inria-00548679, version 1
Accurate Object Localization with Shape Masks
Marcin Marszałek 1, 2Cordelia Schmid
1, 2
IEEE Conference on Computer Vision & Pattern Recognition (CVPR '07) (2007) 1--8
Abstract: This paper proposes an object class localization approach which goes beyond bounding boxes, as it also determines the outline of the object. Unlike most current localization methods, our approach does not require any hypothesis parameter space to be defined. Instead, it directly generates, evaluates and clusters shape masks. Thus, the presented framework produces much richer answers to the object class localization problem. For example, it easily learns and detects possible object viewpoints and articulations, which are often well characterized by the object outline. We evaluate the proposed approach on the challenging natural-scene Graz-02 object classes dataset. The results demonstrate the extended localization capabilities of our method.
- 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)
- 2: Laboratoire Jean Kuntzmann (LJK)
- CNRS : UMR5224 – Université Joseph Fourier - Grenoble I – Université Pierre Mendès-France - Grenoble II – Institut Polytechnique de Grenoble - Grenoble Institute of Technology
- Domain : Computer Science/Computer Vision and Pattern Recognition
- Keywords : computer vision – object recognition
- inria-00548679, version 1
- http://hal.inria.fr/inria-00548679
- oai:hal.inria.fr:inria-00548679
- From: Team Lear
- Submitted for:
- Submitted on: Monday, 20 December 2010 10:28:09
- Updated on: Monday, 10 January 2011 17:25:24
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