Abstract
A method to estimate complex objects is to aggregate local estimates of object fragments. Given uncertainties and ambiguities in the interpretation of these locally estimated fragments, it is usually necessary to maintain multiple hypotheses about fragment aggregates. This introduces redundancies in the representation of each object which can increase exponentially with the size of the objects. A simple procedure to prune redundancies is proposed and analyzed for the problem of estimating objects which can be decomposed into linearly ordered sets of parts.
Research supported by MURI grant DAAH04-96-1-0445, Foundations of Performance Metrics for Object Recognition and NSF grant ECS-9873451.
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Casadei, S. (2000). Redundancy Elimination in the Estimation of Multiple Paths. In: Djaferis, T.E., Schick, I.C. (eds) System Theory. The Springer International Series in Engineering and Computer Science, vol 518. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5223-9_14
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DOI: https://doi.org/10.1007/978-1-4615-5223-9_14
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