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| Time | Program Item |
|---|---|
| 14:00 | Introduction |
| 14:05 | Invited Talk: Jose Neira: The Chimera of Robust Place Recognition In this talk I will discuss the history of the place recognition, or loop closing problem in SLAM. I will also present some of the most recent algorithms and results of our group in this field, and I will also explain why hoping for a fool-proof place recognition algorithm is a chimera, and SLAM systems should instead accommodate for possible failures in place recognition. |
| 14:35 | Niko Sünderhauf: TBADeep Learning for Place Recognition & What to do if Place Recognition Fails |
15:00 | Invited Talk: Jose M.M. Montiel: Visual Place recognition in ORBSLAM The talk focuses on the ORBSLAM a bag of words place recognizer built on DBoW2 with ORB. ORB are binary features invariant to rotation and scale, resulting in a very fast recognizer with good invariance to viewpoint. The system has been designed targeting a tight integration of the place recognition at the core the visual SLAM architecture. Thanks to this tight integration the system achieves a reliable relocation and loop closure capabilities that warrants the full system robust performance in realistic operational environments. |
| 15:30 | Coffee Break |
| 16:00 | Fei Han et al. – Life-Long Place Recognition by Shared Representative Appearance Learning |
| 16:15 | Muneeb Shahid, Tayyab Naseer, Wolfram Burgard – DTLC: Deeply Trained Loop Closure Detections for Lifelong Visual SLAM |
| 16:30 | Charbel Azzi et al. – Global Descriptors Reduce the Image-Based Localization Search Space |
| 16:45 | Stephanie Lowry and Henrik Andreasson – Visual place recognition techniques for pose estimation in changing environments |
| 17:00 | Concluding Remarks and Discussion |
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