Multi-view people detection on arbitrary ground in real-time

Ákos Kiss, Tamás Szirányi

Research output: Conference contribution

2 Citations (Scopus)

Abstract

We show a method to detect accurate 3D position of people from multiple views, regardless of the geometry of the ground. In our new method we search for intersections of 3D primitives (cones) to find positions of feet. The cones are computed by back-projecting ellipses covering feet in input images. Instead of computing complex intersection body, we use approximation to speed up intersection computing. We found that feet positions are determined accurately, and the height map of the ground can be reconstructed with small error. We compared our method to other multiview-detectors - using somewhat different test methodology -, and achieved comparable results, with the benefit of handling arbitrary ground. We also present accurately reconstructed height map of non-planar ground. Our algorithm is fast and most of steps are parallelizable, making it possibly available for smart camera systems.

Original languageEnglish
Title of host publicationVISAPP 2013 - Proceedings of the International Conference on Computer Vision Theory and Applications
Pages675-680
Number of pages6
Publication statusPublished - máj. 31 2013
Event8th International Conference on Computer Vision Theory and Applications, VISAPP 2013 - Barcelona, Spain
Duration: febr. 21 2013febr. 24 2013

Publication series

NameVISAPP 2013 - Proceedings of the International Conference on Computer Vision Theory and Applications
Volume1

Other

Other8th International Conference on Computer Vision Theory and Applications, VISAPP 2013
CountrySpain
CityBarcelona
Period2/21/132/24/13

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ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Cite this

Kiss, Á., & Szirányi, T. (2013). Multi-view people detection on arbitrary ground in real-time. In VISAPP 2013 - Proceedings of the International Conference on Computer Vision Theory and Applications (pp. 675-680). (VISAPP 2013 - Proceedings of the International Conference on Computer Vision Theory and Applications; Vol. 1).