Struct FeatureTrackerConfig::CornerDetector

Nested Relationships

This struct is a nested type of Class FeatureTrackerConfig.

Nested Types

Struct Documentation

struct CornerDetector

Corner detector configuration structure.

Public Types

enum class Type : std::int32_t

Values:

enumerator HARRIS

Harris corner detector.

enumerator SHI_THOMASI

Shi-Thomasi corner detector.

Public Functions

DEPTHAI_SERIALIZE(CornerDetector, type, cellGridDimension, numTargetFeatures, numMaxFeatures, thresholds, enableSobel, enableSorting)

Public Members

Type type = Type::HARRIS

Corner detector algorithm type.

std::int32_t cellGridDimension = 4

Ensures distributed feature detection across the image. Image is divided into horizontal and vertical cells, each cell has a target feature count = numTargetFeatures / cellGridDimension. Each cell has its own feature threshold. A value of 4 means that the image is divided into 4x4 cells of equal width/height. Maximum 4, minimum 1.

std::int32_t numTargetFeatures = 320

Target number of features to detect. Maximum number of features is determined at runtime based on algorithm type.

std::int32_t numMaxFeatures = AUTO

Hard limit for the maximum number of features that can be detected. 0 means auto, will be set to the maximum value based on memory constraints.

bool enableSobel = true

Enable 3x3 Sobel operator to smoothen the image whose gradient is to be computed. If disabled, a simple 1D row/column differentiator is used for gradient.

bool enableSorting = true

Enable sorting detected features based on their score or not.

Thresholds thresholds

Threshold settings. These are advanced settings, suitable for debugging/special cases.

struct Thresholds

Threshold settings structure for corner detector.

Public Functions

DEPTHAI_SERIALIZE(Thresholds, initialValue, min, max, decreaseFactor, increaseFactor)

Public Members

float initialValue = AUTO

Minimum strength of a feature which will be detected. 0 means automatic threshold update. Recommended so the tracker can adapt to different scenes/textures. Each cell has its own threshold. Empirical value.

float min = AUTO

Minimum limit for threshold. Applicable when automatic threshold update is enabled. 0 means auto, 6000000 for HARRIS, 1200 for SHI_THOMASI. Empirical value.

float max = AUTO

Maximum limit for threshold. Applicable when automatic threshold update is enabled. 0 means auto. Empirical value.

float decreaseFactor = 0.9f

When detected number of features exceeds the maximum in a cell threshold is lowered by multiplying its value with this factor.

float increaseFactor = 1.1f

When detected number of features doesn’t exceed the maximum in a cell, threshold is increased by multiplying its value with this factor.