Images of Peppercorns Transported on a Conveyor Belt - Recording 8

This data set comprises images of peppercorns 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 Georg Maier, Florian Pfaff, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden, Thomas Längle, Uwe D. Hanebeck, Jürgen Beyerer, Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking, 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. 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 Florian Pfaff, Marcus Baum, Benjamin Noack, Uwe D. Hanebeck, Robin Gruna, Thomas Längle, Jürgen Beyerer, TrackSort: Predictive Tracking for Sorting Uncooperative Bulk Materials, Proceedings of the 2015 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2015), San Diego, California, USA, September 2015. Florian Pfaff, Christoph Pieper, Georg Maier, Benjamin Noack, Robin Gruna, Harald Kruggel-Emden, Uwe D. Hanebeck, Siegmar Wirtz, Viktor Scherer, Thomas Längle, Jürgen Beyerer, Predictive Tracking with Improved Motion Models for Optical Belt Sorting, 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 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, Improving Material Characterization in Sensor-Based Sorting by Utilizing Motion Information, Proceedings of the 3rd Conference on Optical Characterization of Materials (OCM 2017), Karlsruhe, Germany, March 2017. 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, Motion-Based Material Characterization in Sensor-Based Sorting, tm – Technisches Messen, De Gruyter, October 2017. To this date, publications that used these data include Daniel Pollithy, Marcel Reith-Braun, Florian Pfaff, Uwe D. Hanebeck, Estimating Uncertainties of Recurrent Neural Networks in Application to Multitarget Tracking, 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. Acknowledgment 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胡椒粒图像。图像采集于小型光学带式分选机（Tablesort）。关于该系统的详细说明，可参阅Georg Maier、Florian Pfaff、Christoph Pieper、Robin Gruna、Benjamin Noack、Harald Kruggel-Emden、Thomas Längle、Uwe D. Hanebeck、Jürgen Beyerer发表于《IEEE工业电子学汇刊（Transactions on Industrial Electronics）》2020年2月刊的论文《Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking》。另可访问项目网站获取更多相关信息。

本数据集属于光学分选机录制的一批数据合集之一。如需检索该批次数据，请使用关键词"Tobias Hornberger"（需带引号）进行搜索，或通过链接https://doi.org/10.5281/zenodo.5506551 仅获取传送带相关数据集列表。

本次成像所用相机为Bonito CL-400C。外参校准图像为calibration_extrinsics.png，色彩校准图像为calibration_color.png。相关去拜耳（debayer）脚本可在GitHub平台获取。世界坐标系下，每个像素对应的实际尺寸约为0.056 mm，图像帧率为192.9 Hz。

本数据集可用于开发并评估两项核心挑战对应的算法：
1. 多目标跟踪（Multitarget Tracking）：用于预测颗粒运动的算法，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两篇论文：
- Florian Pfaff、Marcus Baum、Benjamin Noack、Uwe D. Hanebeck、Robin Gruna、Thomas Längle、Jürgen Beyerer发表于2015年9月美国加利福尼亚州圣地亚哥举办的2015 IEEE多传感器融合与智能系统国际会议（MFI 2015）的论文《TrackSort: Predictive Tracking for Sorting Uncooperative Bulk Materials》；
- Georg Maier、Florian Pfaff、Christoph Pieper、Benjamin Noack、Robin Gruna、Harald Kruggel-Emden、Uwe D. Hanebeck、Siegmar Wirtz、Viktor Scherer、Thomas Längle、Jürgen Beyerer发表于《Automatisierungstechnik》2020年4月刊的论文《Predictive Tracking with Improved Motion Models for Optical Belt Sorting》。
2. 颗粒分类任务：该任务可借助多目标跟踪器实时累积视觉特征，也可利用颗粒的轨迹信息完成分类。相关细节可参阅以下两篇论文：
- 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发表于2017年3月德国卡尔斯鲁厄举办的第三届材料光学表征会议（OCM 2017）的论文《Improving Material Characterization in Sensor-Based Sorting by Utilizing Motion Information》；
- 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发表于《tm – Technisches Messen》（De Gruyter出版）2017年10月刊的论文《Motion-Based Material Characterization in Sensor-Based Sorting》。

截至目前，已发表的使用本数据集的研究包括：Daniel Pollithy、Marcel Reith-Braun、Florian Pfaff、Uwe D. Hanebeck发表于2020年9月线上举办的2020 IEEE多传感器融合与智能系统国际会议（MFI 2020）的论文《Estimating Uncertainties of Recurrent Neural Networks in Application to Multitarget Tracking》。

已完成颗粒跟踪轨迹关联的CSV文件可通过链接https://doi.org/10.5281/zenodo.5506551 获取。

致谢
本研究得到德国工艺技术研究协会（Forschungs-Gesellschaft Verfahrens-Technik e.V.，GVT）的IGF项目20354 N资助，该项目由德国工业研究促进协会（AiF）通过工业共同体研究与发展（IGF）资助计划提供支持，资助方为德国联邦经济事务与能源部，资助依据为德国联邦议院决议。