Automatic extraction and classification of footwear patterns

Pavlou, M. and Allinson, Nigel (2006) Automatic extraction and classification of footwear patterns. In: 7th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2006, 20-23 September 2006, Burgos, Spain.

Full content URL: http://link.springer.com/chapter/10.1007%2F1187558...

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Item Type:Conference or Workshop contribution (Paper)
Item Status:Live Archive

Abstract

Identification of the footwear traces from crime scenes is an important yet largely forgotten aspect of forensic intelligence and evidence. We present initial results from a developing automatic footwear classification system. The underlying methodology is based on large numbers of localized features located using MSER feature detectors. These features are transformed into robust SIFT or GLOH descriptors with the ranked correspondence between footwear patterns obtained through the use of constrained spectral correspondence methods. For a reference dataset of 368 different footwear patterns, we obtain a first rank performance of 85% for full impressions and 84% for partial impressions. © Springer-Verlag Berlin Heidelberg 2006.

Keywords:Artificial intelligence, Automation, Classification (of information), Data structures, Feature extraction, Spectrum analysis, Constrained spectral correspondence methods, Feature detectors, Feature transformation, Footwear traces, Pattern recognition
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
G Mathematical and Computer Sciences > G740 Computer Vision
F Physical Sciences > F410 Forensic Science
Divisions:College of Science > School of Computer Science
ID Code:8559
Deposited On:12 Apr 2013 10:09

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