资源论文Determining Motion Directly from Normal Flowsupon the use of a Spherical Eye Platform

Determining Motion Directly from Normal Flowsupon the use of a Spherical Eye Platform

2019-11-28 | |  89 |   54 |   0

Abstract We address the problem of recovering camera motion from video data, which does not require the establishment of feature correspondences or computation of optical flflows but from normal flflows directly. We have designed an imaging system that has a wide fifield of view by fifixating a number of cameras together to form an approximate spherical eye. With a substantially widened visual fifield, we discover that estimating the directions of translation and rotation components of the motion separately are possible and particularly effificient. In addition, the inherent ambiguities between translation and rotation also disappear. Magnitude of rotation is recovered subsequently. Experimental results on synthetic and real image data are provided. The results show that not only the accuracy of motion estimation is comparable to those of the state-of-the-art methods that require explicit feature correspondences or optical flflows, but also a faster computation time

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