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Proceedings Paper

A visual scene busyness measure through a region growing spatial segmentation
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Paper Abstract

This paper proposes a visual scene busyness indicator obtained from the properties of a full spatial segmentation of static images. A fast and effective region merging scheme is applied for this purpose. It uses a semi-greedy merging criterion and an adaptive threshold to control segmentation resolution. The core of the framework is a hierarchical parallel merging model and region reduction techniques. The segmentation procedure consists of the following phases: 1. algorithmic region merging, and 2. region reduction, which includes small segment reduction and enclosed region absorption. Quantitative analyses on standard benchmark data have shown the procedure to compare favourably to other segmentation methods. Qualitative assessment of the segmentation results indicate approximate semantic correlations between segmented regions and real world objects. This characteristic is used as a basis for quantifying scene busyness in terms of properties of the segmentation map and the segmentation process that generates it. A visual busyness indicator based on full colour segmentation is evaluated against conventional measures.

Paper Details

Date Published: 30 October 2012
PDF: 9 pages
Proc. SPIE 8546, Optics and Photonics for Counterterrorism, Crime Fighting, and Defence VIII, 85460P (30 October 2012); doi: 10.1117/12.974760
Show Author Affiliations
Gaurav Gupta, Univ. of Westminster (United Kingdom)
Alexandra Psarrou, Univ. of Westminster (United Kingdom)
Sophie Triantaphillidou, Univ. of Westminster (United Kingdom)
Jae-Young Park, Univ. of Westminster (United Kingdom)


Published in SPIE Proceedings Vol. 8546:
Optics and Photonics for Counterterrorism, Crime Fighting, and Defence VIII
Colin Lewis; Douglas Burgess, Editor(s)

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