Detecting spurious features using parity space

14 years 18 days ago
Detecting spurious features using parity space
—Detection of spurious features is instrumental in many computer vision applications. The standard approach is feature based, where extracted features are matched between the image frames. This approach requires only vision, but is computer intensive and not yet suitable for real-time applications. We propose an alternative based on algorithms from the statistical fault detection literature. It is based on image data and an inertial measurement unit (IMU). The principle of analytical redundancy is applied to batches of measurements from a sliding time window. The resulting algorithm is fast and scalable, and requires only feature positions as inputs from the computer vision system. It is also pointed out that the algorithm can be extended to also detect non-stationary features (moving targets for instance). The algorithm is applied to real data from an unmanned aerial vehicle in a navigation application.
David Törnqvist, Thomas B. Schön, Fredri
Added 30 May 2010
Updated 30 May 2010
Type Conference
Year 2008
Authors David Törnqvist, Thomas B. Schön, Fredrik Gustafsson
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