| LDR | | 00000nam u2200205 4500 |
| 001 | | 000000433317 |
| 005 | | 20200225140300 |
| 008 | | 200131s2019 ||||||||||||||||| ||eng d |
| 020 | |
▼a 9781085690911 |
| 035 | |
▼a (MiAaPQ)AAI22592334 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 004 |
| 100 | 1 |
▼a Moraffah, Bahman. |
| 245 | 10 |
▼a Bayesian Nonparametric Modeling and Inference for Multiple Object Tracking. |
| 260 | |
▼a [S.l.]:
▼b Arizona State University.,
▼c 2019. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2019. |
| 300 | |
▼a 180 p. |
| 500 | |
▼a Source: Dissertations Abstracts International, Volume: 81-03, Section: B. |
| 500 | |
▼a Advisor: Papandreou-Suppappola, Antonia. |
| 502 | 1 |
▼a Thesis (Ph.D.)--Arizona State University, 2019. |
| 506 | |
▼a This item must not be sold to any third party vendors. |
| 520 | |
▼a The problem of multiple object tracking seeks to jointly estimate the time-varying cardinality and trajectory of each object. There are numerous challenges that are encountered in tracking multiple objects including a time-varying number of measurements, under varying constraints, and environmental conditions. In this thesis, the proposed statistical methods integrate the use of physical-based models with Bayesian nonparametric methods to address the main challenges in a tracking problem. In particular, Bayesian nonparametric methods are exploited to efficiently and robustly infer object identity and learn time-dependent cardinality |
| 590 | |
▼a School code: 0010. |
| 650 | 4 |
▼a Electrical engineering. |
| 650 | 4 |
▼a Statistics. |
| 650 | 4 |
▼a Computer science. |
| 690 | |
▼a 0544 |
| 690 | |
▼a 0463 |
| 690 | |
▼a 0984 |
| 710 | 20 |
▼a Arizona State University.
▼b Electrical Engineering. |
| 773 | 0 |
▼t Dissertations Abstracts International
▼g 81-03B. |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0010 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2019 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15493238
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 202002
▼f 2020 |
| 990 | |
▼a ***1008102 |
| 991 | |
▼a E-BOOK |