Abstract
Camera-based tracking systems which reconstruct a feature map with structure from motion or SLAM techniques highly depend on the ability to track a single feature in different scales, different lighting conditions and a wide range of viewing angles. The acquisition of high quality features is therefore indispensable for a continuous tracking of a feature with a maximum possible range of valid appearances.
We present a tracking system where not only the position of a feature but also its surface normal is reconstructed and used for precise prediction and tracking recovery of lost features. The appearance of a reference patch is also estimated sequentially and refined during the tracking, which leads to a more stable feature tracking step. Such reconstructed reference templates can be used for tracking a camera pose with a great variety of viewing positions.
This feature reconstruction process is combined with a feature management system, where a statistical analysis of the ability to track a feature is performed, and only the most stable features for a given camera viewing position are used for the 2D feature tracking step. This approach results in a map of high quality features, where the the real time capabilities can be preserved by only tracking the most necessary 2D feature points.
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Wuest, H., Wientapper, F., Stricker, D. (2008). Acquisition of High Quality Planar Patch Features. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2008. Lecture Notes in Computer Science, vol 5358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89639-5_51
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DOI: https://doi.org/10.1007/978-3-540-89639-5_51
Publisher Name: Springer, Berlin, Heidelberg
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