Scalable Vision Graph Estimation for a Vision Sensor Network

摘要：

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.

作者: Shin Kondo Shingo Kagami Koichi Hashimoto

作者单位: Graduate School of Information Sciences,Tohoku University,Japan

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Robotics and Biomimetics(2009 IEEE 机器人与仿生技术国际会议 ROBIO 2009)

会议地点: 桂林

会议语种:英文

页码: 865-870

在线出版日期: 2009-12-19（万方平台首次上网日期，不代表论文的发表时间）