A search space strategy for pedestrian detection and localization in world coordinates

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

Abstract

The focus of this work is detecting pedestrians, captured in a surveillance setting, and locating them in world coordinates. Commonly adopted search strategies operate in the image plane to address the object detection problem with machine learning, for example using scale-space pyramid with the sliding windows methodology or object proposals. In contrast, here a new search space is presented, which exploits camera calibration information and geometric priors. The proposed search strategy will facilitate detectors to directly estimate pedestrian presence in world coordinates of interest. Results are demonstrated on real world outdoor collected data along a path in dim light conditions, with the goal to locate pedestrians in world coordinates. The proposed search strategy indicate a mean error under 20 cm, while image plane search methods, with additional processing adopted for localization, yielded around or above 30 cm in mean localization error. This while only observing 3-4% of patches required by the image plane searches at the same task.

Detaljer

Författare
Enheter & grupper
Forskningsområden

Ämnesklassifikation (UKÄ) – OBLIGATORISK

  • Datorseende och robotik (autonoma system)

Nyckelord

Originalspråkengelska
Titel på värdpublikationVISAPP
FörlagSciTePress
Sidor17-24
Antal sidor8
Volym5
ISBN (elektroniskt)9789897582905
StatusPublished - 2018 jan 1
PublikationskategoriForskning
Peer review utfördJa
Evenemang13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2018 - Funchal, Madeira, Portugal
Varaktighet: 2018 jan 272018 jan 29

Konferens

Konferens13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2018
LandPortugal
OrtFunchal, Madeira
Period2018/01/272018/01/29