Indoor surveillance video based feature recognition for pedestrian dead reckoning

Abstract

Driven by the connection of everything, various electronic devices and sensors have been applied to the Internet of Things (IoT) as sources of information. However, indoor surveillance cameras, which are a quality resource, are only used in the field of security monitoring. Based on the development of indoor surveillance camera about image features, this study proposes a positioning method of pedestrian dead reckoning (PDR) based on image feature recognition of indoor surveillance video. In this study, the images collected by traditional indoor surveillance cameras are used as the data source. By extracting the image features to establish an image landmark database, geographic coordinates are allocated to each feature image of the landmark database in order to establish indoor location benchmark points. These image landmarks are combined with pedestrian dead reckoning to obtain the accurate position estimation. The experimental results show that the proposed indoor surveillance video based feature recognition for pedestrian dead reckoning can effectively use the indoor camera resources as a position benchmark in order to achieve higher pedestrian positioning accuracy. Meanwhile, this strategy of establishing a landmark database based on existing monitoring videos effectively utilizes existing indoor monitoring resources and promotes the application of traditional surveillance cameras.