#15:
K. Palaniappan,
M. Faisal,
C. Kambhamettu, and
A. F. Hasler
10th IEEE Int. Parallel Processing Symp.,
pgs. 864--872,
1996
Abstract,
Bibtex,
PlainText,
PDF,
DOI,
Google Scholar
The implementation of a parallel algorithmf o r estimating non-rigid motion vectors using a semi-$uid motion model applied to time-varying satellite imagery is described. De-
formable motion tracking of non-rigid biological objects and remotely sensed objects such as clouds, atmospheric aerosols and gases, polar sea ice, or ocean currents are important application domains f o r the Semi-fluid Motion Analysis (SMA)algorithm. Thefocus of this paper is on the parallelization of the SMA algorithmfor the MasPar MP-2 architecture. Implementation issues that were evaluated in order to make itfeasible to explore dense semi-jluid motion estimates of rapid-scan time-varying geostationary satel- lite imagery of clouds and weather pattems are described. Cloud motion vectorsfrom the SMA algorithm can be used toestimatethewind$eld thatwouldbeusefulinavariety of meteorological applications. Comparisons between the parallel and sequential implementations of the SMA algo-
rithm, and with manual results are briejly discussed.
@article{Palani:IPPS-1996,
author = "K. Palaniappan and M. Faisal and C. Kambhamettu and A. F. Hasler",
title = "Implementation of an automatic semi-fluid motion analysis algorithm on a massively parallel computer",
year = 1996,
journal = "10th IEEE Int. Parallel Processing Symp.",
pages = "864--872",
keywords = "motion, parallelization, stereo, cloud, big data, remote sensing",
doi = "10.1109/IPPS.1996.508193"
}
K. Palaniappan, M. Faisal, C. Kambhamettu, and A. F. Hasler. Implementation of an automatic semi-fluid motion analysis algorithm on a massively parallel computer. 10th IEEE Int. Parallel Processing Symp., pages 864--872, 1996.
