第二届生物特征足迹识别国际StepUP竞赛：从单步到跨步
The 2nd International StepUP Competition for Biometric Footstep Recognition: From Steps to Strides
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中文总结 AI 辅助
第二届生物特征足迹识别国际StepUP竞赛利用大规模数据集应对三项关键挑战，吸引26个注册者。ArogyaPandit研究团队用时空卷积神经网络结合集成评分策略获8.00%最佳等错误率，顶级方案展示相关策略价值，不过识别未知个人鞋类用户仍具挑战。
中文摘要 AI 辅助
国际StepUP竞赛系列旨在通过标准化且具挑战性的评估框架推动基于压力的足迹生物特征识别研究。第二届竞赛使用大规模StepUP - P150数据集及未发布测试集，应对三项关键挑战：有限注册数据下对未知用户的泛化、鞋类和步行速度变化导致的域转移鲁棒性、左右配对足迹的有效融合。竞赛吸引26个来自学术界和行业的注册者，ArogyaPandit研究团队采用时空卷积神经网络结合基于集成的评分策略取得8.00%的最佳等错误率。顶级解决方案展示了利用时间模式及纳入推理时归一化和校准策略以改进评分的价值，但结果也表明识别未知个人鞋类中的用户仍是挑战，尤其是存在具有相似特征的干扰因素时。
英文摘要
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.
发表机构
- University of New Brunswick（新不伦瑞克大学）
- ArogyaPandit Private Limited（阿罗吉亚潘迪特私人有限公司）
- Institute of Electrical and Control Engineering, National Yang Ming Chiao Tung University（国立阳明交通大学电气与控制工程研究所）
机构由 AI 辅助整理，请以论文原文为准。
