Collaborative multi-sensor image transmission and data fusion in mobile visual sensor networks equipped with RGB-D cameras

Xiaoqin Wang, Y. Ahmet Sekercioglu, Tom Drummond, Enrico Natalizio, Isabelle Fantoni, Vincent Fremont

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

3 Citations (Scopus)

Abstract

We present a scheme for multi-sensor data fusion applications, called Relative Pose based Redundancy Removal (RPRR), that efficiently enhances the wireless channel utilization in bandwidth-constrained operational scenarios for RGB-D camera equipped visual sensor networks. Pairs of nodes cooperatively determine their own relative pose, and by using this knowledge they identify the correlated data related to the common regions of the captured color and depth images. Then, they only transmit the non-redundant information present in these images. As an additional benefit, the scheme also extends the battery life through reduced number of packet transmissions. Experimental results confirm that significant gains in terms of wireless channel utilization and energy consumption would be achieved when the RPRR scheme is used in visual sensor network operations.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2016)
Subtitle of host publicationBaden-Baden, Germany, 19-21 September 2016
Place of PublicationPiscataway, NJ
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1-8
Number of pages8
ISBN (Electronic)9781467397087
ISBN (Print)9781467397094
DOIs
Publication statusPublished - 9 Feb 2017
EventIEEE International conference on Multisensor Fusion and Integration for Intelligent Systems 2016 - Baden-Baden, Germany
Duration: 19 Sep 201621 Sep 2016

Conference

ConferenceIEEE International conference on Multisensor Fusion and Integration for Intelligent Systems 2016
Abbreviated titleMFI 2016
CountryGermany
CityBaden-Baden
Period19/09/1621/09/16

Cite this