Talks and Poster Presentations (with Proceedings-Entry):

A. Aldoma, F. Tombari, W. Kropatsch, M. Vincze:
"Localizing and Segmenting Objects with 3D Objectness.";
Talk: CVWW 2013, 18th Computer Vision Winter Workshop, Hernstein, Austria (invited); 2013-02-04 - 2013-02-06; in: "Proceedings of the 18th Computer Vision Winter Workshop 2013", W. Kropatsch, F. Torres Garcia, G. Ramachandran (ed.); Prip 186/3, Wien (2013), ISBN: 978-3-200-02943-9; 86 - 93.

English abstract:
This paper presents a novel method to lo-
calize and segment objects on close-range table-top
scenarios sensed with a depth sensor. The method is
based on a novel
measure that evaluates
how likely a 3D region in space (defined by an ori-
ented bounding box) could contain an object. Within
a parametrized volume of interest placed above the
table plane, a set of 3D bounding boxes is generated
that exhaustively covers the parameter space. Effi-
ciently evaluating - thanks to integral volumes and
parallel computing - the 3D objectness at each sam-
pled bounding box allows efficiently defining a set
of regions in space with high probability of contain-
ing an object. Bounding boxes characterized by high
objectness are then processed by means of a global
optimization stage aimed at discarding inconsistent
object hypotheses with respect to the scene. We eval-
uate the effectiveness of the method for the task of
scene segmentation

Created from the Publication Database of the Vienna University of Technology.