Real-time spatio-temporal analysis of dynamic scenes

Tobias Warden, Ubbo Visser

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

We propose a set of tools for spatio-temporal real-time analysis of dynamic scenes. It is designed to improve the grounding situation of autonomous agents in (simulated) physical domains. We introduce a knowledge processing pipeline ranging from relevance-driven compilation of a qualitative scene description to a knowledge-based detection of complex event and action sequences, conceived as a spatio-temporal pattern-matching problem. A methodology for the formalization of motion patterns and their inner composition is introduced and applied to capture human expertise about domain-specific motion situations. We present extensive experimental results from a challenging environment: 3D soccer simulation. It substantiates real-time applicability of our approach under tournament conditions, based on a 5-Hz (a) precise and (b) noisy/incomplete perception. The approach is not limited to robot soccer. Instead, it can also be applied in other fields such as experimental biology and logistic processes.

Original languageEnglish (US)
Pages (from-to)243-279
Number of pages37
JournalKnowledge and Information Systems
Volume32
Issue number2
DOIs
StatePublished - Aug 1 2012

Keywords

  • Analysis of dynamic scenes
  • Qualitative knowledge
  • Spatio-temporal pattern matching

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Human-Computer Interaction
  • Hardware and Architecture
  • Artificial Intelligence

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