Mathematics – Probability
Scientific paper
Jun 1996
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1996spie.2755..472z&link_type=abstract
Proc. SPIE Vol. 2755, p. 472-483, Signal Processing, Sensor Fusion, and Target Recognition V, Ivan Kadar; Vibeke Libby; Eds.
Mathematics
Probability
2
Scientific paper
Extracting satellite solar-array and main-body orientation vector information from optical imagery is an integral part of space object identification analysis. We describe a model-based image analysis system which automatically estimates the 3-D orientation vector of satellites by analyzing images obtained from ground-based optical telescopes. We adopt a two-step approach. First, pose estimates are derived from comparisons with a model database, and second, pose refinements are derived from photogrammetric information. The model database is formed by representing each available training image by a set of derived geometric primitives. To obtain fast access to the model database and to increase the probability of early successful matching, a novel indexing method is introduced. We present our preliminary results, evaluate the overall performance of the technique, and suggest improvements.
Ahalt Stanley C.
Stribling Bruce E.
Zhao Jun
No associations
LandOfFree
Three-dimensional orientation vector estimation from satellite imagery does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Three-dimensional orientation vector estimation from satellite imagery, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Three-dimensional orientation vector estimation from satellite imagery will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1304995