Matching point features with ordered geometric, rigidity, anddisparity constraints
Xiaoping Hu; Ahuja, N.
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Volume 16, Issue 10, Oct 1994 Page(s):1041 - 1049
Digital Object Identifier 10.1109/34.329004
Summary:This correspondence presents a matching algorithm for obtaining
feature point correspondences across images containing rigid objects
undergoing different motions. First point features are detected using
newly developed feature detectors. Then a variety of constraints are
applied starting with simplest and following with more informed ones.
First, an intensity-based matching algorithm is applied to the feature
points to obtain unique point correspondences. This is followed by the
application of a sequence of newly developed heuristic tests involving
geometry, rigidity, and disparity. The geometric tests match
two-dimensional geometrical relationships among the feature points, the
rigidity test enforces the three dimensional rigidity of the object, and
the disparity test ensures that no matched feature point in an image
could be rematched with another feature, if reassigned another disparity
value associated with another matched pair or an assumed match on the
epipolar line. The computational complexity is proportional to the
numbers of detected feature points in the two images. Experimental
results with indoor and outdoor images are presented, which show that
the algorithm yields only correct matches for scenes containing rigid
objects
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