Pii: 0262-8856(91)90043-o
نویسندگان
چکیده
M5tion estinlati~n is a very impQriant problem irl dynamic scene attatysis. Although it is easier to estimate motion ~ararneters frown 3D data than from 21) images, it is not trivial~ sauce the 3D data we have are almost always corrupted by noise, A comparative study on motion estimation from 3D line segments is presented. Two representations of Ike segments and two representations o~rotat~on are ~e~~~~~~~~ f?rirh ~~~~~~~~ represenratioas of fine segments apld rotaf~o~, a ~~~~~ber of methods for rnot~o~ estimation are ~re.~e~ied~ ~~~~ud~ng the extended Kalman filter, a genera/ minimization process and the singular value decomposition. These methods are compared using both synthetic and real data obtained by a trinocular stereo. It is observed that the extended Kalman filter with the rotation axis representation of rotat~o~l is preferable_ Note that a@ ~~ethods d~s&~sed cafa be directly a~~~~ed to 30 point data.
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Feature-based correspondence: an eigenvector approach
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