Title: Automatic enrolment for gait-based person re-identification under various view angles

Authors: Imen Chtourou; Emna Fendri; Mohamed Hammami

Addresses: MIRACL Laboratory, ENIS, University of Sfax, Road Sokra, km 4, BP 1173, 3038 Sfax, Tunisia ' MIRACL Laboratory, FSS, University of Sfax, Road Sokra, km 4, BP 802, 3038 Sfax, Tunisia ' MIRACL Laboratory, FSS, University of Sfax, Road Sokra, km 4, BP 802, 3038 Sfax, Tunisia

Abstract: Automatic enrolment constitutes a demanding decision-making practice for person re-identification task but rarely considered in the literature. This paper introduces a new method for automatic enrolment relying on gait analysis. The enrolment problem involves that the gallery database is automatically fed as a new subject is presented. The originality of the proposed method is that in the gallery, a given subject may be represented by several samples. This will improve the re-identification under various view angles. Experiments on CASIA-B database based on accuracy, sensitivity and specificity proved the performance and flexibility of the proposed method.

Keywords: gait; automatic enrolment; person re-identification; view angles.

DOI: 10.1504/IJBM.2021.117868

International Journal of Biometrics, 2021 Vol.13 No.4, pp.432 - 446

Received: 08 Feb 2020
Accepted: 18 Oct 2020
Published online: 04 Oct 2021 *

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