ImageFeatureTrack

ImageFeatureTrack[{image1,image2,…,imagen}]

tracks features from image1 through imagen.

ImageFeatureTrack[{image1,image2,…,imagen},pts]

tracks features starting from the initial set of points pts in image1.

Details and Options

  • ImageFeatureTrack tracks feature points in a sequence of images.
  • ImageFeatureTrack works with an AnimatedImage or a sequence of images of the same dimensions.
  • ImageFeatureTrack[{image1,image2,…,imagen}] automatically determines a set of feature points in the images to track, and returns a list {pts1,pts2,…,ptsn}, where ptsi is the position of the features in imagei.
  • ImageFeatureTrack assumes the standard image coordinate system, where x runs from 0 to width and y runs from 0 to height. Position {0,0} corresponds to the bottom-left corner of the image.
  • If a point is not found in some imagei, the coordinates are returned as Missing[].
  • The following options can be specified:
  • Masking Allregion of interest
    MaxFeatureDisplacement15maximum distance between corresponding points in adjacent images
    MaxFeatures 100maximum number of tracked points
    MaxIterations20maximum number of iterations
    Tolerance0.03tolerance for matching points
  • With the setting MaxFeatureDisplacement->{r1,r2}, different search window ranges can be specified for vertical and horizontal directions.
  • With Masking->roi, the set of points is restricted so that the returned points pts1 of image1 all lie within the region of interest roi.
  • The tracking between subsequent images is computed by an iterative algorithm. With MaxIterations->n and Tolerance->tol, the algorithm terminates when the iterative displacement is less than tol or the number of iterations exceeds n.

Examples

open allclose all

Basic Examples  (1)

Track specified points from one image to another:

Scope  (2)

Automatically find the initial set of points to track:

Visualize tracked points:

Options  (2)

Masking  (1)

Track only the points that are inside of the specified mask:

MaxFeatures  (1)

Specify a maximum number of points to be tracked:

Applications  (2)

Show the optical flow of points in two images:

Track the image corners between images:

Interactive Examples  (1)

Track points in a sequence of images:

Plot the motion of each tracked feature:

Neat Examples  (1)

Tracking particles:

Wolfram Research (2012), ImageFeatureTrack, Wolfram Language function, https://reference.wolfram.com/language/ref/ImageFeatureTrack.html (updated 2022).

Text

Wolfram Research (2012), ImageFeatureTrack, Wolfram Language function, https://reference.wolfram.com/language/ref/ImageFeatureTrack.html (updated 2022).

CMS

Wolfram Language. 2012. "ImageFeatureTrack." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2022. https://reference.wolfram.com/language/ref/ImageFeatureTrack.html.

APA

Wolfram Language. (2012). ImageFeatureTrack. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/ImageFeatureTrack.html

BibTeX

@misc{reference.wolfram_2024_imagefeaturetrack, author="Wolfram Research", title="{ImageFeatureTrack}", year="2022", howpublished="\url{https://reference.wolfram.com/language/ref/ImageFeatureTrack.html}", note=[Accessed: 18-December-2024 ]}

BibLaTeX

@online{reference.wolfram_2024_imagefeaturetrack, organization={Wolfram Research}, title={ImageFeatureTrack}, year={2022}, url={https://reference.wolfram.com/language/ref/ImageFeatureTrack.html}, note=[Accessed: 18-December-2024 ]}