Detecting and tracking moving objects in long-distance imaging through turbulent medium

Eli Chen; Oren Haik; Yitzhak Yitzhaky

doi:10.1364/AO.53.001181

Applied Optics
Vol. 53,
Issue 6,
pp. 1181-1190
(2014)
•https://doi.org/10.1364/AO.53.001181

Detecting and tracking moving objects in long-distance imaging through turbulent medium

Eli Chen, Oren Haik, and Yitzhak Yitzhaky

Not Accessible

Your library or personal account may give you access

Get PDF
Email
Share
Get Citation
Copy Citation Text
Eli Chen, Oren Haik, and Yitzhak Yitzhaky, "Detecting and tracking moving objects in long-distance imaging through turbulent medium," Appl. Opt. 53, 1181-1190 (2014)

Export Citation
- BibTex
- Endnote (RIS)
- HTML
- Plain Text
Citation alert
Save article

Related Topics
Table of Contents Category
- Image Processing
Optics & Photonics Topics
?

The topics in this list come from the Optics and Photonics Topics applied to this article.

About this Article
History
- Original Manuscript: October 18, 2013
- Revised Manuscript: January 14, 2014
- Manuscript Accepted: January 14, 2014
- Published: February 20, 2014
Virtual Issues
Virtual Journal for Biomedical Optics Vol. 9, Iss. 4

Abstract

The challenge of detecting and tracking moving objects in imaging throughout the atmosphere stems from the atmospheric turbulence effects that cause time-varying image shifts and blur. These phenomena significantly increase the miss and false detection rates in long-range horizontal imaging. An efficient method was developed, which is based on novel criteria for objects’ spatio-temporal properties, to discriminate true from false detections, following an adaptive thresholding procedure for foreground detection and an activity-based false alarm likeliness masking. The method is demonstrated on significantly distorted videos and compared with state of the art methods, and shows better false alarm and miss detection rates.

Full Article | PDF Article

Previous Article Next Article

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Figures (4)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Tables (2)

You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Equations (12)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

	Proposed Method			Oreifej et al. [5]			Barnich and Van Droogenbroeck [9] $R = 80$			Barnich and Van Droogenbroeck [9] $R = 40$			Previous Method [11]
	TP	FN	FP	TP	FN	FP	TP	FN	FP	TP	FN	FP	TP	FN	FP
Seq1	1	0	0	1	0	0	0	1	0	1	0	37	1	0	67
Seq2	16	0	0	9	7	13	16	0	1	16	0	5	5	11	3
Seq3	3	0	0	2	1	5	2	1	2	3	0	12	3	0	0
Seq4	4	1	4	5	0	153	4	1	13	5	0	73	5	0	6
Seq5	2	0	1	1	1	167	2	0	46	2	0	113	0	2	149
Seq6	1	0	0	1	0	195	1	0	49	1	0	134	1	0	2

	Proposed method			Oreifej et al. [5]			Barnich and Van Droogenbroeck [9] $R = 80$			Barnich and Van Droogenbroeck [9] $R = 40$			Previous method [11]
Turb. level	Prec.	Recall	$F_{1}$	Prec.	Recall	$F_{1}$	Prec.	Recall	$F_{1}$	Prec.	Recall	$F_{1}$	Prec.	Recall	$F_{1}$
Moderate	1.00	1.00	1.00	0.57	0.74	0.62	0.81	0.56	0.51	0.33	1.00	0.41	0.55	0.77	0.48
Strong	0.72	0.93	0.83	0.02	0.83	0.03	0.10	0.93	0.16	0.03	1.00	0.08	0.26	0.66	0.37

	Proposed Method			Oreifej et al. [5]			Barnich and Van Droogenbroeck [9] $R = 80$			Barnich and Van Droogenbroeck [9] $R = 40$			Previous Method [11]
	TP	FN	FP	TP	FN	FP	TP	FN	FP	TP	FN	FP	TP	FN	FP
Seq1	1	0	0	1	0	0	0	1	0	1	0	37	1	0	67
Seq2	16	0	0	9	7	13	16	0	1	16	0	5	5	11	3
Seq3	3	0	0	2	1	5	2	1	2	3	0	12	3	0	0
Seq4	4	1	4	5	0	153	4	1	13	5	0	73	5	0	6
Seq5	2	0	1	1	1	167	2	0	46	2	0	113	0	2	149
Seq6	1	0	0	1	0	195	1	0	49	1	0	134	1	0	2

	Proposed method			Oreifej et al. [5]			Barnich and Van Droogenbroeck [9] $R = 80$			Barnich and Van Droogenbroeck [9] $R = 40$			Previous method [11]
Turb. level	Prec.	Recall	$F_{1}$	Prec.	Recall	$F_{1}$	Prec.	Recall	$F_{1}$	Prec.	Recall	$F_{1}$	Prec.	Recall	$F_{1}$
Moderate	1.00	1.00	1.00	0.57	0.74	0.62	0.81	0.56	0.51	0.33	1.00	0.41	0.55	0.77	0.48
Strong	0.72	0.93	0.83	0.02	0.83	0.03	0.10	0.93	0.16	0.03	1.00	0.08	0.26	0.66	0.37

Abstract

References

Cited By

Figures (4)

Tables (2)

Equations (12)

Metrics

Applied Optics

Login or Create Account