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arXiv · 2607.13905

The 2nd International StepUP Competition for Biometric Footstep Recognition: From Steps to Strides

Robyn Larracy·Anant Gupta·Gourav Gupta·Ethan Eddy·Maxime Devanne·Cyril Meyer·Jin-Chern Chiou·Yueh-Shan Lee·Zong-Han Lu·Aaron Tabor·Erik Scheme
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Abstract

The International StepUP Competition Series was launched to advance research in pressure-based footstep biometrics through a standardized and challenging evaluation framework. Using the large-scale StepUP-P150 dataset (with more than 200,000 high-resolution dynamic footsteps from 150 individuals) and a previously unreleased test set, the 2nd edition of the competition addressed three key challenges: (1) generalization to unseen users with limited enrollment data, (2) robustness to domain shift caused by variations in footwear and walking speed and (3) effective fusion of paired left-right footsteps. While the first two challenges built on the inaugural competition, this edition introduced more extreme cross-domain conditions and moved beyond isolated footsteps to stride-level verification, enabling new opportunities for representation learning and inter-step information fusion. The competition attracted 26 registrants from academia and industry, with a best equal error rate of 8.00% achieved by the ArogyaPandit Research Team using a spatiotemporal CNN combined with an ensemble-based scoring strategy. The top solutions showcase the value of harnessing temporal patterns and of incorporating inference-time normalization and calibration strategies to improve scoring. However, the results also reveal that recognizing users in unseen personal footwear remains a challenge, especially in the presence of distractors with similar characteristics.

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Robyn Larracy, Anant Gupta, Gourav Gupta, Ethan Eddy, Maxime Devanne, Cyril Meyer, Jin-Chern Chiou, Yueh-Shan Lee, Zong-Han Lu, Aaron Tabor, Erik Scheme. 2026-07-15. The 2nd International StepUP Competition for Biometric Footstep Recognition: From Steps to Strides. https://arxiv.org/abs/2607.13905

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