Data set for the simulator experiment in the PLOS ONE article "Bio-inspired visual self-localization in real world scenarios using Slow Feature Analysis"

Data set for the simulator experiment in the PLOS ONE article:<br>"Bio-inspired visual self-localization in real world scenarios<br>using Slow Feature Analysis"<br><br>Images 'panorama_0.png' - 'panorama_628.png' are panoramic images rendered on<br>an equidistant grid in a simulator environment.<br><br>Sequences for the training- and test-set were created artificially by<br>sampling successive image/coordinate pairs from the grid.<br><br>The files 'train_sequence.csv' and 'test_sequence.csv' contain the image file<br>names and corresponding coordinates for the respective sets.本数据集用于发表于PLOS ONE期刊的论文《基于慢特征分析（Slow Feature Analysis）的真实场景仿生视觉自定位》中的模拟器实验。 图像文件panorama_0.png至panorama_628.png为在模拟器环境的等距网格上渲染得到的全景图像。 训练集与测试集的序列均通过从该网格中采样连续的图像-坐标对人工生成。 文件train_sequence.csv与test_sequence.csv分别包含对应数据集的图像文件名及配套坐标信息。