Generalized Boundaries from Multiple Image Interpretations

Details Generalized Boundaries from Multiple Image Interpretations Generalized Boundaries from Multiple Image Interpretations

2012-02-16

arxiv.org/abs/1202.3684v1

Computer Science

Computer Vision and Pattern Recognition

Scientific paper

Boundary detection is essential for a variety of computer vision tasks such as segmentation and recognition. In this paper we propose a unified formulation and a novel algorithm that are applicable to the detection of different types of boundaries, such as intensity edges, occlusion boundaries or object category specific boundaries. Our formulation leads to a simple method with state-of-the-art performance and significantly lower computational cost than existing methods. We evaluate our algorithm on different types of boundaries, from low-level boundaries extracted in natural images, to occlusion boundaries obtained using motion cues and RGB-D cameras, to boundaries from soft-segmentation. We also propose a novel method for figure/ground soft-segmentation that can be used in conjunction with our boundary detection method and improve its accuracy at almost no extra computational cost.

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