Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Exploring the relationship between stride, stature and hand size for forensic assessment
AU - Guest, Richard M.
AU - Miguel-Hurtado, Oscar
AU - Stevenage, Sarah
AU - Black, Sue
N1 - The authors gratefully acknowledge the support of the UK Engineering and Physical Sciences Research Council in the production of this work funded as part of EPSRC EP/J004995/1.
PY - 2017/11/1
Y1 - 2017/11/1
N2 - Forensic evidence often relies on a combination of accurately recorded measurements, estimated measurements from landmark data such as a subject's stature given a known measurement within an image, and inferred data. In this study a novel dataset is used to explore linkages between hand measurements, stature, leg length and stride. These three measurements replicate the type of evidence found in surveillance videos with stride being extracted from an automated gait analysis system. Through correlations and regression modelling, it is possible to generate accurate predictions of stature from hand size, leg length and stride length (and vice versa), and to predict leg and stride length from hand size with, or without, stature as an intermediary variable. The study also shows improved accuracy when a subject's sex is known a-priori. Our method and models indicate the possibility of calculating or checking relationships between a suspect's physical measurements, particularly when only one component is captured as an accurately recorded measurement.
AB - Forensic evidence often relies on a combination of accurately recorded measurements, estimated measurements from landmark data such as a subject's stature given a known measurement within an image, and inferred data. In this study a novel dataset is used to explore linkages between hand measurements, stature, leg length and stride. These three measurements replicate the type of evidence found in surveillance videos with stride being extracted from an automated gait analysis system. Through correlations and regression modelling, it is possible to generate accurate predictions of stature from hand size, leg length and stride length (and vice versa), and to predict leg and stride length from hand size with, or without, stature as an intermediary variable. The study also shows improved accuracy when a subject's sex is known a-priori. Our method and models indicate the possibility of calculating or checking relationships between a suspect's physical measurements, particularly when only one component is captured as an accurately recorded measurement.
U2 - 10.1016/j.jflm.2017.08.006
DO - 10.1016/j.jflm.2017.08.006
M3 - Journal article
VL - 52
SP - 46
EP - 55
JO - Journal of Forensic and Legal Medicine
JF - Journal of Forensic and Legal Medicine
SN - 1752-928X
ER -