Micro Focus Lcc

Entit Software LLC

David Collier

Pashmina Cameron

In some examples, a camera tracking failure in a simultaneous localization and mapping (SLAM) process with respect to a first SLAM map may be identified. Responsive to identification of the camera tracking failure, a second SLAM map for the SLAM process may be initialized. A video frame tracked through the second SLAM map may be accessed. Matched features between the video frame and individual keyframes of the first SLAM map may be identified to determine a keyframe subset. The keyframe subset may be analyzed to determine a candidate camera position from among the keyframe subset. The candidate camera position may be tracked with respect to the first SLAM map for subsequent video frames. The first SLAM map may be stitched to the second SLAM map responsive to tracking the candidate camera position with respect to the first SLAM map for the subsequent.

Stitching maps generated using simultaneous localization and mapping

Examples disclosed herein relate to detecting change in a 3-dimensional (3D) view. The examples enable determining a first set of sparse local features from a first set of frames of an initial 3D scene; determining whether the initial 3D scene is different from a current 3D scene based on the first set of sparse local features; and providing information about any determined differences between the initial 3D scene and the current 3D scene.

Growing community of inventors

Cambridge, United Kingdom

David Collier