inria-00548577, version 1
Towards multi-view object class detection
Alexander Thomas 1Vittorio Ferrari
2Bastian Leibe 3Tinne Tuytelaars 4Bernt Schiele 5Luc Van Gool 3
IEEE Conference on Computer Vision & Pattern Recognition (CPRV '06) 2 (2006) 1589
Abstract: We present a novel system for generic object class detection. In contrast to most existing systems which focus on a single viewpoint or aspect, our approach can detect object instances from arbitrary viewpoints. This is achieved by combining the Implicit Shape Model for object class detection proposed by Leibe and Schiele with the multi-view specific object recognition system of Ferrari et al. After learning single-view codebooks, these are interconnected by so-called activation links, obtained through multi-view region tracks across different training views of individual object instances. During recognition, these integrated codebooks work together to determine the location and pose of the object. Experimental results demonstrate the viability of the approach and compare it to a bank of independent single-view detectors.
- 1: Katholieke Universiteit Leuven (KUL)
- Université Catholique de Louvain
- 2: LEAR (IMAG-INRIA Rhône-Alpes / GRAVIR)
- CNRS : FR71 – CNRS : UMR5527 – INRIA – Université Joseph Fourier - Grenoble I – Institut National Polytechnique de Grenoble (INPG)
- 3: Eldgenössische Technische Hochschule Zürich (ETH Zürich)
- ETH Zurich
- 4: Department of Electrical Engineering (ESAT)
- Katholieke Universiteit Leuven
- 5: Department of Computer Science
- Technische Universitat Darmstadt
- Domain : Computer Science/Computer Vision and Pattern Recognition
- Keywords : object detection – multiple views – local features
- inria-00548577, version 1
- http://hal.inria.fr/inria-00548577
- oai:hal.inria.fr:inria-00548577
- From: Team Lear
- Submitted for:
- Submitted on: Monday, 20 December 2010 09:49:18
- Updated on: Monday, 10 January 2011 11:39:33






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