{"ID":2867739,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.17805","arxiv_id":"2509.17805","title":"Selecting Optimal Camera Views for Gait Analysis: A Multi-Metric Assessment of 2D Projections","abstract":"Objective: To systematically quantify the effect of the camera view (frontal vs. lateral) on the accuracy of 2D markerless gait analysis relative to 3D motion capture ground truth. Methods: Gait data from 18 subjects were recorded simultaneously using frontal, lateral and 3D motion capture systems. Pose estimation used YOLOv8. Four metrics were assessed to evaluate agreement: Dynamic Time Warping (DTW) for temporal alignment, Maximum Cross-Correlation (MCC) for signal similarity, Kullback-Leibler Divergence (KLD) for distribution differences, and Information Entropy (IE) for complexity. Wilcoxon signed-rank tests (significance: $p \u003c 0.05$) and Cliff's delta ($δ$) were used to measure statistical differences and effect sizes. Results: Lateral views significantly outperformed frontal views for sagittal plane kinematics: step length (DTW: $53.08 \\pm 24.50$ vs. $69.87 \\pm 25.36$, $p = 0.005$) and knee rotation (DTW: $106.46 \\pm 38.57$ vs. $155.41 \\pm 41.77$, $p = 0.004$). Frontal views were superior for symmetry parameters: trunk rotation (KLD: $0.09 \\pm 0.06$ vs. $0.30 \\pm 0.19$, $p \u003c 0.001$) and wrist-to-hipmid distance (MCC: $105.77 \\pm 29.72$ vs. $75.20 \\pm 20.38$, $p = 0.003$). Effect sizes were medium-to-large ($δ: 0.34$--$0.76$). Conclusion: Camera view critically impacts gait parameter accuracy. Lateral views are optimal for sagittal kinematics; frontal views excel for trunk symmetry. Significance: This first systematic evidence enables data-driven camera deployment in 2D gait analysis, enhancing clinical utility. Future implementations should leverage both views via disease-oriented setups.","short_abstract":"Objective: To systematically quantify the effect of the camera view (frontal vs. lateral) on the accuracy of 2D markerless gait analysis relative to 3D motion capture ground truth. Methods: Gait data from 18 subjects were recorded simultaneously using frontal, lateral and 3D motion capture systems. Pose estimation used...","url_abs":"https://arxiv.org/abs/2509.17805","url_pdf":"https://arxiv.org/pdf/2509.17805v1","authors":"[\"Dong Chen\",\"Huili Peng\",\"Yong Hu\",\"Kenneth MC. Cheung\"]","published":"2025-09-22T14:00:20Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[]","has_code":false}