PolarBearVidID: A Video-based Re-Identification Benchmark Dataset for Polar Bears

The peer-reviewed publication for this dataset has now been published in Animals, an MDPI journal, and can be accessed here: https://doi.org/10.3390/ani13050801. Please cite this when using the dataset. PolarBearVidID includes 13 individual polar bears housed in six institutions. Each identity has 110 sequences on average. The maximum length of the sequences is 8 seconds, respectively 100 frames at a frame rate of 12.5 frames per second. The average length of the sequences is 96.69 images. In total, the dataset includes 1431 sequences. The resolution of the images is set to 256 x 128 pixels. Finally, PolarBearVidID is the first dataset to enable utilizing the movement of a non-human species as a feature for the task of re-identification.本数据集的同行评议论文现已发表于MDPI旗下期刊《Animals》，可通过以下链接获取：https://doi.org/10.3390/ani13050801。使用本数据集时请引用该论文。 PolarBearVidID数据集共收录了来自6家机构的13只独立北极熊个体，每个个体平均包含110条序列。单条序列的最长时长为8秒，当帧率为12.5帧每秒时，对应100帧图像；序列的平均长度为96.69帧图像。本数据集总计包含1431条序列，图像分辨率统一为256×128像素。最后，PolarBearVidID是首个将非人类物种的运动特征应用于身份重识别任务的数据集。

搜集汇总

背景与挑战

背景概述

PolarBearVidID是一个基于视频的北极熊再识别基准数据集，包含来自六个机构的13只北极熊，总计1431个序列，平均每个身份110个序列，序列最大长度8秒，图像分辨率256x128像素。该数据集首次实现了利用非人类物种的运动特征进行再识别任务，为动物行为研究和深度学习应用提供了重要资源。