Uneingeschränkter Zugang

The Process of Data Validation and Formatting for an Event-Based Vision Dataset in Agricultural Environments


Zitieren

[1] E. Mueggler, H. Rebecq, G. Gallego, T. Delbruck, and D. Scaramuzza, ‘The event-camera dataset and simulator: Event-based data for pose estimation, visual odometry, and SLAM,” International Journal of Robotics Research, vol. 36, no. 2, pp. 142–149, Feb. 2017. https://doi.org/10.1177/027836491769111510.1177/0278364917691115 Search in Google Scholar

[2] G. Gallego et al., “Event-based vision: A survey,” arXiv, pp. 1–30, Apr. 2019. https://doi.org/10.1109/tpami.2020.300841310.1109/TPAMI.2020.300841332750812 Search in Google Scholar

[3] D. Weikersdorfer, D. B. Adrian, D. Cremers, and J. Conradt, “Event-based 3D SLAM with a depth-augmented dynamic vision sensor,” in IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, Sep. 2014, pp. 359–364. https://doi.org/10.1109/ICRA.2014.690688210.1109/ICRA.2014.6906882 Search in Google Scholar

[4] A. Z. Zhu, D. Thakur, T. Özaslan, B. Pfrommer, V. Kumar, and K. Daniilidis, “The multivehicle stereo event camera dataset: An event camera dataset for 3D perception,” IEEE Robotics and Automation Letters, vol. 3, no. 3, pp. 2032–2039, Jul. 2018. https://doi.org/10.1109/LRA.2018.280079310.1109/LRA.2018.2800793 Search in Google Scholar

[5] A. Geiger, P. Lenz, C. Stiller, and R. Urtasun, “Vision meets robotics: The KITTI dataset,” International Journal of Robotics Research, vol. 32, no. 11, pp. 1231–1237, Aug. 2013. https://doi.org/10.1177/027836491349129710.1177/0278364913491297 Search in Google Scholar

[6] F. Barranco, C. Fermuller, Y. Aloimonos, and T. Delbruck, “A dataset for visual navigation with neuromorphic methods,” Frontiers in Neuroscience, vol. 10, pp. 1–9, Feb. 2016. https://doi.org/10.3389/fnins.2016.0004910.3389/fnins.2016.00049476308426941595 Search in Google Scholar

[7] J. Binas, D. Neil, S. C. Liu, and T. Delbruck, “DDD17: End-to-end DAVIS driving dataset,” arXiv Computer Vision and Pattern Recognition, pp. 1–9, Nov. 2017. Search in Google Scholar

[8] J. Wulff, D. J. Butler, G. B. Stanley, and M. J. Black, “Lessons and insights from creating a synthetic optical flow benchmark,” in Computer Vision – ECCV 2012. Workshops and Demonstrations. ECCV 2012 (Lecture Notes in Computer Science), A. Fusiello, V. Murino, R. Cucchiara, Eds. Springer, Berlin, Heidelberg, vol. 7584, 2012, pp. 168–177. https://doi.org/10.1007/978-3-642-33868-7_1710.1007/978-3-642-33868-7_17 Search in Google Scholar

[9] A. Zujevs, M. Pudzs, V. Osadcuks, A. Ardavs, M. Galauskis and J. Grundspenkis, “An Event-based vision dataset for visual navigation tasks in agricultural environments,” in 2021 IEEE International Conference on Robotics and Automation (ICRA), Xi’an, China, Oct. 2021, pp. 13769–13775. https://doi.org/10.1109/ICRA48506.2021.956174110.1109/ICRA48506.2021.9561741 Search in Google Scholar

[10] A. Zujevs, M. Pudzs, V. Osadcuks, A. Ardavs, M. Galauskis, and J. Grundspenkis, “Agri-EBV-autumn dataset,” 2021. [Online]. Available on: https://ieee-dataport.org/open-access/agri-ebv-autumn. Accessed on: Aug 20, 2021. Search in Google Scholar

[11] W. Hess, D. Kohler, H. Rapp, and D. Andor, “Real-time loop closure in 2D LIDAR SLAM,” in 2016 IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, June 2016, pp. 1271–1278. https://doi.org/10.1109/ICRA.2016.748725810.1109/ICRA.2016.7487258 Search in Google Scholar

[12] T. Toth, Z. Pusztai, and L. Hajder, “Automatic LiDAR-camera calibration of extrinsic parameters using a spherical target,” in 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France, 2020, pp. 8580–8586. https://doi.org/10.1109/ICRA40945.2020.919731610.1109/ICRA40945.2020.9197316 Search in Google Scholar

eISSN:
2255-8691
Sprache:
Englisch
Zeitrahmen der Veröffentlichung:
2 Hefte pro Jahr
Fachgebiete der Zeitschrift:
Informatik, Künstliche Intelligenz, Informationstechnik, Projektmanagement, Softwareentwicklung