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Title |
Moving Object Segmentation Method Based on Motion Information Classification by X-means and Spatial Region Segmentation |
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Author |
Kousuke Imamura |
| Citation |
Vol. 13 No. 11 pp. 1-7 |
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Abstract |
We here in propose a moving object segmentation method based on motion information classification by x-means clustering and region segmentation. In the proposed method, a current frame is first segmented by a morphological watershed algorithm. Affine motion information obtaining from three frames at the feature points is classified by x-means clustering. Whether a feature point corresponds to an uncovered background region or an occlusion is then estimated based on the temporal correlation of the clustering results, and incorrect classified feature point is excluded. Finally, a label is assigned to the segmented region based on the clustering results of motion information. The labeled region represents the moving object segmentation results of the proposed method. The experimental results reveal that the proposed method provides good moving object segmentation for a suitable number of objects. |
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Keywords |
Moving object segmentation, X-means clustering, Morphological watershed algorithm |
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URL |
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Title |
Moving Object Segmentation Method Based on Motion Information Classification by X-means and Spatial Region Segmentation |
|
Author |
Kousuke Imamura |
| Citation |
Vol. 13 No. 11 pp. 1-7 |
|
Abstract |
We here in propose a moving object segmentation method based on motion information classification by x-means clustering and region segmentation. In the proposed method, a current frame is first segmented by a morphological watershed algorithm. Affine motion information obtaining from three frames at the feature points is classified by x-means clustering. Whether a feature point corresponds to an uncovered background region or an occlusion is then estimated based on the temporal correlation of the clustering results, and incorrect classified feature point is excluded. Finally, a label is assigned to the segmented region based on the clustering results of motion information. The labeled region represents the moving object segmentation results of the proposed method. The experimental results reveal that the proposed method provides good moving object segmentation for a suitable number of objects. |
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Keywords |
Moving object segmentation, X-means clustering, Morphological watershed algorithm |
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URL |
