In this paper we consider the problem of segmenting points in a collection of images that contain multiple moving objects. Our contribution is three-fold: (i) we propose a matrix representation of segmentation that permits to formulate the problem in terms of 'synchronization' of binary matrices; (ii) we derive a spectral solution to solve such a problem, which is inspired by previous works on synchronization of rotations, homographies, rigid motions and permutations; (iii) we explain how our solution can be interpreted in terms of spectral clustering. The proposed approach is validated on both synthetic and real scenarios, in addition to the Hopkins benchmark.

Motion segmentation via synchronization

Arrigoni Federica;
2019-01-01

Abstract

In this paper we consider the problem of segmenting points in a collection of images that contain multiple moving objects. Our contribution is three-fold: (i) we propose a matrix representation of segmentation that permits to formulate the problem in terms of 'synchronization' of binary matrices; (ii) we derive a spectral solution to solve such a problem, which is inspired by previous works on synchronization of rotations, homographies, rigid motions and permutations; (iii) we explain how our solution can be interpreted in terms of spectral clustering. The proposed approach is validated on both synthetic and real scenarios, in addition to the Hopkins benchmark.
2019
2019 International Conference on Computer Vision Workshops
978-1-7281-5023-9
Motion segmentation
Spectral clustering
Synchronization
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1223972
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