Shape-Based Mutual Segmentation |
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Authors: | Tammy Riklin-Raviv Nir Sochen Nahum Kiryati |
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Affiliation: | (1) School of Electrical Engineering, Tel Aviv University, Tel Aviv, 69978, Israel;(2) Department of Applied Mathematics, Tel Aviv University, Tel Aviv, 69978, Israel |
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Abstract: | We present a novel variational approach for simultaneous segmentation of two images of the same object taken from different viewpoints. Due to noise, clutter and occlusions, neither of the images contains
sufficient information for correct object-background partitioning. The evolving object contour in each image provides a dynamic
prior for the segmentation of the other object view. We call this process mutual segmentation. The foundation of the proposed method is a unified level-set framework for region and edge based segmentation, associated
with a shape similarity term. The suggested shape term incorporates the semantic knowledge gained in the segmentation process
of the image pair, accounting for excess or deficient parts in the estimated object shape. Transformations, including planar
projectivities, between the object views are accommodated by a registration process held concurrently with the segmentation.
The proposed segmentation algorithm is demonstrated on a variety of image pairs. The homography between each of the image
pairs is estimated and its accuracy is evaluated. |
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Keywords: | Mutual segmentation Level sets Shape Perspective transformation Planar projective homography |
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