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arXiv Computer Vision By Athanasios Angelakis, Marta Gomez-Barrero

From ECG Signals to Representative-Morphology Heatmaps for Biometric Recognition

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The paper introduces representative‑morphology heatmaps, a deterministic ECG‑to‑image representation that averages the five beats closest to the block mean within each ten‑beat block, producing either a conventional trace or a dense cardiac‑time‑by‑lead heatmap. Experiments on PTB, ECG‑ID, and MIMIC‑IV‑ECG‑DEMO show that heatmaps consistently improve verification and identification performance across 15 compact models, reducing EER by an average of 9.59 percentage points and increasing Rank‑1 by 24.69 points. The study also demonstrates that ImageNet initialization benefits multilead datasets, that performance does not scale monotonically with model size, and that useful channel combinations vary by cohort and biometric task.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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