otherwise.

◆ dwFeature2DDetector_setCUDAStream()

DW_API_PUBLIC dwStatus dwFeature2DDetector_setCUDAStream	(	cudaStream_t	stream,
		dwFeature2DDetectorHandle_t	obj
	)

Sets the CUDA stream for CUDA related operations.

Note: The ownership of the stream remains by the callee.

Parameters

[in]	stream	The CUDA stream to be used. Default is the one passed during dwFeature2DDetector_initialize.
[in]	obj	A handle to the feature Detector module to set CUDA stream for.

Returns: DW_INVALID_ARGUMENT if feature Detector handle is NULL.
DW_SUCCESS otherwise.

◆ dwFeature2DDetector_setMask()

DW_API_PUBLIC dwStatus dwFeature2DDetector_setMask	(	const uint8_t *	d_mask,
		const uint32_t	maskStrideBytes,
		const uint32_t	maskWidth,
		const uint32_t	maskHeight,
		dwFeature2DDetectorHandle_t	obj
	)

Sets a mask to ignore areas of the image.

Areas where mask != 0xff will not produce new features when detectNewFeatures() is called. The size of the mask must be the same as the image.

Note: If this function is called after dwFeature2DDetector_initialize(), it must be called with the same input parameters after dwFeature2DDetector_reset because reset() function will clear the existing mask.

Parameters

[in]	d_mask	A GPU pointer to the mask data. The data is copied.
[in]	maskStrideBytes	Specifies the stride, in bytes, for each row of the mask.
[in]	maskWidth	Specifies the width of the mask.
[in]	maskHeight	Specifies the height of the mask.
[in]	obj	Specifies the feature detector handle.

Returns: DW_INVALID_ARGUMENT if feature Detector handle or d_mask are NULL or maskWidth or maskHeight are invalid.
DW_SUCCESS otherwise.

◆ dwFeature2DDetector_setPVAStream()

DW_API_PUBLIC dwStatus dwFeature2DDetector_setPVAStream	(	cupvaStream_t	stream,
		dwFeature2DDetectorHandle_t	obj
	)

Sets the CUPVA stream for PVA related operations.

Note: The ownership of the stream remains by the callee.

Parameters

[in]	stream	The CUPVA stream to be used. Default is the one passed during dwFeature2DDetector_initialize.
[in]	obj	A handle to the feature Detector module to set CUPVA stream for.

Returns: DW_INVALID_ARGUMENT if feature Detector handle is NULL.
DW_SUCCESS otherwise.

Variable Documentation

◆ DW_FEATURES2D_DETECTOR_MAX_CELL_SIZE

const uint32_t DW_FEATURES2D_DETECTOR_MAX_CELL_SIZE = 128

Definition at line 249 of file FeatureDetector.h.

Detailed Description

Data Structures

Typedefs

Enumerations

Functions

Variables

Data Structure Documentation

◆ dwFeature2DDetectorConfig

Typedef Documentation

◆ dwConstFeature2DDetectorHandle_t

◆ dwFeature2DDetectorHandle_t

Enumeration Type Documentation

◆ dwFeature2DDetectorType

◆ dwFeature2DSelectionMaskType

Function Documentation

◆ dwFeature2DDetector_detectFromImage()

◆ dwFeature2DDetector_detectFromPyramid()

◆ dwFeature2DDetector_getCUDAStream()

◆ dwFeature2DDetector_getPVAStream()

◆ dwFeature2DDetector_getValidTrackedCount()

◆ dwFeature2DDetector_initDefaultParams()

◆ dwFeature2DDetector_initDefaultParamsForCamera()

◆ dwFeature2DDetector_initialize()

◆ dwFeature2DDetector_release()

◆ dwFeature2DDetector_reset()

◆ dwFeature2DDetector_setCUDAStream()

◆ dwFeature2DDetector_setMask()

◆ dwFeature2DDetector_setPVAStream()

Variable Documentation

◆ DW_FEATURES2D_DETECTOR_MAX_CELL_SIZE