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Whole-body Detection, Recognition and Identification at Altitude and Range

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arxiv 2311.05725 v1 pith:UBQE43S4 submitted 2023-11-09 cs.CV

classification cs.CV
keywords recognitiondetectionidentificationacceptanceaccuracyachievesanglesbiometric
verification ladder T0 review T1 audit T2 compute T3 formal
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In this paper, we address the challenging task of whole-body biometric detection, recognition, and identification at distances of up to 500m and large pitch angles of up to 50 degree. We propose an end-to-end system evaluated on diverse datasets, including the challenging Biometric Recognition and Identification at Range (BRIAR) dataset. Our approach involves pre-training the detector on common image datasets and fine-tuning it on BRIAR's complex videos and images. After detection, we extract body images and employ a feature extractor for recognition. We conduct thorough evaluations under various conditions, such as different ranges and angles in indoor, outdoor, and aerial scenarios. Our method achieves an average F1 score of 98.29% at IoU = 0.7 and demonstrates strong performance in recognition accuracy and true acceptance rate at low false acceptance rates compared to existing models. On a test set of 100 subjects with 444 distractors, our model achieves a rank-20 recognition accuracy of 75.13% and a TAR@1%FAR of 54.09%.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. A Quality-Guided Mixture of Score-Fusion Experts Framework for Human Recognition

    cs.CV 2025-07 conditional novelty 5.0 of 10

    Quality-weighted mixture-of-experts score fusion improves whole-body biometric recognition over fixed and learned baselines across face, gait, and body modalities.

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