Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

THIS WEBPAGE IS DEPRECATED - please visit our new website

K. Tateno, F. Tombari, N. Navab
Large Scale and Long Standing Simultaneous Reconstruction and Segmentation
Computer Vision and Image Understanding (CVIU), Volume 157, Pages 138-150, April, 2017.
The final publication is available at

This work proposes a method to segment a 3D point cloud of a scene while simultaneously reconstructing it via Simultaneous Localization And Mapping (SLAM). The proposed method incrementally merges segments obtained from each input depth image in an unified global model leveraging the camera pose estimated via SLAM. Differently from other approaches, our method is able to yield segmentation of scenes reconstructed from multiple views in real-time and with a complexity that does not depend on the size of the global model. Moreover, we endow our system with two additional contributions: a loop closure approach and a failure recovery and re-localization approach, both specifically designed so to enforce global consistency between merged segments, thus making our system suitable for large scale and long standing reconstruction and segmentation. We validate our proposal against the state of the art in terms of computational efficiency and accuracy on several benchmark datasets, as well as by showing how our method enables real-time reconstruction and segmentation of diverse real indoor environments.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each authors copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Edit | Attach | Refresh | Diffs | More | Revision r1.13 - 30 Jan 2019 - 15:16 - LeslieCasas

Lehrstuhl für Computer Aided Medical Procedures & Augmented Reality    rss.gif