Abstract

We present a system for accurate real-time mapping of complex and arbitrary indoor scenes in variable lighting conditions, using only a moving low-cost depth camera and commodity graphics hardware. We fuse all of the depth data streamed from a Kinect sensor into a single global implicit surface model of the observed scene in real-time. The current sensor pose is simultaneously obtained by tracking the live depth frame relative to the global model using a coarse-to-fine iterative closest point (ICP) algorithm, which uses all of the observed depth data available. We demonstrate the advantages of tracking against the growing full surface model compared with frame-to-frame tracking, obtaining tracking and mapping results in constant time within room sized scenes with limited drift and high accuracy. We also show both qualitative and quantitative results relating to various aspects of our tracking and mapping system. Modelling of natural scenes, in real-time with only commodity sensor and GPU hardware, promises an exciting step forward in augmented reality (AR), in particular, it allows dense surfaces to be reconstructed in real-time, with a level of detail and robustness beyond any solution yet presented using passive computer vision.

Keywords

Computer scienceRobustness (evolution)Computer visionArtificial intelligenceFrame rateTracking (education)Fuse (electrical)GraphicsComputer graphicsAugmented realityTracking systemFrame (networking)Computer graphics (images)Kalman filterEngineering

Affiliated Institutions

Related Publications

A Survey of Augmented Reality

This paper surveys the field of augmented reality (AR), in which 3D virtual objects are integrated into a 3D real environment in real time. It describes the medical, manufacturi...

1997 PRESENCE Virtual and Augmented Reality 9373 citations

Publication Info

Year
2011
Type
article
Pages
127-136
Citations
3852
Access
Closed

External Links

Social Impact

Social media, news, blog, policy document mentions

Citation Metrics

3852
OpenAlex

Cite This

Richard A. Newcombe, Andrew Fitzgibbon, Shahram Izadi et al. (2011). KinectFusion: Real-time dense surface mapping and tracking. , 127-136. https://doi.org/10.1109/ismar.2011.6092378

Identifiers

DOI
10.1109/ismar.2011.6092378