Crate optical_flow_lk 

High-performance computer vision algorithms for real-time applications

Provides implementations of:

• Lucas-Kanade optical flow
• Shi-Tomasi feature detection
• Optimized image processing pipelines

Designed to be compatible with WebAssembly (Wasm).

Structs

TrackResult

Per-point result of calc_optical_flow_ex.

TrackerContext

Reusable owner of every buffer the tracking hot path touches: both frame pyramids, the Lucas-Kanade scratch, the result vector and the forward-backward intermediates.

Enums

TrackStatus

Why a feature point ended up where it did after tracking.

Constants

DEFAULT_FB_THRESHOLD

Default forward-backward round-trip threshold (pixels) for calc_optical_flow_fb.

DEFAULT_MIN_EIGEN_THRESHOLD

Default minimum-eigenvalue threshold used by calc_optical_flow.

Functions

build_pyramid

Builds a pyramid of images where each successive layer is half as large in width and height

build_pyramid_into

Builds the pyramid into an existing buffer, reusing each level’s storage when its dimensions are unchanged.

calc_optical_flowDeprecated

Compute optical flow using the pyramidal Lucas-Kanade method.

calc_optical_flow_ex

Compute optical flow using the pyramidal Lucas-Kanade method, returning a per-point TrackResult with status and photometric error.

calc_optical_flow_fb

Track points prev->next, then re-track the results next->prev, and flag any point whose round-trip lands further than fb_threshold pixels from where it started as TrackStatus::FbInconsistent.

good_features_to_track

Finds good features points using the Shi-Tomasi algorithm

good_features_to_track_grid

Finds good feature points with uniform frame coverage by detecting per grid cell, while respecting features that are already being tracked.