DocumentCode :
889561
Title :
Motion parameter estimation from global flow field data
Author :
Hummel, Robert ; Sundareswaran, V.
Author_Institution :
Dept. of Comput. Sci., New York Univ., NY, USA
Volume :
15
Issue :
5
fYear :
1993
fDate :
5/1/1993 12:00:00 AM
Firstpage :
459
Lastpage :
476
Abstract :
Presented are two methods for the determination of the parameters of motion of a sensor, given the vector flow field induced by an imaging system governed by a perspective transformation of a rigid scene. Both algorithms integrate global data to determine motion parameters. The first (the flow circulation algorithm) determines the rotational parameters. The second (the FOE search algorithm) determines the translational parameters of the motion independently of the first algorithm. Several methods for determining when the function has the appropriate form are suggested. One method involves filtering the function by a collection of circular-surround zero-mean receptive fields. The other methods project the function onto a linear space of quadratic polynomials and measures the distance between the two functions. The error function for the first two methods is a quadratic polynomial of the candidate position, yielding a very rapid search strategy
Keywords :
computer vision; filtering and prediction theory; motion estimation; parameter estimation; polynomials; FOE search; circular-surround zero-mean receptive fields; filtering; flow circulation algorithm; global flow field data; imaging system; motion parameter estimation; quadratic polynomials; rotational parameters; translational parameters; vector flow field; Computer science; Extraterrestrial measurements; Filtering; Focusing; Image sensors; Layout; Linear approximation; Parameter estimation; Polynomials; Sensor systems;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.211466
Filename :
211466
Link To Document :
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