Abstract
Camera phones are a promising platform for hand-held augmented reality. As their computational resources grow, they are becoming increasingly suitable for visual tracking tasks. At the same time, they still offer considerable challenges: Their cameras offer a narrow field-of-view not best suitable for robust tracking; images are often received at less than 15 Hz; long exposure times result in significant motion blur; and finally, a rolling shutter causes severe smearing effects. This paper describes an attempt to implement a keyframe-based SLAMsystem on a camera phone (specifically, the Apple iPhone 3 G). We describe a series of adaptations to the Parallel Tracking and Mapping system to mitigate the impact of the device's imaging deficiencies. Early results demonstrate a system capable of generating and augmenting small maps, albeit with reduced accuracy and robustness compared to SLAM on a PC.
Keywords
Computer scienceRobustness (evolution)Computer visionCamera phoneArtificial intelligenceTracking (education)PhoneShutterSingle cameraField of viewTracking systemMotion blurAugmented realityComputer graphics (images)Kalman filterImage (mathematics)Engineering
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Publication Info
- Year
- 2009
- Type
- article
- Citations
- 518
- Access
- Closed
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Cite This
Georg Klein,
David W. Murray
(2009).
Parallel Tracking and Mapping on a camera phone.
.
https://doi.org/10.1109/ismar.2009.5336495
Identifiers
- DOI
- 10.1109/ismar.2009.5336495