Automated exploration and inspection: Comparing two visual novelty detectors

  • Vieira Neto H
  • Nehmzow U
  • 20


    Mendeley users who have this article in their library.
  • 7


    Citations of this article.


Mobile robot applications that involve exploration and inspection of dynamic environments benefit, and often even are dependant on reliable novelty detection algorithms. In this paper we compare and discuss the performance and functionality of two different on-line novelty detection algorithms, one based on incremental Principal Component Analysis and the other on a Grow-When-Required artificial neural network. A series of experiments using visual input obtained by a mobile robot interacting with laboratory and real-world environments demonstrate and measure advantages and disadvantages of each approach.

Author-supplied keywords

  • Mobile robotics
  • On-line novelty detection
  • Real-time computer vision

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document


  • Hugo Vieira Neto

  • Ulrich Nehmzow

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free