Abstract
We propose a model-based camera pose estimation approach, which makes use of GPU-assisted analysis-by-synthesis methods on a very wide field of view (e.g. fish-eye) camera. After an initial registration, the synthesis part of the tracking is performed on graphics hardware, which simulates internal and external parameters of the camera, this way minimizing lens and perspective differences between a model view and a real camera image. We show how such a model is automatically created from a scene and analyze the sensitivity of the tracking to the model accuracy, in particular the case when we represent free-form surfaces by planar patches. We also examine accuracy and show on synthetic and on real data that the system does not suffer from drift accumulation. The wide field of view of the camera and the subdivision of our reference model into many textured free-form surfaces make the system robust against moving persons and other occlusions within the environment and provide a camera pose estimate in a fixed and known coordinate system.
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Koeser, K., Bartczak, B., Koch, R. (2007). An Analysis-by-Synthesis Camera Tracking Approach Based on Free-Form Surfaces. In: Hamprecht, F.A., Schnörr, C., Jähne, B. (eds) Pattern Recognition. DAGM 2007. Lecture Notes in Computer Science, vol 4713. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74936-3_13
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DOI: https://doi.org/10.1007/978-3-540-74936-3_13
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