Active visual object exploration and recognition with an unmanned aerial vehicle

Uriel Martinez Hernandez, Victor Cedeno-Campos, Adrian Rubio-Solis

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

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Abstract

In this paper, an active control method for visual object exploration and recognition with an unmanned aerial vehicle is presented. This work uses a convolutional neural network for visual object recognition, where input images are obtained with an unmanned aerial vehicle from multiple objects. The object recognition task is an iterative process actively controlled by a saliency map module, which extracts interesting object regions for exploration. The active control allows the unmanned aerial vehicle to autonomously explore better object regions to improve the recognition accuracy. The iterative exploration task stops when the probability from the convolutional neural network exceeds a decision threshold. The active control is validated with offline and real-time experiments for visual exploration and recognition of five objects. Furthermore, passive exploration is also tested for performance comparison. Experiments show that the unmanned aerial vehicle is capable to autonomously explore interesting object regions. Results also show an improvement in recognition accuracy from 88.14% to 95.66% for passive and active exploration, respectively. Overall, this work offers a framework to allow robots to autonomously decide where to move and look next, to improve the performance during a visual object exploration and recognition task.

Original languageEnglish
Title of host publicationInternational Joint Conference on Neural Networks (IJCNN)
Place of PublicationU. S. A.
PublisherIEEE
Number of pages7
ISBN (Electronic)9781728119854
ISBN (Print)978-1-7281-1986-1
DOIs
Publication statusPublished - 30 Sep 2019

Publication series

NameProceedings of the International Joint Conference on Neural Networks
PublisherIEEE
Volume2019-July
ISSN (Print)2161-4393
ISSN (Electronic)2161-4407

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

Cite this

Martinez Hernandez, U., Cedeno-Campos, V., & Rubio-Solis, A. (2019). Active visual object exploration and recognition with an unmanned aerial vehicle. In International Joint Conference on Neural Networks (IJCNN) [8851738] (Proceedings of the International Joint Conference on Neural Networks; Vol. 2019-July). U. S. A.: IEEE. https://doi.org/10.1109/IJCNN.2019.8851738