Scalable vision graph estimation for a vision sensor network

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

Abstract

This paper describes a scalable method of estimating a vision graph, in which a pair of camera nodes are connected by an edge if the two nodes share the same field of view, based on local image feature correspondences. The proposed method is implemented in a distributed fashion, meanwhile avoiding the flooding of the image feature information since it can be a bottleneck in achieving scalability. The key idea is to partition the image feature space into a set of disjoint regions so that the correspondence search can be carried out within a partitioned region, with each region served by a different network node independently. Simulated results using real images show that the proposed method achieves reasonable estimation performance while improving the traffic amount and traffic balance greatly.

Original languageEnglish
Title of host publication2009 IEEE International Conference on Robotics and Biomimetics, ROBIO 2009
Pages865-870
Number of pages6
DOIs
Publication statusPublished - 2009 Dec 1
Event2009 IEEE International Conference on Robotics and Biomimetics, ROBIO 2009 - Guilin, China
Duration: 2009 Dec 192009 Dec 23

Publication series

Name2009 IEEE International Conference on Robotics and Biomimetics, ROBIO 2009

Other

Other2009 IEEE International Conference on Robotics and Biomimetics, ROBIO 2009
Country/TerritoryChina
CityGuilin
Period09/12/1909/12/23

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Biomaterials

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