An improved searching algorithm for indoor trajectory reconstruction
Author(s) -
Min Li,
Jingjing Fu,
Yanfang Zhang,
Zhujun Zhang,
Siye Wang,
Huafeng Kong,
Rui Mao
Publication year - 2017
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1177/1550147717743697
Subject(s) - computer science , trajectory , process (computing) , scheme (mathematics) , reconstruction algorithm , algorithm , scale (ratio) , range (aeronautics) , search algorithm , trajectory optimization , iterative reconstruction , computer vision , artificial intelligence , mathematical optimization , mathematics , physics , astronomy , mathematical analysis , materials science , quantum mechanics , composite material , operating system
Trajectory reconstruction of mobile targets in large-scale infrastructure enables events in a range of applications, such as regional security, tourism, and healthcare, to be visualized. However, indoor environmental factors complicate the reconstruction process, usually resulting in reduced efficiency. In this article, we propose a searching algorithm that aims at a reasonable trajectory reconstruction scheme. The algorithm is developed based on the branch-and-bound method, which incorporates both depth-first search and breadth-first search so that a fast trajectory reconstruction on a topological map becomes viable. Experimental results demonstrated that the considered strategies are effective in accelerating reconstruction through a performance evaluation against current approaches for trajectory reconstruction.
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