lucas_kanade.h File Reference

efficient fixed-point optical-flow calculation More...

#include "std.h"
#include "image.h"

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Macros
#define	LARGE_FLOW_ERROR   1E5
#define	MEDIUM_FLOW_ERROR   1E3

Functions
struct flow_t *	opticFlowLK (struct image_t *new_img, struct image_t *old_img, struct point_t *points, uint16_t *points_cnt, uint16_t half_window_size, uint16_t subpixel_factor, uint8_t max_iterations, uint8_t step_threshold, uint8_t max_points, uint8_t pyramid_level, uint8_t keep_bad_points)
struct flow_t *	opticFlowLK_flat (struct image_t *new_img, struct image_t *old_img, struct point_t *points, uint16_t *points_cnt, uint16_t half_window_size, uint16_t subpixel_factor, uint8_t max_iterations, uint8_t step_threshold, uint16_t max_points, uint8_t keep_bad_points)
	Compute the optical flow of several points using the Lucas-Kanade algorithm by Yves Bouguet The initial fixed-point implementation is doen by G. More...

Detailed Description

efficient fixed-point optical-flow calculation

• Initial fixed-point C implementation by G. de Croon
• Algorithm: Lucas-Kanade by Yves Bouguet
• Publication: http://robots.stanford.edu/cs223b04/algo_tracking.pdf

Definition in file lucas_kanade.h.

Macro Definition Documentation

LARGE_FLOW_ERROR

#define LARGE_FLOW_ERROR   1E5

Definition at line 37 of file lucas_kanade.h.

MEDIUM_FLOW_ERROR

#define MEDIUM_FLOW_ERROR   1E3

Definition at line 38 of file lucas_kanade.h.

Function Documentation

opticFlowLK()

struct flow_t* opticFlowLK	(	struct image_t *	new_img,
		struct image_t *	old_img,
		struct point_t *	points,
		uint16_t *	points_cnt,
		uint16_t	half_window_size,
		uint16_t	subpixel_factor,
		uint8_t	max_iterations,
		uint8_t	step_threshold,
		uint8_t	max_points,
		uint8_t	pyramid_level,
		uint8_t	keep_bad_points
	)

Definition at line 74 of file lucas_kanade.c.

References flow_t::error, flow_t::flow_x, flow_t::flow_y, image_t::h, image_calculate_g(), image_create(), image_difference(), image_free(), IMAGE_GRADIENT, image_gradients(), IMAGE_GRAYSCALE, image_multiply(), image_subpixel_window(), LARGE_FLOW_ERROR, opticFlowLK_flat(), p, patch_size, flow_t::pos, pyramid_build(), image_t::w, point_t::x, and point_t::y.

Referenced by calc_fast9_lukas_kanade().

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opticFlowLK_flat()

struct flow_t* opticFlowLK_flat	(	struct image_t *	new_img,
		struct image_t *	old_img,
		struct point_t *	points,
		uint16_t *	points_cnt,
		uint16_t	half_window_size,
		uint16_t	subpixel_factor,
		uint8_t	max_iterations,
		uint8_t	step_threshold,
		uint16_t	max_points,
		uint8_t	keep_bad_points
	)

Compute the optical flow of several points using the Lucas-Kanade algorithm by Yves Bouguet The initial fixed-point implementation is doen by G.

de Croon and is adapted by Freek van Tienen for the implementation in Paparazzi.

Parameters

[in]	*new_img	The newest grayscale image (TODO: fix YUV422 support)
[in]	*old_img	The old grayscale image (TODO: fix YUV422 support)
[in]	*points	Points to start tracking from
	[in/out]	points_cnt The amount of points and it returns the amount of points tracked
[in]	half_window_size	Half the window size (in both x and y direction) to search inside
[in]	subpixel_factor	The subpixel factor which calculations should be based on
[in]	max_iteration	Maximum amount of iterations to find the new point
[in]	step_threshold	The threshold at which the iterations should stop
[in]	max_point	The maximum amount of points to track, we skip x points and then take a point.

Returns

The vectors from the original *points in subpixels

Definition at line 275 of file lucas_kanade.c.

References flow_t::error, FALSE, flow_t::flow_x, flow_t::flow_y, image_t::h, image_calculate_g(), image_create(), image_difference(), image_free(), IMAGE_GRADIENT, image_gradients(), IMAGE_GRAYSCALE, image_multiply(), image_subpixel_window(), LARGE_FLOW_ERROR, p, patch_size, flow_t::pos, TRUE, image_t::w, point_t::x, and point_t::y.

Referenced by opticFlowLK().

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