Fast adaptive object detection towards a smart environment by a mobile robot

Shigeru Takano, Ilya Loshchilov, David Meunier, Michèle Sebag, Einoshin Suzuki

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

2 Citations (Scopus)


This paper proposes a novel method to detect objects by a mobile robot which adapts to an environment. Such a robot would help human designers of a smart environment to recognize objects in the environment with their attributes, which significantly facilitates his/her design. We first introduce Lifting Complex Wavelet Transform (LCWT) which plays an important role in this work. Since the LCWT has a set of controllable free parameters, we can design the LCWTs with various properties by tuning their parameters. In this paper we construct a set of LCWTs so that they can extract local features from an image by multi-scale. The extracted local features must be robust against several kinds of changes of the image such as shift, scale and rotation. Our method can design these LCWTs by selecting their parameters so that the mobile robot adapts to the environment. Applying the new set of LCWTs to the images captured by the mobile robot in the environment, a local feature database can be constructed. By using this database, we implement an object detection system based on LCWTs on the mobile robot. Effectiveness of our method is demonstrated by several test results using the mobile robot.

Original languageEnglish
Title of host publicationAmbient Intelligence - 4th International Joint Conference, AmI 2013, Proceedings
PublisherSpringer Verlag
Number of pages16
ISBN (Print)9783319036465
Publication statusPublished - 2013
Event4th International Joint Conference on Ambient Intelligence, AmI 2013 - Dublin, Ireland
Duration: Dec 3 2013Dec 5 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8309 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other4th International Joint Conference on Ambient Intelligence, AmI 2013

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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