Graphcut-based interactive segmentation using colour and depth cues
He, Hu, McKinnon, David, Warren, Michael, & Upcroft, Ben (2010) Graphcut-based interactive segmentation using colour and depth cues. In Australasian Conference on Robotics and Automation (ACRA 2010), 1-3 December 2010, Queensland University of Technology, Brisbane.
Segmentation of novel or dynamic objects in
a scene, often referred to as background sub-
traction or foreground segmentation, is critical
for robust high level computer vision applica-
tions such as object tracking, object classifca-
tion and recognition. However, automatic real-
time segmentation for robotics still poses chal-
lenges including global illumination changes,
ections, colour similarity of
foreground to background, and cluttered back-
grounds. This paper introduces depth cues
provided by structure from motion (SFM) for
interactive segmentation to alleviate some of
these challenges. In this paper, two prevailing
interactive segmentation algorithms are com-
pared; Lazysnapping [Li et al., 2004] and Grab-
cut [Rother et al., 2004], both based on graph-
cut optimisation [Boykov and Jolly, 2001]. The
algorithms are extended to include depth cues
rather than colour only as in the original pa-
pers. Results show interactive segmentation
based on colour and depth cues enhances the
performance of segmentation with a lower er-
ror with respect to ground truth.
Citation countsare sourced monthly fromand citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
|Item Type:||Conference Paper|
|Keywords:||interactive segmentation, graph cuts, energy minimisation|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)|
|Divisions:||Current > QUT Faculties and Divisions > Division of Research and Commercialisation|
Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Schools > School of Engineering Systems
|Copyright Owner:||Copyright 2010 Please consult the authors.|
|Deposited On:||15 Mar 2011 12:16|
|Last Modified:||01 Mar 2012 00:33|
Repository Staff Only: item control page