Improved Image Boundaries for Better Video Segmentation

Anna Khoreva, Rodrigo Benenson, Fabio Galasso,

Matthias Hein and Bernt Schiele

Abstract

Graph-based video segmentation methods rely on superpixels as starting point. While most previous work has focused on the construction of the graph edges and weights as well as solving the graph partitioning problem, this paper focuses on better superpixels for video segmentation. We demonstrate by a comparative analysis that superpixels extracted from boundaries perform best, and show that
boundary estimation can be significantly improved via image and time domain cues. With superpixels generated from our better boundaries we observe consistent improvement for two video segmentation methods in two different datasets.

Results

Data

ArXiv  Paper   Presentation slides

For further information or data, please contact Anna Khoreva <khoreva at mpi-inf.mpg.de>.

References

[Khoreva et al., 2016] Improved Image Boundaries for Better Video Segmentation, A. Khoreva, R. Benenson, F. Galasso,  M. Hein and B. Schiele, ECCV Workshops, (2016)

 

@inproceedings{khoreva_ECCV16,
title={Improved Image Boundaries for Better Video Segmentation
},
author={A. Khoreva and R. Benenson and F. Galasso and M. Hein and B. Schiele},
booktitle={
European Conference on Computer Vision Workshops},
year={2016}}