Object cosegmentation
- 1 June 2011
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 2217-2224
- https://doi.org/10.1109/cvpr.2011.5995530
Abstract
Cosegmentation is typically defined as the task of jointly segmenting “something similar” in a given set of images. Existing methods are too generic and so far have not demonstrated competitive results for any specific task. In this paper we overcome this limitation by adding two new aspects to cosegmentation: (1) the “something” has to be an object, and (2) the “similarity” measure is learned. In this way, we are able to achieve excellent results on the recently introduced iCoseg dataset, which contains small sets of images of either the same object instance or similar objects of the same class. The challenge of this dataset lies in the extreme changes in viewpoint, lighting, and object deformations within each set. We are able to considerably outperform several competitors. To achieve this performance, we borrow recent ideas from object recognition: the use of powerful features extracted from a pool of candidate object-like segmentations. We believe that our work will be beneficial to several application areas, such as image retrieval.Keywords
This publication has 14 references indexed in Scilit:
- What is an object?Published by Institute of Electrical and Electronics Engineers (IEEE) ,2010
- Constrained parametric min-cuts for automatic object segmentationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2010
- Global and efficient self-similarity for object classification and detectionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2010
- Discriminative clustering for image co-segmentationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2010
- Half-integrality based algorithms for cosegmentation of imagesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2009
- Spatially Coherent Latent Topic Model for Concurrent Segmentation and Classification of Objects and ScenesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2007
- Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene CategoriesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2006
- LOCUS: learning object classes with unsupervised segmentationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Distinctive Image Features from Scale-Invariant KeypointsInternational Journal of Computer Vision, 2004
- "GrabCut"Published by Association for Computing Machinery (ACM) ,2004