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%.

我们提出了一个端到端系统，用于在长达 500 米和大于 50 度的高角度的情况下进行全身生物识别的检测、识别和辨认。我们的方法在各种室内、室外和航空场景下进行了全面的评估，表现出强大的识别准确性和低虚假接受率。