Détectez les objets en rotation
ImageDisplacements peut capturer les caractéristiques dynamiques dans les séquences vidéo. D'une image vidéo à l'autre, ImageDisplacements fournit un champ vectoriel décrivant le flux optique qui correspond essentiellement au champ de mouvement d'objets en 2D dans la vidéo.
L'analyse du champ vectoriel fournit une variété d'outils pour analyser ces champs de mouvement. Cet exemple montre la courbe pour détecter les objets en rotation.
Une séquence vidéo consistant à faire tourner les éoliennes.
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"], {{0, 256}, {256, 0}}, {0, 255},
ColorFunction->RGBColor],
BoxForm`ImageTag["Byte", ColorSpace -> "RGB", Interleaving -> True],
Selectable->False],
DefaultBaseStyle->"ImageGraphics",
ImageSizeRaw->{256, 256},
PlotRange->{{0, 256}, {0, 256}}]\), ...};
ListAnimate[seq]
Obtenez le flux optique moyen de la séquence vidéo entière.
flow = Mean@ImageDisplacements[Append[seq, First[seq]]];
Show[
First[seq],
ListVectorPlot[Transpose@Reverse@flow, VectorStyle -> Yellow,
VectorPoints -> Fine]
]
La boucle d'un champ vectoriel détermine la quantité de rotation inhérente.
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"];
curl = ImageAdjust@Image@(listCurl@flow)
Une distribution de courbure floue donne un résultat plus robuste pour les rotations à grande échelle. Le noir correspond à une rotation négative, le blanc à une rotation d'orientation positive.
blurredCurl = ImageAdjust[GaussianFilter[curl, 8 {3, 1}]]
Coloriez le plan de rotation et superposez-le sur l'image originale.
ImageCompose[seq[[1]],
SetAlphaChannel[
Colorize[blurredCurl,
ColorFunction -> ColorData[{"TemperatureMap", "Reverse"}]],
ColorNegate[blurredCurl]]]