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Lauren Barghout; Empirical data on the configural architecture of human scene perception using natural images. Journal of Vision 2009;9(8):964. doi: https://doi.org/10.1167/9.8.964.
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© ARVO (1962-2015); The Authors (2016-present)
Purpose: Both local and configural processes play a role in the figure-ground organization of scenes. Local factors include bottom-up processes that fuse smaller regions into a larger figure. Configural theories propose top-down processes able to utilize more global scene information, prior experience, and meaningfulness. The Berkeley Segmentation DataSet (Martin, Fowlkes, Tal, & Malik (2001)) provides a corpus of images whose contours were hand segmented by humans and annotated for figure-ground status. Though useful for studying local mechanisms, an additional dataset designed to capture configural information is also needed.
Methods: Paper surveys consisted of a photograph and the instructions: “Please put an “x” at the ‘center of the subject of the photograph and write a few words to describe it”. Photographs, downloaded the internet via Google, search were chosen for object type and configuration to match an N by M factorial design, where N represents object type (such as a bird) and M the number of objects of the same type appearing in the image. Configurations of single, double, triple and large numbers were used. For each photograph, at least 50 surveys were collected.
This method assumes that asking someone to mark the ‘center of the subject of the photograph’ serves as a proxy of the figural status of the region centered at the point marked. Since the method does not distinguish between a foreground, a single object or an object within an object, I use the term ‘spatial taxon’ to refer to a region centered around the position indicated by survey participants. This operational definition is analogous to but also much broader than the term ‘figure’ as defined in the literature.
Conclusion: A dataset of natural scenes annotated with empirically derived spatial taxons and their relative frequency provides insight as to the configural architecture of natural scenes.
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