ICRA 2020 Workshop on Sensing, Estimating and Understanding the Dynamic World - Call For Papers
Date: 31 May, 2020. Location: Paris, France. Website: https://robotics.sydney.edu.au/?page_id=322 Submission Deadline: 29 March, 2020 Author Notification: 26 April, 2020 Camera-ready paper: 3 May, 2020 LaTeX template: Download Zip <https://robotics.sydney.edu.au/wp-content/uploads/2020/02/RAS-Workshop-Resources_W2020.zip> Submission link: https://cmt3.research.microsoft.com/DynamicSLAM2020 Objective: Dynamic scenes extend and challenge a number of mature research areas in Robotics and Computer Vision, including simultaneous localization and mapping (SLAM), structure from motion (SFM), visual odometry (VO), multiple object detection and tracking, etc. Most of the existing solutions to these problems rely heavily on assumptions about the static nature of the environment. This drastically reduces the amount of information that can be obtained in complex environments cluttered with moving objects and may cause the techniques to fail. It also removes important relationships between moving sensors and objects, such as obstacle avoidance in robotics and intelligent transportation. This workshop seeks to motivate and investigate approaches designed for dynamic environments. It will do so by drawing on expertise in both the robotics and computer vision communities to highlight the challenges of dynamic scenes, the existing capabilities and limitations of sensor modalities and computational techniques, and discussing potential ways forward towards developing algorithms to map, estimate, and understand the dynamic world. Speakers: - Wolfram Burgard (University of Freiburg, Toyota Research Institute) - Lourdes Agapito (University College London) - Luca Carlone (MIT) - Cesar Cadena (ETH Zurich) - Daniel Cremers (Technische Universität München) - Ruigang Yang (Baidu Research) - Matia Pizzoli (Oculus) - Davide Migliore (Prophesee) - Jonathan Gammell Call for papers and demos: We encourage researchers as well as companies to contribute to the workshop. Contributions are solicited in, but not limited to, the following topics: - Sensing the dynamic scene - Dynamic scene representation - Scene flow - Multi-body SLAM - Multi-motion visual odometry - Multiple object tracking (MOT) - Multi-body structure from motion - Multi-target tracking - Background / foreground segmentation - Motion detection - Motion segmentation - Motion prediction and planning primitives - Datasets in dynamic environments We invite the attendees of this workshop to submit short papers explaining their current work or developed systems in the above-mentioned topics. *Contributions in the form of live demonstrations are also welcome*. The recommended length of the contribution is 2 pages (maximum 6 pages), and it must follow the provided RAS LaTeX template: (LINK <https://robotics.sydney.edu.au/wp-content/uploads/2020/02/RAS-Workshop-Resources_W2020.zip>). Authors are encouraged to submit a supporting video clip. Submissions will be selected based on their originality, relevance to the workshop topics, contributions, technical clarity, and presentation. Accepted papers will be presented in an interactive poster session during the workshop and will be posted on the workshop website. Please submit your manuscripts at this link <https://cmt3.research.microsoft.com/DynamicSLAM2020>. For any queries regarding the workshop, please send an email to dynamic.slam.works...@gmail.com A detailed overview of the workshop program can be found here <https://robotics.sydney.edu.au/?page_id=322>. Program Committee - Teresa Vidal (University of Technology Sydney) - Donald Dansereau (The University of Sydney) - Ravi Garg (University of Adelaide) - Laurent Kneip (Shanghai Tech) - Mina Henein (Australian National University) - Kevin Judd (University of Oxford) Thank you. Best regards, Organizers Viorela Ila (The University of Sydney) Jonathan Gammell (University of Oxford) Sundara Tejaswi Digumarti (The University of Sydney) Tat Jun Chin (University of Adelaide) Guillermo Gallego (Technische Universität Berlin)
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