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New Ordering-Based Pruning Metrics for Ensembles of Classifiers in Imbalanced Datasets Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Object Tracking Using the Parametric Active Contour Model in Video Streams

Author : Marcin Ciecholewski

Published in: Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015

Publisher: Springer International Publishing

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Abstract

This article proposes a new approach which helps to prevent the formation of self-crossings and loops in the parametric active contour model while tracking moving objects in video streams. The presented solutions mean that the process of tracking is stable in all subsequent video sequences. On the other hand, self-crossings of nodes and the resultant contour loops happen very often in the basic model and ruin the tracking process. The Gaussian filter was used to eliminate noise from video streams.

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previous chapter On Properties of Undersampling Bagging and Its Extensions for Imbalanced Data
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Metadata
Title
Object Tracking Using the Parametric Active Contour Model in Video Streams
Author
Marcin Ciecholewski
Copyright Year
2016
Book
Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015

Print ISBN: 978-3-319-26225-3

Electronic ISBN: 978-3-319-26227-7

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-26227-7_39

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