Fast Classification of Empty and Occupied Parking Spaces Using Integral Channel Features

Forskningsoutput: Kapitel i bok/rapport/Conference proceedingKonferenspaper i proceeding

Abstract

In this paper we present a novel, fast and accurate system for detecting the presence of cars in parking lots. The system is based on fast integral channel features and machine learning. The methods are well suited for running embedded on low performance platforms. The methods are tested on a database of nearly 700,000 images of parking spaces, where 48.5% are occupied and the rest are free. The experimental evaluation shows improved robustness in comparison to the baseline methods for the dataset.

Detaljer

Författare
Enheter & grupper
Forskningsområden

Ämnesklassifikation (UKÄ) – OBLIGATORISK

  • Matematik
  • Datorseende och robotik (autonoma system)
Originalspråkengelska
Titel på värdpublikationProceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016
FörlagIEEE Computer Society
Sidor1609-1615
Antal sidor7
ISBN (elektroniskt)9781467388504
StatusPublished - 2016 dec 16
PublikationskategoriForskning
Peer review utfördJa
Evenemang2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016 - Las Vegas, USA
Varaktighet: 2016 jun 262016 jul 1

Konferens

Konferens2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016
LandUSA
OrtLas Vegas
Period2016/06/262016/07/01