Inherent Ambiguities in Recovering 3-D Motion and Structure from a Noisy Flow Field
IEEE Transactions on Pattern Analysis and Machine Intelligence
Subspace methods for recovering rigid motion I: algorithm and implementation
International Journal of Computer Vision
The Frequency Structure of One-Dimensional Occluding Image Signals
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Optical navigation by the method of differences
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 2
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Previous methods for estimating the motion of an observerthrough a static scene require that image velocitiescan be measured. For the case of motion through a cluttered3D scene, however, measuring optical .ow is problematicbecause of the high density of depth discontinuities. Thispaper introduces a method for estimating motion through acluttered 3D scene that does not measure velocities at individualpoints. Instead the method measures a distributionof velocities over local image regions. We show that motionthrough a cluttered scene produces a bowtie pattern in thepower spectra of local image regions. We show how to estimatethe parameters of the bowtie for different image regionsand how to use these parameters to estimate observermotion. We demonstrate our method on synthetic and realdata sequences.