Fast task-specific target detection via graph based constraints representation and checking

Wentao Luan, Yezhou Yang, Cornelia Fermuller, John S. Baras

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

We present a framework for fast target detection in real-world robotics applications. Considering that an intelligent agent attends to a task-specific object target during execution, our goal is to detect the object efficiently. We propose the concept of early recognition, which influences the candidate proposal process to achieve fast and reliable detection performance. To check the target constraints efficiently, we put forward a novel policy which generates a sub-optimal checking order, and we prove that it has bounded time cost compared to the optimal checking sequence, which is not achievable in polynomial time. Experiments on two different scenarios: 1) rigid object and 2) non-rigid body part detection validate our pipeline. To show that our method is widely applicable, we further present a human-robot interaction system based on our non-rigid body part detection.

Original languageEnglish (US)
Title of host publicationICRA 2017 - IEEE International Conference on Robotics and Automation
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3984-3991
Number of pages8
ISBN (Electronic)9781509046331
DOIs
StatePublished - Jul 21 2017
Event2017 IEEE International Conference on Robotics and Automation, ICRA 2017 - Singapore, Singapore
Duration: May 29 2017Jun 3 2017

Other

Other2017 IEEE International Conference on Robotics and Automation, ICRA 2017
CountrySingapore
CitySingapore
Period5/29/176/3/17

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ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Artificial Intelligence
  • Electrical and Electronic Engineering

Cite this

Luan, W., Yang, Y., Fermuller, C., & Baras, J. S. (2017). Fast task-specific target detection via graph based constraints representation and checking. In ICRA 2017 - IEEE International Conference on Robotics and Automation (pp. 3984-3991). [7989458] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICRA.2017.7989458