Wolfram Language

Image and Signal Processing

Detect Rotating Objects

ImageDisplacements can capture dynamic features in video sequences. From one video frame to the next, ImageDisplacements provides a vector field that describes the optical flow that is essentially the 2D motion field of objects in the video.

Vector field analysis provides a variety of tools to analyze these motion fields. This example focuses on the curl to detect rotating objects.

A video sequence of rotating wind turbines.

In[1]:=
Click for copyable input
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In[2]:=
Click for copyable input
ListAnimate[seq]
Play Animation
Stop Animation

Obtain the average optical flow of the entire video sequence.

In[3]:=
Click for copyable input
flow = Mean@ImageDisplacements[Append[seq, First[seq]]];
In[4]:=
Click for copyable input
Show[ First[seq], ListVectorPlot[Transpose@Reverse@flow, VectorStyle -> Yellow, VectorPoints -> Fine] ]
Out[4]=

The curl of a vector field determines the amount of inherent rotation.

In[5]:=
Click for copyable input
listCurl = flow \[Function] ListConvolve[{{0.5`, 0, -0.5`}}, flow[[All, All, 2]], {{1, 2}, {1, 2}}, "Fixed"] - ListConvolve[{{-0.5`}, {0.`}, {0.5`}}, flow[[All, All, 1]], {{1, 2}, {1, 2}}, "Fixed"];
In[6]:=
Click for copyable input
curl = ImageAdjust@Image@(listCurl@flow)
Out[6]=

A blurred curl distribution provides a more robust result for large-scale rotations. Black stands for negative rotation; white denotes rotation with positive orientation.

In[7]:=
Click for copyable input
blurredCurl = ImageAdjust[GaussianFilter[curl, 8 {3, 1}]]
Out[7]=

Colorize the rotation map and superimpose it on top of the original image.

In[8]:=
Click for copyable input
ImageCompose[seq[[1]], SetAlphaChannel[ Colorize[blurredCurl, ColorFunction -> ColorData[{"TemperatureMap", "Reverse"}]], ColorNegate[blurredCurl]]]
Out[8]=

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