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Proceedings Paper

Human pose classification within the context of near-IR imagery tracking
Author(s): Jiwan Han; Anna Gaszczak; Ryszard Maciol; Stuart E. Barnes; Toby P. Breckon
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Paper Abstract

We address the challenge of human behaviour analysis within automated image understanding. Whilst prior work concentrates on this task within visible-band (EO) imagery, by contrast we target basic human pose classification in thermal-band (infrared, IR) imagery. By leveraging the key advantages of limb localization this imagery offers we target two distinct human pose classification problems of varying complexity: 1) identifying passive or active individuals within the scene and 2) the identification of individuals potentially carrying weapons. Both approaches use a discrete set of features capturing body pose characteristics from which a range of machine learning techniques are then employed for final classification. Significant success is shown on these challenging tasks over a wide range of environmental conditions within the wider context of automated human target tracking in thermal-band (IR) imagery.

Paper Details

Date Published: 16 October 2013
PDF: 11 pages
Proc. SPIE 8901, Optics and Photonics for Counterterrorism, Crime Fighting and Defence IX; and Optical Materials and Biomaterials in Security and Defence Systems Technology X, 89010E (16 October 2013); doi: 10.1117/12.2028375
Show Author Affiliations
Jiwan Han, Cranfield Univ. (United Kingdom)
Anna Gaszczak, Cranfield Univ. (United Kingdom)
Ryszard Maciol, Cranfield Univ. (United Kingdom)
Stuart E. Barnes, Cranfield Univ. (United Kingdom)
Toby P. Breckon, Cranfield Univ. (United Kingdom)


Published in SPIE Proceedings Vol. 8901:
Optics and Photonics for Counterterrorism, Crime Fighting and Defence IX; and Optical Materials and Biomaterials in Security and Defence Systems Technology X
Roberto Zamboni; Douglas Burgess; Gari Owen; Francois Kajzar; Attila A. Szep, Editor(s)

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