Abstract book (pdf) - ICPR 2010

16:40-17:00, Paper ThCT3.4
Boosted Edge Orientation Histograms for Grasping Point Detection
Lefakis, Leonidas, TU Vienna
Wildenauer, Horst, Vienna Univ. of Tech.
Pascual García-Tubío, Manuel, Vienna Univ. of Tech.
Szumilas, Lech, Ind. Research Inst. for Automation & Measurement
In this paper, we describe a novel algorithm for the detection of grasping points in images of previously unseen objects.
A basic building block of our approach is the use of a newly devised descriptor, representing semi-local grasping point
shape by the use edge orientation histograms. Combined with boosting, our method learns discriminative grasp point models
for new objects from a set of annotated real-world images. The method has been extensively evaluated on challenging
images of real scenes, exhibiting largely varying characteristics concerning illumination conditions, scene complexity,
and viewpoint. Our experiments show that the method works in a stable manner and that its performance compares favorably
to the state-of-the-art.
17:00-17:20, Paper ThCT3.5
Automatic Refinement of Foreground Regions for Robot Trail Following
Kocamaz, Mehmet Kemal, Univ. of Delaware
Rasmussen, Christopher, Univ. of Delaware
Continuous trails are extended regions along the ground such as roads, hiking paths, rivers, and pipelines which can be
navigationally useful for ground-based or aerial robots. Finding trails in an image and determining possible obstacles on
them are important tasks for robot navigation systems. Assuming that a rough initial segmentation or outline of the region
of interest is available, our goal is to refine the initial guess to obtain a more accurate and detail representation of the true
trail borders. In this paper, we compare the suitability of several previously published segmentation algorithms both in
terms of agreement with ground truth and speed on a range of trail images with diverse appearance characteristics. These
algorithms include generic graph cut, a shape-based version of graph cut which employs a distance penalty, Grab Cut, and
an iterative superpixel grouping method.
ThCT4 Dolmabahçe Hall A
Image Representation and Analysis Regular Session
Session chair: Debled-Rennesson, Isabelle (LORIA-Nancy Univ.)
15:40-16:00, Paper ThCT4.1
Object Decomposition via Curvilinear Skeleton Partition
Serino, Luca, Istituto di Cibernetica
Sanniti Di Baja, Gabriella, CNR
Arcelli, Carlo, Istituto di Cibernetica
A method to decompose a complex 3D object into simpler parts is presented, based on a suitable partition of the curvilinear
skeleton of the object. The curvilinear skeleton is divided into subsets, by taking into account the regions of influence that
can be associated with its branch points. The obtained subsets are then used to recover the parts into which the object can
be decomposed.
16:00-16:20, Paper ThCT4.2
Differential Area Profiles
Ouzounis, Georgios, Joint Res. Center - Ispra, European Commission,
Soille, Pierre, Ec. Joint Res. Centre
In this paper a new feature descriptor, the differential area profile (DAP), is presented. DAPs, like the regular differential
morphological profiles, are computed from some size distribution. The proposed method is based on the area metric given
by regular connected area filters. Area compared to local width, i.e. the diameter of the structuring element in the corresponding
set of openings by reconstruction in classical DMPs, leads to a rather different multi-scale decomposition. This
is investigated here and an example on a very high resolution satellite image tile is given.
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