SHOT: Scenario-type hypothesis object tracking with indoor sensor networks

Masakazu Murata, Yoshiaki Taniguchi, Go Hasegawa, Hirotaka Nakano

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

In the present paper, we propose an object tracking method called scenario-type hypothesis object tracking. In the proposed method, an indoor monitoring region is divided into multiple closed microcells using sensor nodes that can detect objects and their moving directions. Sensor information is accumulated in a tracking server through wireless multihop networks, and object tracking is performed at the tracking server. In order to estimate the trajectory of objects from sensor information, we introduce a novel concept of the virtual world, which consists of virtual micro-cells and virtual objects. Virtual objects are generated, transferred, and deleted in virtual micro-cells according to sensor information. In order to handle specific movements of objects in micro-cells, such as slowdown of passing objects in a narrow passageway, we also consider the generation of virtual objects according to interactions among virtual objects. In addition, virtual objects are generated when the tracking server estimates loss of sensor information in order to decrease the number of object tracking failures. Through simulations, we confirm that the ratio of successful tracking is improved by up to 29% by considering interactions among virtual objects. Furthermore, the tracking performance is improved up to 6% by considering loss of sensor information.

Original languageEnglish
Pages (from-to)1035-1044
Number of pages10
JournalIEICE Transactions on Information and Systems
VolumeE94-D
Issue number5
DOIs
Publication statusPublished - 2011 May

Keywords

  • Object tracking
  • Region segmentation
  • Sensor network
  • Virtual object

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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