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

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
Event2016 IEEE lnternational Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2016 - Baden-Baden, Germany
Duration: 19 Sep 201621 Sep 2016

Conference

Conference2016 IEEE lnternational Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2016
CountryGermany
CityBaden-Baden
Period19/09/1621/09/16

Cite this

Wang, X., Ahmet Sekercioglu, Y., Drummond, T., Natalizio, E., Fantoni, I., & Fremont, V. (2017). Collaborative multi-sensor image transmission and data fusion in mobile visual sensor networks equipped with RGB-D cameras. In 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2016): Baden-Baden, Germany, 19-21 September 2016 (pp. 1-8). [7849458] Piscataway, NJ: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/MFI.2016.7849458
Wang, Xiaoqin ; Ahmet Sekercioglu, Y. ; Drummond, Tom ; Natalizio, Enrico ; Fantoni, Isabelle ; Fremont, Vincent. / Collaborative multi-sensor image transmission and data fusion in mobile visual sensor networks equipped with RGB-D cameras. 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2016): Baden-Baden, Germany, 19-21 September 2016. Piscataway, NJ : IEEE, Institute of Electrical and Electronics Engineers, 2017. pp. 1-8
@inproceedings{caa24b9488624c9b9c4f0fab0dd63bce,
title = "Collaborative multi-sensor image transmission and data fusion in mobile visual sensor networks equipped with RGB-D cameras",
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.",
author = "Xiaoqin Wang and {Ahmet Sekercioglu}, Y. and Tom Drummond and Enrico Natalizio and Isabelle Fantoni and Vincent Fremont",
year = "2017",
month = "2",
day = "9",
doi = "10.1109/MFI.2016.7849458",
language = "English",
isbn = "9781467397094",
pages = "1--8",
booktitle = "2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2016)",
publisher = "IEEE, Institute of Electrical and Electronics Engineers",
address = "United States of America",

}

Wang, X, Ahmet Sekercioglu, Y, Drummond, T, Natalizio, E, Fantoni, I & Fremont, V 2017, Collaborative multi-sensor image transmission and data fusion in mobile visual sensor networks equipped with RGB-D cameras. in 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2016): Baden-Baden, Germany, 19-21 September 2016., 7849458, IEEE, Institute of Electrical and Electronics Engineers, Piscataway, NJ, pp. 1-8, 2016 IEEE lnternational Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2016, Baden-Baden, Germany, 19/09/16. https://doi.org/10.1109/MFI.2016.7849458

Collaborative multi-sensor image transmission and data fusion in mobile visual sensor networks equipped with RGB-D cameras. / Wang, Xiaoqin; Ahmet Sekercioglu, Y.; Drummond, Tom; Natalizio, Enrico; Fantoni, Isabelle; Fremont, Vincent.

2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2016): Baden-Baden, Germany, 19-21 September 2016. Piscataway, NJ : IEEE, Institute of Electrical and Electronics Engineers, 2017. p. 1-8 7849458.

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

TY - GEN

T1 - Collaborative multi-sensor image transmission and data fusion in mobile visual sensor networks equipped with RGB-D cameras

AU - Wang, Xiaoqin

AU - Ahmet Sekercioglu, Y.

AU - Drummond, Tom

AU - Natalizio, Enrico

AU - Fantoni, Isabelle

AU - Fremont, Vincent

PY - 2017/2/9

Y1 - 2017/2/9

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85015188157&partnerID=8YFLogxK

U2 - 10.1109/MFI.2016.7849458

DO - 10.1109/MFI.2016.7849458

M3 - Conference Paper

SN - 9781467397094

SP - 1

EP - 8

BT - 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2016)

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Piscataway, NJ

ER -

Wang X, Ahmet Sekercioglu Y, Drummond T, Natalizio E, Fantoni I, Fremont V. Collaborative multi-sensor image transmission and data fusion in mobile visual sensor networks equipped with RGB-D cameras. In 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2016): Baden-Baden, Germany, 19-21 September 2016. Piscataway, NJ: IEEE, Institute of Electrical and Electronics Engineers. 2017. p. 1-8. 7849458 https://doi.org/10.1109/MFI.2016.7849458