Probabilistic Inference of Multi-Object Trajectories

Authors:
Pengcheng Wang
Affiliations:
Shanghai Jiao Tong University, Shanghai, China
Venue:
Proceedings of International Conference on Advances in Mobile Computing & Multimedia
Year:
2013

Citing 5
Cited 0

Indoor Localization Using Camera Phones

WMCSA '06 Proceedings of the Seventh IEEE Workshop on Mobile Computing Systems & Applications
EnTracked: energy-efficient robust position tracking for mobile devices

Proceedings of the 7th international conference on Mobile systems, applications, and services
Improving energy efficiency of location sensing on smartphones

Proceedings of the 8th international conference on Mobile systems, applications, and services
Did you see Bob?: human localization using mobile phones

Proceedings of the sixteenth annual international conference on Mobile computing and networking
Automatic inference of movements from contact histories

Proceedings of the ACM SIGCOMM 2011 conference

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a novel approach of inferring the trajectories of moving objects in a library, a conference hall, or a large shopping mall, where GPS, Wi-Fi or cellular localization is not readily available or is deemed too expensive. Our solution is a distributed one whereby each object records all the other objects it encounters as well as the time of contact and such contact histories collectively enable the probabilistic inference of each object's whereabouts in the past as long as the map of the area is known.