Abstract
More and more processing of visual information is nowadays done by computers, but the images captured by conventional cameras are still based on the pinhole principle inspired by our own eyes. This principle though is not necessarily the optimal image-formation principle for automated processing of visual information. Each camera samples the space of light rays according to some pattern. If we understand the structure of the space formed by the light rays passing through a volume of space, we can determine the camera, or in other words the sampling pattern of light rays, that is optimal with regard to a given task. In this work we analyze the differential structure of the space of time-varying light rays described by the plenoptic function and use this analysis to relate the rigid motion of an imaging device to the derivatives of the plenoptic function. The results can be used to define a hierarchy of camera models with respect to the structure from motion problem and formulate a linear, scene-independent estimation problem for the rigid motion of the sensor purely in terms of the captured images.
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Neumann, J., Fermüller, C. Plenoptic video geometry. Vis Comput 19, 395–404 (2003). https://doi.org/10.1007/s00371-003-0203-5
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DOI: https://doi.org/10.1007/s00371-003-0203-5