Highly Consistent Sequential Segmentation

Michael Donoser, Martin Urschler, Hayko Riemenschneider, Horst Bischof

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in Buch/Bericht

Abstract

This paper deals with segmentation of image sequences in an unsupervised manner with the goal of getting highly consistent segmentation results from frame-to-frame. We first introduce a segmentation method that uses results of the previous frame as initialization and significantly improves consistency in comparison to a single frame based approach. We also find correspondences between the segmented regions from one frame to the next to further increase consistency. This matching step is based on a modified version of an efficient partial shape matching method which allows identification of similar parts of regions despite topology changes like merges and splits. We use the identified matched parts to define a partial matching cost which is then used as input to pairwise graph matching. Experiments demonstrate that we can achieve highly consistent segmentations for diverse image sequences, even allowing to track manually initialized moving and static objects.
Originalspracheenglisch
TitelImage Analysis
Untertitel17th Scandinavian Conference, SCIA 2011, Ystad, Sweden, May 2011. Proceedings
Redakteure/-innenAnders Heyden, Fredrik Kahl
Herausgeber (Verlag)Springer International Publishing AG
Seiten48-58
Band6688
ISBN (elektronisch)978-3-642-21227-7
ISBN (Print)978-3-642-21226-0
DOIs
PublikationsstatusVeröffentlicht - 2011
VeranstaltungScandinavian Conference on Image Analysis - Ystad Saltsjöbad, Schweden
Dauer: 23 Mai 201127 Mai 2011

Publikationsreihe

NameLecture Notes in Computer Science

Konferenz

KonferenzScandinavian Conference on Image Analysis
LandSchweden
OrtYstad Saltsjöbad
Zeitraum23/05/1127/05/11

Fields of Expertise

  • Information, Communication & Computing

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