3D generic object categorization, localization and pose estimation
Top Cited Papers
- 1 January 2007
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- No. 15505499,p. 1-8
- https://doi.org/10.1109/iccv.2007.4408987
Abstract
We propose a novel and robust model to represent and learn generic 3D object categories. We aim to solve the problem of true 3D object categorization for handling arbitrary rotations and scale changes. Our approach is to capture a compact model of an object category by linking together diagnostic parts of the objects from different viewing points. We emphasize on the fact that our "parts" are large and discriminative regions of the objects that are composed of many local invariant features. Instead of recovering a full 3D geometry, we connect these parts through their mutual homographic transformation. The resulting model is a compact summarization of both the appearance and geometry information of the object class. We propose a framework in which learning is done via minimal supervision compared to previous works. Our results on categorization show superior performances to state-of-the-art algorithms such as (Thomas et al., 2006). Furthermore, we have compiled a new 3D object dataset that consists of 10 different object categories. We have tested our algorithm on this dataset and have obtained highly promising results.Keywords
This publication has 23 references indexed in Scilit:
- Flexible Object Models for Category-Level 3D Object RecognitionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2007
- 3D LayoutCRF for Multi-View Object Class Recognition and SegmentationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2007
- The pyramid match kernel: discriminative classification with sets of image featuresPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Scale & Affine Invariant Interest Point DetectorsInternational Journal of Computer Vision, 2004
- A Similarity-Based Aspect-Graph Approach to 3D Object RecognitionInternational Journal of Computer Vision, 2004
- Multiple View Geometry in Computer VisionPublished by Cambridge University Press (CUP) ,2004
- Semi-Local Affine Parts for Object RecognitionPublished by British Machine Vision Association and Society for Pattern Recognition ,2004
- Saliency, Scale and Image DescriptionInternational Journal of Computer Vision, 2001
- Object recognition from local scale-invariant featuresPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1999
- The singularities of the visual mappingBiological Cybernetics, 1976