Talks & Interviews from the Lab

What is the SIFT Algorithm ? | CLICK 3D EP. 17 | ft. Cyrill Stachniss

What is the SIFT Algorithm ? | CLICK 3D EP. 17 | ft. Cyrill Stachniss

Do you know what is the SIFT algorithm? The scale-invariant feature transform (SIFT) is a feature detection algorithm in computer vision to detect and describe local features in images. Applications include object recognition, robotic mapping and navigation, image stitching, 3D modeling, gesture recognition, video tracking, individual identification of wildlife and match moving. . Eugene Liscio from ai2- 3D talks with Cyrill Stachniss – about the SIFT algorithm. . Are you into Photogrammetry and 3D models? Watch these other videos for more tips! 5 Common Mistakes when photographing for photogrammetry https://youtu.be/SzobKDdghGo Can I use video to create 3D models? https://youtu.be/kT9BTdaTFPU Creating 3D model of footwear impressions https://youtu.be/miIq-oid_CM Virtual Reality uses for Forensics – ft. Alex Harvey from RiVR https://youtu.be/RIDvUm2li1I How to document a rapidly deteriorating crime scene? | Photogrammetry | Create Realistic 3D models https://youtu.be/ambB69DfmXE . Still haven’t subscribed to ForensicAnimations on YouTube? ►► https://www.youtube.com/user/Forensic… . Follow us on Instagram @ai2_3d Follow us on Linkedin https://www.linkedin.com/company/ai2_3d . #forensicscience #forensics #forensicfiles #forensic #photogrammetry #3dmodeling #vr #crimesceneinvestigator #csi #laserscanner #laserscanning

Talk by N. Chebrolu: Spatio-Temporal Registration of Plant Point Clouds for Pheno... (DIGICROP'2020)

Talk by N. Chebrolu: Spatio-Temporal Registration of Plant Point Clouds for Pheno… (DIGICROP’2020)

Keynote Talk by C. Stachniss on LiDAR-based SLAM using Geometry and Semantics ... (ITSC'20 SLAM-WS)

Keynote Talk by C. Stachniss on LiDAR-based SLAM using Geometry and Semantics … (ITSC’20 SLAM-WS)

Keynote Talk by C. Stachniss on LiDAR-based SLAM using Geometry and Semantics for Self-driving Cars given at the IEEE International Conference on Intelligent Transportation Systems SLAM Workshop, 2020

Nik Petrinic: Impact and Shock Mechanics Research for High-Performance Engineering Products

Nik Petrinic: Impact and Shock Mechanics Research for High-Performance Engineering Products

Talk by F. Magistri: Segmentation-Based 4D Registration of Plants Point Clouds (IROS'20)

Talk by F. Magistri: Segmentation-Based 4D Registration of Plants Point Clouds (IROS’20)

Paper: F. Magistri, N. Chebrolu, and C. Stachniss, “Segmentation-Based 4D Registration of Plants Point Clouds for Phenotyping,” in Proceedings of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), 2020. PDF: https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/magistri2020iros.pdf

Talk by D. Gogoll: Unsupervised Domain Adaptation for Transferring Plant Classification...(IROS'20)

Talk by D. Gogoll: Unsupervised Domain Adaptation for Transferring Plant Classification…(IROS’20)

D. Gogoll, P. Lottes, J. Weyler, N. Petrinic, and C. Stachniss, “Unsupervised Domain Adaptation for Transferring Plant Classification Systems to New Field Environments, Crops, and Robots,” in Proceedings of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), 2020. PAPER: https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/gogoll2020iros.pdf

Talk by J. Behley on Domain Transfer for Semantic Segmentation of LiDAR Data using DNNs... (IROS'20)

Talk by J. Behley on Domain Transfer for Semantic Segmentation of LiDAR Data using DNNs… (IROS’20)

F. Langer, A. Milioto, A. Haag, J. Behley, and C. Stachniss, “Domain Transfer for Semantic Segmentation of LiDAR Data using Deep Neural Networks,” in Proceedings of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), 2020. PDF: https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/langer2020iros.pdf

Talk by X. Chen on Learning an Overlap-based Observation Model for 3D LiDAR Localization (IROS'20)

Talk by X. Chen on Learning an Overlap-based Observation Model for 3D LiDAR Localization (IROS’20)

X. Chen, T. Läbe, L. Nardi, J. Behley, and C. Stachniss, “Learning an Overlap-based Observation Model for 3D LiDAR Localization,” in Proceedings of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), 2020. PAPER: https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/chen2020iros.pdf CODE: https://github.com/PRBonn/overlap_localization

Keynote Talk by C. Stachniss: Map-based Localization for Autonomous Driving (ECCV 2020 Workshops)

Keynote Talk by C. Stachniss: Map-based Localization for Autonomous Driving (ECCV 2020 Workshops)

Invited Talk by Cyrill Stachniss ECCV 2020 Workshop on Map-based Localization for Autonomous Driving https://sites.google.com/view/mlad-eccv2020

Talk by X. Chen on OverlapNet - Loop Closing for LiDAR-based SLAM (RSS'20)

Talk by X. Chen on OverlapNet – Loop Closing for LiDAR-based SLAM (RSS’20)

Talk for the RSS 2020 paper: X. Chen, T. Läbe, A. Milioto, T. Röhling, O. Vysotska, A. Haag, J. Behley, and C. Stachniss, “OverlapNet: Loop Closing for LiDAR-based SLAM,” in Proceedings of Robotics: Science and Systems (RSS), 2020. Paper: https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/chen2020rss.pdf Code available: https://github.com/PRBonn/OverlapNet

Keynote Talk by C. Stachniss: Robots in the Field - Towards Sustainable Crop Production (ICRA'20)

Keynote Talk by C. Stachniss: Robots in the Field – Towards Sustainable Crop Production (ICRA’20)

Robots in the Fields: Directions Towards Sustainable Crop Production ICRA 2020 Keynote Talk by Cyrill Stachniss International Conference on Robotics and Automation, Paris, 2020 Abstract: Food, feed, fiber, and fuel: Crop farming plays an essential role for the future of humanity and our planet. We heavily rely on agricultural production and at the same time, we need to reduce the footprint of agriculture production: less input of chemicals like herbicides and fertilizer and other limited resources. Simultaneously, the decline in arable land and climate change pose additional constraints like drought, heat, and other extreme weather events. Robots and other new technologies offer promising directions to tackle different management challenges in agricultural fields. To achieve this, autonomous field robots need the ability to perceive and model their environment, to predict possible future developments, and to make appropriate decisions in complex and changing situations. This talk will showcase recent developments towards robot-driven sustainable crop production. We will illustrate how certain management tasks can be automized using UAVs and UGVs and which new ways this technology offers. Among work conducted in collaborative European projects, the talk covers ongoing developments of the Cluster of Excellence “PhenoRob – Robotics and Phenotyping for Sustainable Crop Production” and some of our current exploitation activities.

Talk by N. Chebrolu on Spatio-Temporal Non-Rigid Registration of 3D Point Clouds of Plants (ICRA'20)

Talk by N. Chebrolu on Spatio-Temporal Non-Rigid Registration of 3D Point Clouds of Plants (ICRA’20)

ICRA 2020 talk about the paper: N. Chebrolu, T. Laebe, and C. Stachniss, “Spatio-Temporal Non-Rigid Registration of 3D Point Clouds of Plants,” in Proceedings of the IEEE Int. Conf. on Robotics & Automation (ICRA), 2020. https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/chebrolu2020icra.pdf

Talk by L. Nardi on Long-Term Robot Navigation in Indoor Environments... (ICRA'20)

Talk by L. Nardi on Long-Term Robot Navigation in Indoor Environments… (ICRA’20)

ICRA 2020 talk about the paper: L. Nardi and C. Stachniss, “Long-Term Robot Navigation in Indoor Environments Estimating Patterns in Traversability Changes,” in Proceedings of the IEEE Int. Conf. on Robotics & Automation (ICRA), 2020. PDF: https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/nardi2020icra.pdf Discussion Slack Channel: https://icra20.slack.com/app_redirect?channel=moa08_1

Talk by J. Quenzel on Beyond Photometric Consistency: Gradient-based Dissimilarity for VO (ICRA'20)

Talk by J. Quenzel on Beyond Photometric Consistency: Gradient-based Dissimilarity for VO (ICRA’20)

ICRA 2020 talk about the paper: J. Quenzel, R. A. Rosu, T. Laebe, C. Stachniss, and S. Behnke, “Beyond Photometric Consistency: Gradient-based Dissimilarity for Improving Visual Odometry and Stereo Matching,” in Proceedings of the IEEE Int. Conf. on Robotics & Automation (ICRA), 2020. PDF: http://www.ipb.uni-bonn.de/pdfs/quenzel2020icra.pdf

Talk by R. Sheikh on Gradient and Log-based Active Learning for Semantic Segmentation... (ICRA'20)

Talk by R. Sheikh on Gradient and Log-based Active Learning for Semantic Segmentation… (ICRA’20)

ICRA 2020 talk about the paper: R. Sheikh, A. Milioto, P. Lottes, C. Stachniss, M. Bennewitz, and T. Schultz, “Gradient and Log-based Active Learning for Semantic Segmentation of Crop and Weed for Agricultural Robots,” in Proceedings of the IEEE Int. Conf. on Robotics & Automation (ICRA), 2020. PDF: https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/sheikh2020icra.pdf

Talk by A. Ahmadi on Visual Servoing-based Navigation for Monitoring Row-Crop Fields (ICRA'20)

Talk by A. Ahmadi on Visual Servoing-based Navigation for Monitoring Row-Crop Fields (ICRA’20)

ICRA 2020 talk about the paper: A. Ahmadi, L. Nardi, N. Chebrolu, and C. Stachniss, “Visual Servoing-based Navigation for Monitoring Row-Crop Fields,” in Proceedings of the IEEE Int. Conf. on Robotics & Automation (ICRA), 2020. PDF: https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/ahmadi2020icra.pdf CODE: https://github.com/PRBonn/visual-crop-row-navigation