Images of Balls Transported on a Conveyor Belt - Recording 9
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This data set comprises images of balls on a conveyor belt. 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 or use the list at https://doi.org/10.5281/zenodo.5506551 (conveyor belt data sets only). 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> Each pixel is approximately 0.056 mm long in world coordinates. 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. <br> To this date, publications that used these data include <em>Daniel Pollithy, Marcel Reith-Braun, Florian Pfaff, Uwe D. Hanebeck,</em><br> <strong>Estimating Uncertainties of Recurrent Neural Networks in Application to Multitarget Tracking</strong>,<br> Proceedings of the 2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2020), Virtual, September 2020. CSV-files with already associated particle tracks are available at https://doi.org/10.5281/zenodo.5506551. <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.
本数据集包含传送带上的球体图像。该系列图像由小型光学带式分选机Tablesort采集得到。关于Tablesort系统的详细说明可参阅文献：<em>Georg Maier、Florian Pfaff、Christoph Pieper、Robin Gruna、Benjamin Noack、Harald Kruggel-Emden、Thomas Längle、Uwe D. Hanebeck、Jürgen Beyerer</em>，<strong>《一种集成预测性实时多目标跟踪（Multiobject Tracking）的新型传感器分选方法的实验评估》</strong>，《IEEE工业电子学汇刊》，2020年2月。另可参阅项目官网。 本数据集属于光学分选机采集的一批录制数据之一。可通过搜索关键词“Tobias Hornberger”（需带引号）检索相关数据，或访问https://doi.org/10.5281/zenodo.5506551获取仅包含传送带数据集的列表。 本次采集使用的相机为Bonito CL-400C。外参标定图像可于calibration_extrinsics.png中获取，色彩标定图像则对应calibration_color.png。GitHub平台提供了去拜耳化（debayer）脚本，详见相关页面。 在世界坐标系下，每个像素对应实际长度约0.056 mm。图像帧率为192.9 Hz。 本数据集可用于开发并评估两类核心算法挑战：一是用于预测颗粒运动的多目标跟踪（Multitarget Tracking）算法，该算法可用于提升光学分选机的分选性能。相关细节可参阅以下文献： <em>Florian Pfaff、Marcus Baum、Benjamin Noack、Uwe D. Hanebeck、Robin Gruna、Thomas Längle、Jürgen Beyerer</em>，<strong>《TrackSort：面向非合作散装物料分选的预测性跟踪》</strong>，收录于《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>，<strong>《面向光学带式分选的改进运动模型预测性跟踪》</strong>，《Automatisierungstechnik》，2020年4月。 二是颗粒分类任务：可通过多目标跟踪器随时间累积视觉特征完成分类，也可利用颗粒轨迹信息实现分类。相关研究可参阅以下文献： <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>，<strong>《利用运动信息提升传感器分选系统中的物料表征精度》</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>，<strong>《传感器分选系统中基于运动信息的物料表征》</strong>，《tm – Technisches Messen》（De Gruyter出版），2017年10月。 截至目前，使用本数据集的已发表文献包括：<em>Daniel Pollithy、Marcel Reith-Braun、Florian Pfaff、Uwe D. Hanebeck</em>，<strong>《循环神经网络在多目标跟踪任务中的不确定性估计》</strong>，收录于《2020年IEEE多传感器融合与智能系统国际会议（MFI 2020）论文集》，虚拟会议，2020年9月。已完成轨迹关联的颗粒跟踪CSV文件可于https://doi.org/10.5281/zenodo.5506551获取。 <strong>致谢</strong> 本研究依托德国加工技术研究协会（Forschungs-Gesellschaft Verfahrens-Technik e.V.，简称GVT）的IGF项目20354 N开展，该项目由德国联邦经济事务与能源部通过AiF工业社区研究与发展促进计划（IGF计划）资助，资助依据为德国联邦议院决议。
