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Related Experiment Video

Updated: Feb 7, 2026

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Relative Pose Based Redundancy Removal: Collaborative RGB-D Data Transmission in Mobile Visual Sensor Networks.

Xiaoqin Wang1, Y Ahmet Şekercioğlu2, Tom Drummond3

  • 1ARC Centre of Excellence for Robotic Vision, Monash University, Victoria 3800, Australia. xiaoqin.wang@monash.edu.

Sensors (Basel, Switzerland)
|July 28, 2018
PubMed
Summary

A new Relative Pose based Redundancy Removal (RPRR) scheme optimizes mobile RGB-D sensor networks. This method significantly improves wireless channel efficiency and reduces power consumption for 3D mapping in static environments.

Keywords:
3D mappingRGB-D sensorscollaborative codingrelative pose estimationrobotic visionvisual sensors

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Area of Science:

  • Robotics and Sensor Networks
  • Computer Vision and 3D Mapping
  • Wireless Communication Efficiency

Background:

  • Mobile RGB-D sensor networks are crucial for 3D mapping in various applications.
  • Bandwidth constraints in wireless networks limit data transmission efficiency and increase power consumption.
  • Existing methods often transmit redundant visual and depth information, leading to inefficiencies.

Purpose of the Study:

  • To introduce a novel Relative Pose based Redundancy Removal (RPRR) scheme.
  • To enhance wireless channel usage efficiency and reduce power consumption in mobile RGB-D sensor networks.
  • To enable rapid 3D mapping in bandwidth-constrained scenarios, particularly for static environments.

Main Methods:

  • The RPRR scheme operates in a multiview scenario with multiple RGB-D sensors.
  • It identifies and removes redundant visual and depth information by analyzing relative sensor poses.
  • The processed, non-redundant data is then transmitted, conserving bandwidth and power.

Main Results:

  • Experimental results demonstrate a 250% improvement in wireless channel utilization.
  • Battery consumption is reduced by 50% compared to independent sensor image transmission.
  • The RPRR scheme effectively minimizes data redundancy in multiview 3D mapping.

Conclusions:

  • The Relative Pose based Redundancy Removal (RPRR) scheme significantly improves the efficiency of mobile RGB-D sensor networks.
  • RPRR is highly suitable for applications requiring rapid 3D mapping in static, bandwidth-constrained environments, such as disaster recovery.
  • The scheme offers substantial benefits in terms of wireless channel usage and power savings.