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|Title:||Estimating vision parameters given data with covariances|
Van Den Hengel, A.
|Citation:||Proceedings of the 11th British Machine Vision Conference 2000: pp.182-191|
|Publisher:||ILES Central Press|
|Publisher Place:||Bristol, UK|
|Conference Name:||British Machine Vision Conference (11th : 2000 : Bristol, UK)|
|Wojciech Chojnacki, Michael J. Brooks, Anton van den Hengel and Darren Gawley|
|Abstract:||A new parameter estimation method is presented, applicable to many computer vision problems. It operates under the assumption that the data (typically image point locations) are accompanied by covariance matrices characterising data uncertainty. An MLE-based cost function is first formulated and a new minimisation scheme is then developed. Unlike Sampson’s method or the renormalisation technique of Kanatani, the new scheme has as its theoretical limit the true minimum of the cost function. It also has the advantages of being simply expressed, efficient, and unsurpassed in our comparative testing.|
|Rights:||Copyright status unknown|
|Appears in Collections:||Australian Institute for Machine Learning publications|
Computer Science publications
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