inria-00548684, version 1
Learning Distance Functions for Automatic Annotation of Images
Josip Krapac
a, 1Frédéric Jurie
b, 1
5th Adaptive Multimedia Retrieval 4918 (2007) 1--16
Abstract: This paper gives an overview of recent approaches towards image representation and image similarity computation for content-based image retrieval and automatic image annotation (category tagging). Additionaly, a new similarity function between an image and an object class is proposed. This similarity function combines various aspects of object class appearance through use of representative images of the class. Similarity to a representative image is determined by weighting local image similarities, where weights are learned from training image pairs, labeled “same” and “different”, using linear SVM. The proposed approach is validated on a challenging dataset where it performed favorably.
- a – INRIA
- b – Université de Caen
- 1: LEAR (INRIA Grenoble Rhône-Alpes / LJK Laboratoire Jean Kuntzmann)
- CNRS : FR71 – CNRS : UMR5527 – INRIA – Laboratoire Jean Kuntzmann – Université Joseph Fourier - Grenoble I – Institut National Polytechnique de Grenoble (INPG)
- Domain : Computer Science/Computer Vision and Pattern Recognition
- inria-00548684, version 1
- http://hal.inria.fr/inria-00548684
- oai:hal.inria.fr:inria-00548684
- From: Team Lear
- Submitted for:
- Submitted on: Tuesday, 25 January 2011 12:52:49
- Updated on: Thursday, 27 January 2011 11:41:26






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