Struct FeatureTrackerConfig::MotionEstimator

Nested Relationships

This struct is a nested type of Class FeatureTrackerConfig.

Nested Types

Struct Documentation

struct MotionEstimator

Used for feature reidentification between current and previous features.

Public Types

enum class Type : std::int32_t

Values:

enumerator LUCAS_KANADE_OPTICAL_FLOW

Using the pyramidal Lucas-Kanade optical flow method.

enumerator HW_MOTION_ESTIMATION

Using a dense motion estimation hardware block (Block matcher).

Public Functions

DEPTHAI_SERIALIZE(MotionEstimator, enable, type, opticalFlow)

Public Members

bool enable = true

Enable motion estimation or not.

Type type = Type::LUCAS_KANADE_OPTICAL_FLOW

Motion estimator algorithm type.

OpticalFlow opticalFlow

Optical flow configuration. Takes effect only if MotionEstimator algorithm type set to LUCAS_KANADE_OPTICAL_FLOW.

struct OpticalFlow

Optical flow configuration structure.

Public Functions

DEPTHAI_SERIALIZE(OpticalFlow, pyramidLevels, searchWindowWidth, searchWindowHeight, epsilon, maxIterations)

Public Members

std::int32_t pyramidLevels = AUTO

Number of pyramid levels, only for optical flow. AUTO means it’s decided based on input resolution: 3 if image width <= 640, else 4. Valid values are either 3/4 for VGA, 4 for 720p and above.

std::int32_t searchWindowWidth = 5

Image patch width used to track features. Must be an odd number, maximum 9. N means the algorithm will be able to track motion at most (N-1)/2 pixels in a direction per pyramid level. Increasing this number increases runtime

std::int32_t searchWindowHeight = 5

Image patch height used to track features. Must be an odd number, maximum 9. N means the algorithm will be able to track motion at most (N-1)/2 pixels in a direction per pyramid level. Increasing this number increases runtime

float epsilon = 0.01f

Feature tracking termination criteria. Optical flow will refine the feature position on each pyramid level until the displacement between two refinements is smaller than this value. Decreasing this number increases runtime.

std::int32_t maxIterations = 9

Feature tracking termination criteria. Optical flow will refine the feature position maximum this many times on each pyramid level. If the Epsilon criteria described in the previous chapter is not met after this number of iterations, the algorithm will continue with the current calculated value. Increasing this number increases runtime.