Seat detection in a car for a smart airbag application

David Schreiber, Yun Luo

Publikation: Beitrag in FachzeitschriftArtikelBegutachtung

Abstract

We present a method to detect the seat and head-rest of the by-passenger, as a part of a smart airbag system. The recognition of the
seat and head-rest is useful for the purpose of background subtraction, as well as for assisting head-tracking and occupant classification.
We use a multi-resolution probabilistic generalized Hough transform (GHT). We present experimental results for the detection, as well as
an error analysis. Our experiments were performed using an imperfect set of models on close-range images with low dynamic range and
under sever occlusions. Nevertheless, we have found that one needs to consider only the best 11 hypotheses of the GHT to ensure recognition.
Moreover, when at least 25% of the seat contour is not occluded, only two hypotheses are needed on the average. The results
show that the head-rest is a more robust clue than the seat. Finally, we discuss how to extend our work and possible uses in the context of
occupant detection and classification.
OriginalspracheEnglisch
Seiten (von - bis)534-544
Seitenumfang11
FachzeitschriftPattern Recognition Letters
Volume28
Issue4
DOIs
PublikationsstatusVeröffentlicht - 1 März 2007

Research Field

  • Former Research Field - Surveillance and Protection

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