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

tracks features from image1 through imagen.

ImageFeatureTrack[video]

tracks features in frames of video.

ImageFeatureTrack[input,pts]

tracks features starting from the initial set of points pts in the first image or video frame.

Details and Options
Details and Options Details and Options
Examples  
Basic Examples  
Scope  
Options  
Masking  
MaxFeatures  
Applications  
Interactive Examples  
Neat Examples  
See Also
Related Guides
History
Cite this Page

ImageFeatureTrack

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

tracks features from image1 through imagen.

ImageFeatureTrack[video]

tracks features in frames of video.

ImageFeatureTrack[input,pts]

tracks features starting from the initial set of points pts in the first image or video frame.

Details and Options

  • ImageFeatureTrack, also known as feature tracking, tracks feature points over time.
  • ImageFeatureTrack works with a Video object, an AnimatedImage object or a sequence of images.
  • ImageFeatureTrack[input] automatically determines a set of feature points in the first image or first video frame to track.
  • When tracking points in an image sequence or an AnimatedImage, a list {pts1,pts2,…,ptsn} is returned, where ptsi is the position of the features in imagei.
  • Coordinates {x,y} are assumed to be in the standard image coordinate system.
  • If a point is not found in some image or video frame, the coordinates are returned as Missing[] for all subsequent frames.
  • 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:

Wolfram Language code: ImageFeatureTrack[{[image], [image]}, {{141, 86}, {98, 83}}]

Scope  (4)

Automatically find the initial set of points to track:

Wolfram Language code: ImageFeatureTrack[{[image], [image]}]

Visualize tracked points:

Wolfram Language code: images = {[image], [image]}; pts = ImageFeatureTrack[images, MaxFeatures -> 15]; MapThread[HighlightImage, {images, pts}]

Automatically track points in a video:

Wolfram Language code: pts = ImageFeatureTrack[v, MaxFeatures -> 15];
Wolfram Language code: HighlightImage[IconizedObject[«frame»], {RandomColor[Hue[_]], Line[DeleteMissing[#]]}& /@ Transpose[pts], {...}]

Track specified points in a video:

Wolfram Language code: v = \!\(\*VideoBox["![Embedded Video Player](video://content-68hlk)"]\);
Wolfram Language code: pts = ImageFeatureTrack[v, {{365, 85}, {295, 155}}];
Wolfram Language code: HighlightImage[IconizedObject[«frame»], {RandomColor[Hue[_]], Line[DeleteMissing[#]]}& /@ Transpose[pts], {...}]

Options  (2)

Masking  (1)

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

Wolfram Language code: images = {[image], [image]};mask = [image]; pts = ImageFeatureTrack[images, Masking -> mask, MaxFeatures -> 15]; MapThread[HighlightImage, {images, pts}]

MaxFeatures  (1)

By default, all tracked points of interest are returned:

Wolfram Language code: ImageFeatureTrack[{[image], [image]}]//Round//Transpose//Tabular

Specify a maximum number of points to be tracked:

Wolfram Language code: ImageFeatureTrack[{[image], [image]}, MaxFeatures -> 5]//Round//Transpose//Tabular

Applications  (3)

Show the optical flow of points in two images:

Wolfram Language code: pts = ImageFeatureTrack[{im1 = [image], im2 = [image]}, MaxFeatures -> 20]; Show[ImageAssemble[{im1, im2}], Graphics[{Green, PointSize[.02], MapThread[If[#2 === Missing[], {Cyan, Point[#1]}, Arrow[{#1, #2 + {ImageDimensions[im1][[1]], 0}}]]&, pts]}]]

Track the image corners between images:

Wolfram Language code: im1 = [image];im2 = [image]; corners = ImageCorners[im1, 5, Automatic, 15]
Wolfram Language code: ImageFeatureTrack[{im1, im2}, corners]

Track a point on the face of a woman dancing on the stage, to analyze the dance:

Wolfram Language code: video = \!\(\*VideoBox["![Embedded Video Player](video://content-x2tv8)"]\);
Wolfram Language code: points = ImageFeatureTrack[video, {{366, 231}}]; HighlightVideo[video, points]

The number of taps the performer makes can be computed from the coordinate of the tracked point:

Wolfram Language code: heights = points[[All, 1, 2]]; ListLinePlot[heights]

Find the peaks:

Wolfram Language code: peaks = FindPeaks[heights]; ListLinePlot[{heights, peaks}, IconizedObject[«opts»]]

Find the number of jumps/taps frequency from the number of peaks:

Wolfram Language code: Quantity[Length[peaks], "Steps"] / Duration[video]

Interactive Examples  (1)

Track points in a sequence of images:

Wolfram Language code: i = [image]; imgs = ImageRotate[i, # Degree, Full, Background -> 1]& /@ Range[0, 90, 5]; pts = ImageFeatureTrack[imgs, MaxFeatures -> 7]; ListAnimate[MapThread[HighlightImage, {imgs, pts}]]

Plot the motion of each tracked feature:

Wolfram Language code: ListLinePlot[Transpose@pts]

Neat Examples  (1)

Tracking particles:

Wolfram Language code: images = {[image], [image]}; {w, h} = ImageDimensions[images[[1]]]; res = ImageFeatureTrack[images, Flatten[Table[{x, y}, {x, .5, w - .5, 20}, {y, .5, h - .5, 20}], 1]];
Wolfram Language code: Graphics[{Red, If[FreeQ[#, _Missing], Arrow[{#}]]& /@ Transpose[res]}]
Wolfram Research (2012), ImageFeatureTrack, Wolfram Language function, https://reference.wolfram.com/language/ref/ImageFeatureTrack.html (updated 2025).

Text

Wolfram Research (2012), ImageFeatureTrack, Wolfram Language function, https://reference.wolfram.com/language/ref/ImageFeatureTrack.html (updated 2025).

CMS

Wolfram Language. 2012. "ImageFeatureTrack." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2025. 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_2026_imagefeaturetrack, author="Wolfram Research", title="{ImageFeatureTrack}", year="2025", howpublished="\url{https://reference.wolfram.com/language/ref/ImageFeatureTrack.html}", note=[Accessed: 05-October-2026]}

BibLaTeX

@online{reference.wolfram_2026_imagefeaturetrack, organization={Wolfram Research}, title={ImageFeatureTrack}, year={2025}, url={https://reference.wolfram.com/language/ref/ImageFeatureTrack.html}, note=[Accessed: 05-October-2026]}