Towards robust scene analysis: A versatile mid-level feature framework

Engel, D; Curio, C

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Towards robust scene analysis: A versatile mid-level feature framework

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Engel, D
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Project group: Cognitive Engineering, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Curio, C
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Project group: Cognitive Engineering, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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http://www.cogsys2010.ethz.ch/proceedings.html
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Citation

Engel, D., & Curio, C. (2010). Towards robust scene analysis: A versatile mid-level feature framework. Poster presented at 4th International Conference on Cognitive Systems (CogSys 2010), Zürich, Switzerland.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-C18E-3

Abstract

We present a novel set of shape-centered interest points. The interest points are formed at locations of high local symmetry. Our symmetry detection is based on Gradient Vector Flow (GVF) [1] fields which provide a high level of stability against noise. The shape centered interest points allow for a robust scale and orientation estimation. We have shown their usefulness for image encoding and superpixel segmentation and demonstrat that they carry information that is to a certain degree complementary to corner based interest points.