Scalable geometric hashing on MasPar machines
AA Khokhar, VK Prasanna… - Proceedings of IEEE …, 1993 - ieeexplore.ieee.org
AA Khokhar, VK Prasanna, HJ Kim
Proceedings of IEEE Conference on Computer Vision and Pattern …, 1993•ieeexplore.ieee.orgScalable data parallel algorithms for geometric hashing are presented. Implementations of
the proposed algorithms are performed on MasPar MP-1/MP-2. New parallel algorithms are
designed and mapped onto MP-1/MP-2. These techniques significantly improve upon the
number of processors employed while achieving superior time performance. The authors'
implementations run on a P processor machine, such that 1/spl les/P/spl les/S, where S is
the number of feature points in the scene. The results show that a probe of the recognition …
the proposed algorithms are performed on MasPar MP-1/MP-2. New parallel algorithms are
designed and mapped onto MP-1/MP-2. These techniques significantly improve upon the
number of processors employed while achieving superior time performance. The authors'
implementations run on a P processor machine, such that 1/spl les/P/spl les/S, where S is
the number of feature points in the scene. The results show that a probe of the recognition …
Scalable data parallel algorithms for geometric hashing are presented. Implementations of the proposed algorithms are performed on MasPar MP-1/MP-2. New parallel algorithms are designed and mapped onto MP-1/MP-2. These techniques significantly improve upon the number of processors employed while achieving superior time performance. The authors' implementations run on a P processor machine, such that 1/spl les/P/spl les/S, where S is the number of feature points in the scene. The results show that a probe of the recognition phase for a scene consisting of 1024 feature points takes less than 50 ms on a 1-K processor MP-1/MP-2.< >
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