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Erschienen in:
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2017 | OriginalPaper | Buchkapitel

3D Motion Consistency Analysis for Segmentation in 2D Video Projection

verfasst von : Wei Zhao, Nico Roos, Ralf Peeters

Erschienen in: Computer Analysis of Images and Patterns

Verlag: Springer International Publishing

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Abstract

Motion segmentation for 2D videos is usually based on tracked 2D point motions, obtained for a sequence of frames. However, the 3D real world motion consistency is easily lost in the process, due to projection from 3D space to the 2D image plane. Several approaches have been proposed in the literature to recover 3D motion consistency from 2D point motions. To further improve on this, we here propose a new criterion and associated technique, which can be used to determine whether a group of points show 2D motions consistent with joint 3D motion. It is also applicable for estimating the 3D motion information content. We demonstrate that the proposed criterion can be applied to improve segmentation results in two ways: finding the misclassified points in a group, and assigning unclassified points to the correct group. Experiments with synthetic data and different noise levels, and with real data taken from a benchmark, give insight in the performance of the algorithm under various conditions.

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Vorheriges Kapitel Object Triggered Egocentric Video Summarization
Nächstes Kapitel Space-Variant Gabor Decomposition for Filtering 3D Medical Images
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Metadaten
Titel
3D Motion Consistency Analysis for Segmentation in 2D Video Projection
verfasst von
Wei Zhao
Nico Roos
Ralf Peeters
Copyright-Jahr
2017
Buch
Computer Analysis of Images and Patterns

Print ISBN: 978-3-319-64697-8

Electronic ISBN: 978-3-319-64698-5

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-64698-5_37