calibDB: enabling web based computer vision through on-the-fly camera calibration
This enables general deployment of computer vision algorithms on the web, addressing a bottleneck for developers and users lacking calibration data.
The paper tackles the problem of missing camera calibration data for web-based computer vision by proposing a web service that aggregates and enables on-the-fly calibration, allowing precise calibration in about 2 minutes for novice users.
For many computer vision applications, the availability of camera calibration data is crucial as overall quality heavily depends on it. While calibration data is available on some devices through Augmented Reality (AR) frameworks like ARCore and ARKit, for most cameras this information is not available. Therefore, we propose a web based calibration service that not only aggregates calibration data, but also allows calibrating new cameras on-the-fly. We build upon a novel camera calibration framework that enables even novice users to perform a precise camera calibration in about 2 minutes. This allows general deployment of computer vision algorithms on the web, which was previously not possible due to lack of calibration data.