Automated selection of spatial object relations for modeling and recognizing indoor scenes with hierarchical Implicit Shape Models

Pascal Meibner*, Fabian Hanselmann, Rainer Jakel, Sven R. Schmidt-Rohr, Rudiger Dillmann

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

1 Citation (Scopus)

Abstract

We present an approach that uses combinatorial optimization to decide which spatial relations between objects are relevant to accurately describe an indoor scene, made up of objects. We extract scene models from object configurations that are acquired during demonstration of actions, characteristic for a certain scene. We model scenes as graphs with Implicit Shape Models (ISMs), a Generalized Hough Transform variant. ISMs are limited to represent scenes as star-shaped topologies of object relations, leading to false positives in recognizing scenes. To describe other relation topologies, we introduced a representation of trees of ISMs in prior work together with a method to learn such ISM trees from demonstrations. Limited to creating topologies, corresponding to spanning trees, that method omits certain relations so that false positives still occur. In this paper, we introduce a method to convert any relation topology, corresponding to a connected graph, into an ISM tree using a heuristic depth-first-search. It allows using complete graphs as scene models. Despite causing no false positives, complete graphs are intractable for scene recognition. To achieve efficiency, we contribute a method that searches for an optimal relation topology by traversing the space of connected scene graphs, for a given set of objects, using an optimization similar to hill climbing. Optimality is defined as minimizing computational costs during scene recognition, while producing a minimum of false positives. Experiments with up to 15 objects show that both are achievable by the presented method. Costs, growing exponentially with the number of objects, are transferred from online recognition to offline optimization.

Original languageEnglish
Title of host publicationIROS Hamburg 2015 - Conference Digest
Subtitle of host publicationIEEE/RSJ International Conference on Intelligent Robots and Systems
Place of PublicationHamburg, Germany
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4257-4264
Number of pages8
ISBN (Electronic)9781479999941
DOIs
Publication statusPublished - 11 Dec 2015
EventIEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015 - Hamburg, Germany
Duration: 28 Sep 20152 Oct 2015

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
Volume2015-December
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

ConferenceIEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015
Country/TerritoryGermany
CityHamburg
Period28/09/152/10/15

Keywords

  • Topology
  • Trajectory
  • Shape
  • Robot kinematics
  • Vegetation
  • Optimization

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