FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2104146079> ?p ?o ?g. }

• W2104146079 abstract "In multi-target tracking (MTT), we are often interested not only in finding the position of the multiple objects, but also allowing individual objects to be uniquely identified with the passage of time, by placing a label on each track. While there are many MTT algorithms that produce uniquely identified tracks as output, most of them make use of certain heuristics and/or unrealistic assumptions that makes the global result suboptimal of Bayesian sense. An innovative way of performing MTT is the so-called joint multi-target tracking, where the raw output of the algorithm, rather than being already the collection of output tracks, is a multi-target density calculated by approximating the Bayesian recursion that considers the entire system to have a single multidimensional state. The raw output, i.e. the calculated multi-target density, is thereafter processed to obtain output tracks to be displayed to the operator. This elegant approach, at least in theory, would allow us to precisely represent multi-target statistics. However, most joint MTT methods in the literature handle the problem of track in an ad-hoc, i.e. non-Bayesian manner. A number of methods, however, have suggested that the multi-target density, calculated using the Bayesian recursion, should contain information not only about the location of the individual objects but also their identities. This approach, that we refer as joint MTTL (joint multi-target tracking and labelling), looks intuitively advantageous. It would allow us, at least in theory, to obtain an output consisting of labelled tracks that is optimal in Bayesian sense. Moreover, it would allow us to have statistical information about the assigned labels; for instance, we would know what is the probability that track swap may have occurred after some approximation of targets (or, in simpler words, we would know how much we can believe that a target is what the display says that it is). However, the methods proposed in the still emerging joint MTTL literature do not address some problems that may considerably reduce the usefulness of the approach. These problems include: track coalescence after targets move closely to each other, gradual loss of ambiguity information when particle filters or multiple hypotheses approaches are used, and dealing with unknown/varying number of targets. As we are going to see, each of the previously proposed methods handles only a subset of these problems. Moreover, while obtaining a Bayes-optimal output of labelled tracks is one of the main motivations for joint MTTL, how such output should be obtained is a matter of debate. This work will tackle the joint MTTL problem together with a companion memorandum. In this work, we look at the problem from a theoretical perspective, i.e. we aim to provide an accurate and algorithm-independent picture of the aforementioned problems. An algorithm that actually handles these problems will be proposed in the companion memorandum. As one of the contributions of the memorandum, we clearly characterize the so-called labelling phenomenon that leads to track coalescence and other problems, and we verify that, unlike implied in previous literature, it is a physical phenomenon inherent of the MTTL problem rather than specific to a particular approach. We also show how mixed leads to nontrivial issues in practical implementations of joint MTTL. As another of the contributions of the memorandum, we propose a conceptual, algorithm-independent track extraction method for joint MTTL estimators, that gives an output with clear physical interpretation for the user." @default.
• W2104146079 created "2016-06-24" @default.
• W2104146079 creator A5044416381 @default.
• W2104146079 creator A5047401338 @default.
• W2104146079 creator A5053133223 @default.
• W2104146079 creator A5063795360 @default.
• W2104146079 date "2011-09-01" @default.
• W2104146079 modified "2023-09-23" @default.
• W2104146079 title "A theoretical analysis of Bayes-optimal multi-target tracking and labelling" @default.
• W2104146079 cites W1483647304 @default.
• W2104146079 cites W1578343189 @default.
• W2104146079 cites W1974828076 @default.
• W2104146079 cites W2014787937 @default.
• W2104146079 cites W2030200150 @default.
• W2104146079 cites W2061330004 @default.
• W2104146079 cites W2076526444 @default.
• W2104146079 cites W2101295974 @default.
• W2104146079 cites W2102547079 @default.
• W2104146079 cites W2103990233 @default.
• W2104146079 cites W2109255670 @default.
• W2104146079 cites W2115234167 @default.
• W2104146079 cites W2118906152 @default.
• W2104146079 cites W2126885789 @default.
• W2104146079 cites W2127976441 @default.
• W2104146079 cites W2149900846 @default.
• W2104146079 cites W2152830337 @default.
• W2104146079 cites W2166543177 @default.
• W2104146079 cites W2169178103 @default.
• W2104146079 cites W263076117 @default.
• W2104146079 cites W3143184696 @default.
• W2104146079 cites W3145294510 @default.
• W2104146079 cites W3150508362 @default.
• W2104146079 cites W3151841224 @default.
• W2104146079 cites W70609629 @default.
• W2104146079 cites W1561837455 @default.
• W2104146079 hasPublicationYear "2011" @default.
• W2104146079 type Work @default.
• W2104146079 sameAs 2104146079 @default.
• W2104146079 citedByCount "6" @default.
• W2104146079 countsByYear W21041460792012 @default.
• W2104146079 countsByYear W21041460792013 @default.
• W2104146079 countsByYear W21041460792014 @default.
• W2104146079 crossrefType "journal-article" @default.
• W2104146079 hasAuthorship W2104146079A5044416381 @default.
• W2104146079 hasAuthorship W2104146079A5047401338 @default.
• W2104146079 hasAuthorship W2104146079A5053133223 @default.
• W2104146079 hasAuthorship W2104146079A5063795360 @default.
• W2104146079 hasConcept C10138342 @default.
• W2104146079 hasConcept C107673813 @default.
• W2104146079 hasConcept C111919701 @default.
• W2104146079 hasConcept C11413529 @default.
• W2104146079 hasConcept C127705205 @default.
• W2104146079 hasConcept C153180895 @default.
• W2104146079 hasConcept C154945302 @default.
• W2104146079 hasConcept C15744967 @default.
• W2104146079 hasConcept C162324750 @default.
• W2104146079 hasConcept C168773036 @default.
• W2104146079 hasConcept C19417346 @default.
• W2104146079 hasConcept C198082294 @default.
• W2104146079 hasConcept C207201462 @default.
• W2104146079 hasConcept C2775936607 @default.
• W2104146079 hasConcept C41008148 @default.
• W2104146079 hasConceptScore W2104146079C10138342 @default.
• W2104146079 hasConceptScore W2104146079C107673813 @default.
• W2104146079 hasConceptScore W2104146079C111919701 @default.
• W2104146079 hasConceptScore W2104146079C11413529 @default.
• W2104146079 hasConceptScore W2104146079C127705205 @default.
• W2104146079 hasConceptScore W2104146079C153180895 @default.
• W2104146079 hasConceptScore W2104146079C154945302 @default.
• W2104146079 hasConceptScore W2104146079C15744967 @default.
• W2104146079 hasConceptScore W2104146079C162324750 @default.
• W2104146079 hasConceptScore W2104146079C168773036 @default.
• W2104146079 hasConceptScore W2104146079C19417346 @default.
• W2104146079 hasConceptScore W2104146079C198082294 @default.
• W2104146079 hasConceptScore W2104146079C207201462 @default.
• W2104146079 hasConceptScore W2104146079C2775936607 @default.
• W2104146079 hasConceptScore W2104146079C41008148 @default.
• W2104146079 hasIssue "1953" @default.
• W2104146079 hasLocation W21041460791 @default.
• W2104146079 hasOpenAccess W2104146079 @default.
• W2104146079 hasPrimaryLocation W21041460791 @default.
• W2104146079 hasRelatedWork W1533114612 @default.
• W2104146079 hasRelatedWork W1533869576 @default.
• W2104146079 hasRelatedWork W166194254 @default.
• W2104146079 hasRelatedWork W1803592988 @default.
• W2104146079 hasRelatedWork W1822246767 @default.
• W2104146079 hasRelatedWork W1985553337 @default.
• W2104146079 hasRelatedWork W1990884907 @default.
• W2104146079 hasRelatedWork W2051354142 @default.
• W2104146079 hasRelatedWork W2061175976 @default.
• W2104146079 hasRelatedWork W2069850933 @default.
• W2104146079 hasRelatedWork W2126885789 @default.
• W2104146079 hasRelatedWork W2170626353 @default.
• W2104146079 hasRelatedWork W2185524340 @default.
• W2104146079 hasRelatedWork W2586793347 @default.
• W2104146079 hasRelatedWork W2765240552 @default.
• W2104146079 hasRelatedWork W2806381151 @default.
• W2104146079 hasRelatedWork W2949687433 @default.
• W2104146079 hasRelatedWork W3143184696 @default.
• W2104146079 hasRelatedWork W34992941 @default.

• next