Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICIP.2007.4380025
Title: Background cutout with automatic object discovery
Authors: Liu D.
Chen T. 
Keywords: Image segmentation
Unsupervised learning
Issue Date: 2007
Publisher: IEEE Computer Society
Citation: Liu D., Chen T. (2007). Background cutout with automatic object discovery. Proceedings - International Conference on Image Processing, ICIP 4 : IV345-IV348. ScholarBank@NUS Repository. https://doi.org/10.1109/ICIP.2007.4380025
Abstract: We present a novel approach to background cutout for image editing. We show how background cutout can be achieved without any user labeling. This is in contrast to current methods, where the user needs to label each image separately. Our method uses automatic object discovery methods to provide location and scale estimates of the object of interest; these estimates then provide seeds for initializing color distributions of a segmentation algorithm. We show that our approach can achieve similar performance as traditional methods that require users to specify for each image a bounding box of the target object.
Source Title: Proceedings - International Conference on Image Processing, ICIP
URI: http://scholarbank.nus.edu.sg/handle/10635/146279
ISBN: 1424414377
9781424414376
ISSN: 15224880
DOI: 10.1109/ICIP.2007.4380025
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.