AdaBoost for parking lot occupation detection

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F13%3A86089029" target="_blank" >RIV/61989100:27240/13:86089029 - isvavai.cz</a>

Výsledek na webu

<a href="http://link.springer.com/chapter/10.1007%2F978-3-319-00969-8_67" target="_blank" >http://link.springer.com/chapter/10.1007%2F978-3-319-00969-8_67</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-00969-8_67" target="_blank" >10.1007/978-3-319-00969-8_67</a>

Jazyk výsledku

angličtina

Název v původním jazyce

AdaBoost for parking lot occupation detection

Popis výsledku v původním jazyce

Parking lot occupation detection using vision systems is a very important task. Many systems use different sensors and their combinations to find out whether the parking lot or space is occupied or not. Using CCTV systems makes it possible to monitor great areas without a need of many sensors. In this paper, we present a method that uses the boosting algorithm for car detection on particular parking spaces and shifting the image to obtain a probability function of car appearance. Using the model of parking lot, we achieve occupancy of each parking space. We also experimented with the detector that is based on the histogram of oriented gradients (HOG) with a support vector machine (SVM). Nevertheless, we found some drawbacks of this detector that we describe in experiments. On the grounds of these drawbacks, we decided to use the AdaBoost based detector.

Název v anglickém jazyce

AdaBoost for parking lot occupation detection

Popis výsledku anglicky

Parking lot occupation detection using vision systems is a very important task. Many systems use different sensors and their combinations to find out whether the parking lot or space is occupied or not. Using CCTV systems makes it possible to monitor great areas without a need of many sensors. In this paper, we present a method that uses the boosting algorithm for car detection on particular parking spaces and shifting the image to obtain a probability function of car appearance. Using the model of parking lot, we achieve occupancy of each parking space. We also experimented with the detector that is based on the histogram of oriented gradients (HOG) with a support vector machine (SVM). Nevertheless, we found some drawbacks of this detector that we describe in experiments. On the grounds of these drawbacks, we decided to use the AdaBoost based detector.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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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 periodika

Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013

ISSN

2194-5357

e-ISSN

—

Svazek periodika

226

Číslo periodika v rámci svazku

2013

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

10

Strana od-do

681-690

Kód UT WoS článku

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EID výsledku v databázi Scopus

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