Weapon identification using hierarchical classification of acoustic signatures

Saad Khan; Ajay Divakaran; Harpreet S. Sawhney

doi:10.1117/12.818375

5 May 2009 Weapon identification using hierarchical classification of acoustic signatures

Saad Khan, Ajay Divakaran, Harpreet S. Sawhney

Proceedings Volume 7305, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense VIII; 730510 (2009) https://doi.org/10.1117/12.818375
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

Abstract

We apply a unique hierarchical audio classification technique to weapon identification using gunshot analysis. The Audio Classification classifies each audio segment as one of ten weapon classes (e.g., 9mm, 22, shotgun etc.) using lowcomplexity Gaussian Mixture Models (GMM). The first level of hierarchy consists of classification into broad weapons categories such as Rifle, Hand-Gun etc. and the second consists of classification into specific weapons such as 9mm, 357 etc. Our experiments have yielded over 90% classification accuracy at the coarse (rifle-handgun) level of the classification hierarchy and over 85% accuracy at the finer level (weapon category such as 9mm).

Citation Download Citation

Saad Khan, Ajay Divakaran, and Harpreet S. Sawhney "Weapon identification using hierarchical classification of acoustic signatures", Proc. SPIE 7305, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense VIII, 730510 (5 May 2009); https://doi.org/10.1117/12.818375

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