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Detecting acceleration for gait and crime scene analysis

Detecting acceleration for gait and crime scene analysis
Detecting acceleration for gait and crime scene analysis
Identifying criminals from CCTV footage is often a difficult task for crime investigations. The quality of CCTV is often low and criminals can cover their face and wear gloves (to withhold fingerprints) when committing a crime. Gait is the optimal choice in this circumstance since people can be recognised by their walking style, even at a distance with low resolution imagery. The location of the frame when the heel strikes the floor is essential for some gait analyses. We propose a new method to detect heel strikes: by radial acceleration which can also generalise to crime analysis. The frame and position of the heel strikes can be estimated by the quantity and the circle centres of radial acceleration, derived from the optical flow (using DeepFlow). Experimental results show high detection rate on two different gait databases and good robustness under different kinds of noise. We analysedetection of heel strikes to show robustness then we analyse crime scenes to show generalisation capability since violent crime often involves much acceleration. As such, we provide a new basis to a baseline technique in crime scene analysis.
Heel strike detection, Acceleration, Optical flow, Gait Analysis
13-18
Institution of Engineering and Technology
Sun, Yan
15039395-4052-4cb3-b2a8-1c7b08eff821
Hare, Jonathon
65ba2cda-eaaf-4767-a325-cd845504e5a9
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Sun, Yan
15039395-4052-4cb3-b2a8-1c7b08eff821
Hare, Jonathon
65ba2cda-eaaf-4767-a325-cd845504e5a9
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12

Sun, Yan, Hare, Jonathon and Nixon, Mark (2016) Detecting acceleration for gait and crime scene analysis. In 7th International Conference on Imaging for Crime Detection and Prevention (ICDP 2016) : Madrid, Spain 23 – 25 November 2016. Institution of Engineering and Technology. pp. 13-18 .

Record type: Conference or Workshop Item (Paper)

Abstract

Identifying criminals from CCTV footage is often a difficult task for crime investigations. The quality of CCTV is often low and criminals can cover their face and wear gloves (to withhold fingerprints) when committing a crime. Gait is the optimal choice in this circumstance since people can be recognised by their walking style, even at a distance with low resolution imagery. The location of the frame when the heel strikes the floor is essential for some gait analyses. We propose a new method to detect heel strikes: by radial acceleration which can also generalise to crime analysis. The frame and position of the heel strikes can be estimated by the quantity and the circle centres of radial acceleration, derived from the optical flow (using DeepFlow). Experimental results show high detection rate on two different gait databases and good robustness under different kinds of noise. We analysedetection of heel strikes to show robustness then we analyse crime scenes to show generalisation capability since violent crime often involves much acceleration. As such, we provide a new basis to a baseline technique in crime scene analysis.

Text
Detecting Acceleration for Gait and Crime Scene Analysis_YSun_JSHare_MSNixon.pdf - Accepted Manuscript
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More information

Accepted/In Press date: 3 October 2016
e-pub ahead of print date: November 2016
Published date: November 2016
Venue - Dates: International Conference on Imaging for Crime Detection and Prevention, Madrid,, Spain, 2016-11-23 - 2016-11-25
Keywords: Heel strike detection, Acceleration, Optical flow, Gait Analysis

Identifiers

Local EPrints ID: 402396
URI: http://eprints.soton.ac.uk/id/eprint/402396
PURE UUID: 8ae3b249-754f-4c91-b023-c8631de0c58b
ORCID for Jonathon Hare: ORCID iD orcid.org/0000-0003-2921-4283
ORCID for Mark Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 07 Nov 2016 10:34
Last modified: 07 Oct 2020 16:40

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