ATTENTION: This is a web archive! The IMS Group was split up in 2018 and does not exist anymore. Recent work of former members can be found at the VR/AR Group and the Computer Vision Group.

Interactive Media Systems, TU Wien

Large Scale Cut Plane: An Occlusion Management Technique for Immersive Dense 3D Reconstructions

By Annette Mossel and Christian Kößler

Abstract

Dense 3D reconstructions of real-world environments become wide spread and are foreseen to act as data base to solve real world problems, such as remote inspections. Therefore not only scene viewing is required but also the ability to interact with the environment, such as selection of a user-defined part of the reconstruction for later usage. However, inter-object occlusion is inherent to large dense 3D reconstructions, due to scene geometry or reconstruction artifacts that might result in object containment. Since prior art lacks approaches for occlusion management in environments that consist of one or multiple (large) continuous surfaces, we propose the novel technique Large Scale Cut Plane that enables segmentation and subsequent selection of visible, partly or fully occluded patches within a large 3D reconstruction, even at far distance. We combine Large Scale Cut Plane with an immersive virtual reality setup to foster 3D scene understanding and natural user interactions. We furthermore present results from a user study where we investigate performance and usability of our proposed technique compared to a baseline technique. Our results indicate Large Scale Cut Plane to be superior in terms of speed and precision, while we found need of improvement of the user interface. The presented investigations has to the authors´ best knowledge not been subject to previous research.

Reference

A. Mossel, C. Kößler: "Large Scale Cut Plane: An Occlusion Management Technique for Immersive Dense 3D Reconstructions"; in: "Proceedings of ACM Symposium on Virtual Reality Software and Technology (VRST)", ACM Symposium on Virtual Reality Software and Technology (VRST), 2016, ISBN: 978-1-4503-4491-3, 201 - 210.

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