BiCoS: a bi-level co-segmentation method for image classification

Conference item

The objective of this paper is the unsupervised segmentation of image training sets into foreground and background in order to improve image classification performance. To this end we introduce a new scalable, alternation-based algorithm for co-segmentation, BiCoS, which is simpler than many of its predecessors, and yet has superior performance on standard benchmark image datasets.

Authors: Chai, Y; Lempitsky, V; Zisserman, A

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: IEEE
• Host title: 2011 International Conference on Computer Vision
• Pages: 2579-2586
• Publication date: 2012-01-12
• Event title: 13th International Conference on Computer Vision Workshops (ICCVW 2011)
• Event location: Barcelona, Spain
• Event start date: 2011-11-06
• Event end date: 2011-11-13
• DOI: 10.1109/iccv.2011.6126546
• EISSN: 2380-7504
• ISSN: 1550-5499
• EISBN: 9781457711022
• ISBN: 9781457711015
• Language: English
• Keywords: image color analysis; birds; support vector machines; accuracy; training; visualization; image segmentation