Towards Semantic KinectFusion

  • Nicola Fioraio
  • Gregorio Cerri
  • Luigi Di Stefano
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8157)

Abstract

In this paper we propose an extension to the KinectFusion approach which enables both SLAM-graph optimization, usually required on large looping routes, as well as discovery of semantic information in the form of object detection and localization. Global optimization is achieved by incorporating the notion of keyframe into a KinectFusion-style approach, thus providing the system with the ability to explore large environments and maintain a globally consistent map. Moreover, we integrate into the system our recent object detection approach based on a new Semantic Bundle Adjustment paradigm, thereby achieving joint detection, tracking and mapping. Although our current implementation is not optimized for real-time operation, the principles and ideas set forth in this paper can be considered a relevant contribution towards a Semantic KinectFusion system.

Keywords

KinectFusion semantic SLAM semantic bundle adjustment object detection 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Nicola Fioraio
    • 1
  • Gregorio Cerri
    • 1
  • Luigi Di Stefano
    • 1
  1. 1.Dept. of Computer Science and EngineeringUniversity of BolognaBolognaItaly

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