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Predicting multiple target tracking performance for applications on video sequences
2017
Machine Vision and Applications
This dissertation presents a framework to predict the performance of multiple target tracking (MTT) techniques. The framework is based on the mathematical descriptors of point processes, the probability generating functional (p.g.fl). It is shown that conceptually the p.g.fls of MTT techniques can be interpreted as a transform that can be marginalized to an expression that encodes all the information regarding the likelihood model as well as the underlying assumptions present in a given
doi:10.1007/s00138-017-0840-8
fatcat:e3xxdfmqkrgdzngxgpelwemfzm