Associated Raw Data To The Publication: An Accurate And Efficient Camera-Based Indoor Positioning Approach For Intralogistic Environments (Mhcl 2015)

This is a test data set for marker-based augmented reality algorithms used to locate ground conveyors in an industrial environment. It was recorded in the testing area of the chair fml at TUM to develop and evaluate algorithms for locating forklift trucks in the publication "An accurate and efficient camera-based indoor positioning approach for intralogistic environments" at MHCL 2015 conference (see https://mediatum.ub.tum.de/1286589 and http://www.fml.mw.tum.de/fml/images/Publikationen/MHCL_2015_jung_submitted.pdf). Originally these files were recorded and used as uncompressed 8-bit grayscale bitmaps. The images were losslessly compressed to png files in order to reduce the test set file size (by approx. factor 3.5)本数据集为基于标记物的增强现实（augmented reality）算法测试集，用于在工业环境中定位地面输送机。数据集采集自慕尼黑工业大学（TUM）FML研究室的测试区域，旨在开发并评估用于叉车定位的算法，相关研究成果发表于2015年MHCL会议的论文《An accurate and efficient camera-based indoor positioning approach for intralogistic environments》（详情可访问：https://mediatum.ub.tum.de/1286589 与 http://www.fml.mw.tum.de/fml/images/Publikationen/MHCL_2015_jung_submitted.pdf）。原始数据文件采用未压缩的8位灰度位图格式存储，为缩减测试集文件体积（压缩比约为3.5倍），已将所有图像无损压缩为PNG格式文件。