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What is trackable?
| Content Provider | Semantic Scholar |
|---|---|
| Author | Cybenko, George Crespi, Valentino Jiang, Goufei |
| Copyright Year | 2006 |
| Abstract | We have developed a general framework, called a Process Query System (PQS), that serves as a foundation for formulating tracking problems, implementing software solutions to tracking problems and understanding theoretical issues related to tracking in specific scenarios. The PQS framework posits that an environment consists of multiple dynamical processes. Processes have states, state transitions (deterministic, nondeterministic or probabilistic) and observables related to state occupancy. Examples of such dynamical processes are nondeterministic automata, Hidden Markov Models and classical state space models. We define a tracking problem as the inverse problem of determining the processes and process states that explain a stream of observations. This paper describes a quantitative concept of trackability by considering the rate of growth of state sequences of a process model given a temporal sequence of observations. Recent formal results concerning this notion of trackability are summarized without proof. Complete proofs of the various results are contained in a technical report by the authors and cited in the bibliography. |
| File Format | PDF HTM / HTML |
| DOI | 10.1117/12.690628 |
| Alternate Webpage(s) | http://www.ists.dartmouth.edu/library/292.pdf |
| Alternate Webpage(s) | http://www.nec-labs.com/~gfj/cybenko-spie-06.pdf |
| Alternate Webpage(s) | https://doi.org/10.1117/12.690628 |
| Volume Number | 6201 |
| Journal | SPIE Defense + Commercial Sensing |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
