Objektsensitive Verfolgung und Klassifikation von Fußgängern mit verteilten Multi-Sensor-Trägern
State estimation of an unknown number of objects remains a challenging topic - despite the existence of theoretically bayes-optimal multi-object-filters - due to numerous assumptions in the modeling process. This thesis evaluates such filters in real multi-object-multi-sensor scenarios and proposes...
Saved in:
| Superior document: | Forschungsberichte aus der Industriellen Informationstechnik / Institut für Industrielle Informationstechnik (IIIT), Karlsruher Institut für Technologie |
|---|---|
| : | |
| Year of Publication: | 2016 |
| Language: | German |
| Series: | Forschungsberichte aus der Industriellen Informationstechnik / Institut für Industrielle Informationstechnik (IIIT), Karlsruher Institut für Technologie
|
| Physical Description: | 1 electronic resource (XI, 178 p. p.) |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| LEADER | 01729nam-a2200373z--4500 | ||
|---|---|---|---|
| 001 | 993548287904498 | ||
| 005 | 20231214141121.0 | ||
| 006 | m o d | ||
| 007 | cr|mn|---annan | ||
| 008 | 202102s2016 xx |||||o ||| 0|ger d | ||
| 035 | |a (CKB)4920000000100814 | ||
| 035 | |a (oapen)https://directory.doabooks.org/handle/20.500.12854/55091 | ||
| 035 | |a (EXLCZ)994920000000100814 | ||
| 041 | 0 | |a deu | |
| 100 | 1 | |a Pallauf, Johannes |4 auth | |
| 245 | 1 | 0 | |a Objektsensitive Verfolgung und Klassifikation von Fußgängern mit verteilten Multi-Sensor-Trägern |
| 260 | |b KIT Scientific Publishing |c 2016 | ||
| 300 | |a 1 electronic resource (XI, 178 p. p.) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Forschungsberichte aus der Industriellen Informationstechnik / Institut für Industrielle Informationstechnik (IIIT), Karlsruher Institut für Technologie | |
| 520 | |a State estimation of an unknown number of objects remains a challenging topic - despite the existence of theoretically bayes-optimal multi-object-filters - due to numerous assumptions in the modeling process. This thesis evaluates such filters in real multi-object-multi-sensor scenarios and proposes necessary extensions to existing models. The main application of the thesis is indoor pedestrian tracking. | ||
| 546 | |a German | ||
| 653 | |a Multi-Objekt-Verfolgung | ||
| 653 | |a verteilte Systeme | ||
| 653 | |a SensorenMulti-object-tracking | ||
| 653 | |a sensors | ||
| 653 | |a Objektklassifikation | ||
| 653 | |a object classification | ||
| 653 | |a pedestrian tracking | ||
| 653 | |a distributed systems | ||
| 653 | |a Personenverfolgung | ||
| 776 | |z 3-7315-0529-0 | ||
| 906 | |a BOOK | ||
| ADM | |b 2023-12-15 06:04:46 Europe/Vienna |f system |c marc21 |a 2019-11-10 04:18:40 Europe/Vienna |g false | ||
| AVE | |i DOAB Directory of Open Access Books |P DOAB Directory of Open Access Books |x https://eu02.alma.exlibrisgroup.com/view/uresolver/43ACC_OEAW/openurl?u.ignore_date_coverage=true&portfolio_pid=5338768950004498&Force_direct=true |Z 5338768950004498 |b Available |8 5338768950004498 | ||