Literature DB >> 21554307

On using gait in forensic biometrics.

Imed Bouchrika1, Michaela Goffredo, John Carter, Mark Nixon.   

Abstract

Given the continuing advances in gait biometrics, it appears prudent to investigate the translation of these techniques for forensic use. We address the question as to the confidence that might be given between any two such measurements. We use the locations of ankle, knee, and hip to derive a measure of the match between walking subjects in image sequences. The Instantaneous Posture Match algorithm, using Harr templates, kinematics, and anthropomorphic knowledge is used to determine their location. This is demonstrated using real CCTV recorded at Gatwick International Airport, laboratory images from the multiview CASIA-B data set, and an example of real scene of crime video. To access the measurement confidence, we study the mean intra- and inter-match scores as a function of database size. These measures converge to constant and separate values, indicating that the match measure derived from individual comparisons is considerably smaller than the average match measure from a population.
© 2011 American Academy of Forensic Sciences.

Mesh:

Year:  2011        PMID: 21554307     DOI: 10.1111/j.1556-4029.2011.01793.x

Source DB:  PubMed          Journal:  J Forensic Sci        ISSN: 0022-1198            Impact factor:   1.832


  8 in total

1.  Comparing the face to the body, which is better for identification?

Authors:  Teghan Lucas; Maciej Henneberg
Journal:  Int J Legal Med       Date:  2015-02-10       Impact factor: 2.686

2.  Robust clothing-independent gait recognition using hybrid part-based gait features.

Authors:  Zhipeng Gao; Junyi Wu; Tingting Wu; Renyu Huang; Anguo Zhang; Jianqiang Zhao
Journal:  PeerJ Comput Sci       Date:  2022-05-31

3.  Recognition of a Person Wearing Sport Shoes or High Heels through Gait Using Two Types of Sensors.

Authors:  Marcin Derlatka; Mariusz Bogdan
Journal:  Sensors (Basel)       Date:  2018-05-21       Impact factor: 3.576

4.  Gait recognition using a few gait frames.

Authors:  Lingxiang Yao; Worapan Kusakunniran; Qiang Wu; Jian Zhang
Journal:  PeerJ Comput Sci       Date:  2021-03-01

5.  A Low-Cost, Autonomous Gait Detection and Estimation System for Analyzing Gait Impairments in Mice.

Authors:  Pranav U Damale; Edwin K P Chong; Sean L Hammond; Ronald B Tjalkens
Journal:  J Healthc Eng       Date:  2021-11-12       Impact factor: 2.682

6.  Speed invariant gait recognition-The enhanced mutual subspace method.

Authors:  Yumi Iwashita; Hitoshi Sakano; Ryo Kurazume; Adrian Stoica
Journal:  PLoS One       Date:  2021-08-11       Impact factor: 3.240

7.  CNN-Based Multimodal Human Recognition in Surveillance Environments.

Authors:  Ja Hyung Koo; Se Woon Cho; Na Rae Baek; Min Cheol Kim; Kang Ryoung Park
Journal:  Sensors (Basel)       Date:  2018-09-11       Impact factor: 3.576

Review 8.  Critical review of the use and scientific basis of forensic gait analysis.

Authors:  Nina M van Mastrigt; Kevin Celie; Arjan L Mieremet; Arnout C C Ruifrok; Zeno Geradts
Journal:  Forensic Sci Res       Date:  2018-10-09
  8 in total

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