Eliciting perceptual ground truth for image segmentation

Authors:
Victoria Hodge;Garry Hollier;John Eakins;Jim Austin
Affiliations:
Advanced Computer Architectures Group, Department of Computer Science, University of York, York, UK;Advanced Computer Architectures Group, Department of Computer Science, University of York, York, UK;Advanced Computer Architectures Group, Department of Computer Science, University of York, York, UK;Advanced Computer Architectures Group, Department of Computer Science, University of York, York, UK
Venue:
CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
Year:
2006

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Abstract

In this paper, we investigate human visual perception and establish a body of ground truth data elicited from human visual studies. We aim to build on the formative work of Ren, Eakins and Briggs who produced an initial ground truth database. Human participants were asked to draw and rank their perceptions of the parts of a series of figurative images. These rankings were then used to score the perceptions, identify the preferred human breakdowns and thus allow us to induce perceptual rules for human decomposition of figurative images. The results suggest that the human breakdowns follow well-known perceptual principles in particular the Gestalt laws.