A vision-based algorithm for parking lot utilization evaluation using conditional random fields

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F13%3A86088427" target="_blank" >RIV/61989100:27240/13:86088427 - isvavai.cz</a>

Výsledek na webu

<a href="http://link.springer.com/chapter/10.1007%2F978-3-642-41939-3_22" target="_blank" >http://link.springer.com/chapter/10.1007%2F978-3-642-41939-3_22</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-642-41939-3_22" target="_blank" >10.1007/978-3-642-41939-3_22</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A vision-based algorithm for parking lot utilization evaluation using conditional random fields

Popis výsledku v původním jazyce

In this paper, we present an algorithm for estimating the occupancy of individual parking spaces. Our method is based on a computer analysis of images obtained by a camera system monitoring the activities on a parking lot. The proposed method extensivelyuses a priori information about the parking lot layout and the general shape of well-parked cars, which is incorporated in a simplified probabilistic car model. Discriminative features are extracted from a normalized image of every parking space, the relevance of these gradient-based features is prioritized via a selective flow, and furthermore, their spatial relationship is revealed through an undirected graphical model. We strive to avoid the training phase to reduce the time required to bring the system into a fully operational state. The reliability of the here devised approach is evaluated on the set of video sequences captured during different phases of a day and the results are compared against the ground truth data.

Název v anglickém jazyce

A vision-based algorithm for parking lot utilization evaluation using conditional random fields

Popis výsledku anglicky

In this paper, we present an algorithm for estimating the occupancy of individual parking spaces. Our method is based on a computer analysis of images obtained by a camera system monitoring the activities on a parking lot. The proposed method extensivelyuses a priori information about the parking lot layout and the general shape of well-parked cars, which is incorporated in a simplified probabilistic car model. Discriminative features are extracted from a normalized image of every parking space, the relevance of these gradient-based features is prioritized via a selective flow, and furthermore, their spatial relationship is revealed through an undirected graphical model. We strive to avoid the training phase to reduce the time required to bring the system into a fully operational state. The reliability of the here devised approach is evaluated on the set of video sequences captured during different phases of a day and the results are compared against the ground truth data.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2013

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Lecture Notes in Computer Science. Volume 8034

ISBN

978-3-642-41938-6

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

12

Strana od-do

222-233

Název nakladatele

Springer Verlag

Místo vydání

London

Místo konání akce

Rethymnon

Datum konání akce

29. 7. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—