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Main Menu - Block
- Overview
- Anatomy and Histology
- Cell and Tissue Culture
- Cryo-Electron Microscopy
- Drosophila Resources
- Electron Microscopy
- Flow Cytometry Shared Resource (FCSR)
- Gene Targeting and Transgenics
- Janelia Experimental Technology
- Light Microscopy
- Media Prep
- Molecular Biology
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- Project Technical Resources
- Quantitative Genomics
- Scientific Computing Software
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Abstract
In practice, understanding the spatial relationships between the surfaces of an object, can significantly improve the performance of object recognition systems. In this paper we propose a novel framework to recognize objects in pictures taken from arbitrary viewpoints. The idea is to maintain the frontal views of the major faces of objects in a global flat map. Then an unfolding warping technique is used to change the pose of the query object in the test view so that all visible surfaces of the object can be observed from a frontal viewpoint, improving the handling of serious occlusions and large viewpoint changes. We demonstrate the effectiveness of our approach through analysis of recognition trials of complex objects with comparison to popular methods.