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

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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: 21-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: 21-December-2024 ]}