Images of Thin Cuboids Transported on a Chute - Recording 4

This data set comprises images of thin cuboids on a chute. The images were recorded on the small-scale optical belt sorter Tablesort. A thorough description of the Tablesort system can be found in <em>Georg Maier, Florian Pfaff, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden, Thomas Längle, Uwe D. Hanebeck, Jürgen Beyerer,</em> <strong>Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking</strong>, Transactions on Industrial Electronics, February 2020. See also the project website. This dataset is part of a batch of recordings on optical sorters. Please use the search function with the keyword "Tobias Hornberger" (in quotes) to find them. The camera was recorded on a Bonito CL-400C. The calibration image for the extrinsic parameters can be found in calibration_extrinsics.png for the extrinsics and calibration_color.png for the color calibration. Please see the debayer script on GitHub<strong>.</strong> The frame rate is 192.9 Hz. Algorithms for two key challenges can be developed and evaluated on the data sets: Multitarget tracking for predicting the particle’s motion. This can be used to enhance the separation of optical sorters. For further details on this, see the publications <em>Florian Pfaff, Marcus Baum, Benjamin Noack, Uwe D. Hanebeck, Robin Gruna, Thomas Längle, Jürgen Beyerer,</em><br> <strong>TrackSort: Predictive Tracking for Sorting Uncooperative Bulk Materials,</strong><br> Proceedings of the 2015 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2015), San Diego, California, USA, September 2015. <em>Florian Pfaff, Christoph Pieper, Georg Maier, Benjamin Noack, Robin Gruna, Harald Kruggel-Emden, Uwe D. Hanebeck, Siegmar Wirtz, Viktor Scherer, Thomas Längle, Jürgen Beyerer,</em><br> <strong>Predictive Tracking with Improved Motion Models for Optical Belt Sorting</strong>,<br> at – Automatisierungstechnik, April 2020. Classification of particles. The classification may use a multitarget tracker to accumulate visual features over time. One can also use the information on the trajectory to classify the particles. For information on this, refer to <em>Georg Maier, Florian Pfaff, Florian Becker, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden, Thomas Längle, Uwe D. Hanebeck, Siegmar Wirtz, Viktor Scherer, Jürgen Beyerer,</em><br> <strong>Improving Material Characterization in Sensor-Based Sorting by Utilizing Motion Information,</strong><br> Proceedings of the 3rd Conference on Optical Characterization of Materials (OCM 2017), Karlsruhe, Germany, March 2017. <em>Georg Maier, Florian Pfaff, Florian Becker, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden, Thomas Längle, Uwe D. Hanebeck, Siegmar Wirtz, Viktor Scherer, Jürgen Beyerer,</em><br> <strong>Motion-Based Material Characterization in Sensor-Based Sorting,</strong> <br> tm – Technisches Messen, De Gruyter, October 2017. <strong>Acknowledgment</strong> The IGF project 20354 N of the research association Forschungs-Gesellschaft Verfahrens-Technik e.V. (GVT) was supported via the AiF in a program to promote the Industrial Community Research and Development (IGF) by the Federal Ministry for Economic Affairs and Energy on the basis of a resolution of the German Bundestag.本数据集包含滑槽上细长长方体工件的图像。这些图像采集自小型光学带式分选机Tablesort（Tablesort）。关于Tablesort系统的详细说明可参见论文<em>Georg Maier, Florian Pfaff, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden, Thomas Längle, Uwe D. Hanebeck, Jürgen Beyerer,</em> <strong>《新型基于传感器的分选方法的实验评估：集成预测式实时多目标跟踪》</strong>，《IEEE工业电子学报》，2020年2月。亦可参考该项目的官方网站。 本数据集属于光学分选机录制的一批数据之一。请使用搜索功能，以带引号的关键词"Tobias Hornberger"检索以获取相关数据。图像采集设备为Bonito CL-400C相机。外参校准图像可参考calibration_extrinsics.png，色彩校准图像可参考calibration_color.png。相关的去拜耳化脚本可在GitHub上获取<strong>.</strong> 图像帧率为192.9 Hz。 本数据集可用于开发并评估两项关键挑战的算法： 1. 用于预测工件运动的多目标跟踪。该技术可用于提升光学分选机的分选性能。相关细节可参见以下论文： <em>Florian Pfaff, Marcus Baum, Benjamin Noack, Uwe D. Hanebeck, Robin Gruna, Thomas Längle, Jürgen Beyerer,</em><br> <strong>《TrackSort：面向非合作散装物料分选的预测式跟踪》</strong>，2015年IEEE多传感器融合与智能系统国际会议（MFI 2015）论文集，美国加利福尼亚州圣地亚哥，2015年9月。 <em>Florian Pfaff, Christoph Pieper, Georg Maier, Benjamin Noack, Robin Gruna, Harald Kruggel-Emden, Uwe D. Hanebeck, Siegmar Wirtz, Viktor Scherer, Thomas Längle, Jürgen Beyerer,</em><br> <strong>《面向光学带式分选的改进运动模型预测式跟踪》</strong>，《自动化技术》，2020年4月。 2. 工件分类。该分类任务可借助多目标跟踪器实时累积视觉特征，亦可利用工件轨迹信息完成分类。相关细节可参见以下论文： <em>Georg Maier, Florian Pfaff, Florian Becker, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden, Thomas Längle, Uwe D. Hanebeck, Siegmar Wirtz, Viktor Scherer, Jürgen Beyerer,</em><br> <strong>《利用运动信息提升基于传感器分选的材料表征精度》</strong>，第三届材料光学表征会议（OCM 2017）论文集，德国卡尔斯鲁厄，2017年3月。 <em>Georg Maier, Florian Pfaff, Florian Becker, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden, Thomas Längle, Uwe D. Hanebeck, Siegmar Wirtz, Viktor Scherer, Jürgen Beyerer,</em><br> <strong>《基于传感器分选的运动式材料表征》</strong>，《tm——技术测量》，De Gruyter出版社，2017年10月。 <strong>致谢</strong> 本IGF项目20354 N由德国加工技术研究协会（Forschungs-Gesellschaft Verfahrens-Technik e.V., GVT）发起，经由工业研究促进协会（AiF）依托德国联邦经济事务与能源部的工业共同体研究与发展（IGF）资助计划提供支持，资助依据为德国联邦议院的相关决议。