Online multi-person tracking using feature-less location measurements
Name
1014334861-MIT.pdf
Description
Full printable version
Size
3.59 MB
Format
Adobe PDF
Checksum (MD5)
7f047502955cb460cb93f34c1bc0135b
Author(s)
Farag, Emad William
Advisor(s)
Dina Katabi.
Date Issued
2016
Publisher
Massachusetts Institute of Technology
Abstract
This thesis presents a scalable real-time multi-object tracking system based on feature-less location measurements. The thesis introduces a two-stage object tracking algorithm along with a server infrastructure that allows users to view the tracking results live, replay old frames, or compute long-term analytics based on the tracking results. In the first tracking stage, consecutive measurements are connected to form short tracklets using an algorithm based on MHT. In the second stage, the tracklets are connected to form longer tracks in an algorithm that reduces the tracking problem to a minimum-cost flow problem. The system infrastructure allows for a large number of connected devices or sensors while reducing the possible points of failure. The tracking algorithms are evaluated in a controlled environment and in a daylong experiment in a real setting. In the latter, the number of people detected by the tracking algorithms was correct 83% of the time when tracking was done using noisy motion-based measurements.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 65-67).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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