Compressed sensing using hidden Markov models with application to vision based aircraft tracking

Ford, Jason J., Molloy, Timothy L., & Hall, Joanne L. (2014) Compressed sensing using hidden Markov models with application to vision based aircraft tracking. In 17th International Conference on Information Fusion, 7-10 July 2014, Salamanca, Spain.

Abstract

This paper investigates compressed sensing using hidden Markov models (HMMs) and hence provides an extension of recent single frame, bounded error sparse decoding problems into a class of sparse estimation problems containing both temporal evolution and stochastic aspects. This paper presents two optimal estimators for compressed HMMs. The impact of measurement compression on HMM filtering performance is experimentally examined in the context of an important image based aircraft target tracking application. Surprisingly, tracking of dim small-sized targets (as small as 5-10 pixels, with local detectability/SNR as low as − 1.05 dB) was only mildly impacted by compressed sensing down to 15% of original image size.

Impact and interest:

0 citations in Scopus
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

123 since deposited on 14 Jul 2014
23 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 73893
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: hidden Markov model, compressed sensing, target tracking
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Signal Processing (090609)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > Schools > School of Mathematical Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2014 Please consult the authors
Deposited On: 14 Jul 2014 22:46
Last Modified: 29 Oct 2014 23:05

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page