Abstract

We describe a novel method to track targets in a large field of view. This method simultaneously images multiple, encoded sub-fields of view onto a common focal plane. Sub-field encoding enables target tracking by creating a unique connection between target characteristics in superposition space and the target’s true position in real space. This is accomplished without reconstructing a conventional image of the large field of view. Potential encoding schemes include spatial shift, rotation, and magnification. We discuss each of these encoding schemes, but the main emphasis of the paper and all examples are based on one-dimensional spatial shift encoding. System performance is evaluated in terms of two criteria: average decoding time and probability of decoding error. We study these performance criteria as a function of resolution in the encoding scheme and signal-to-noise ratio. Finally, we include simulation and experimental results d onstrating our novel tracking method.

© 2009 Optical Society of America

» View Full Text: Acrobat PDF (493 KB)

History
Original Manuscript: July 25, 2008
Manuscript Accepted: January 19, 2009
Revised Manuscript: October 27, 2008
Published: January 29, 2009

References

1. E. Cuevas, D. Zaldivar, and R. Rojas, "Kalman filter for vision tracking," Free University of Berlin, Tech. Rep. (2005).
2. D. J. Brady, "Micro-optics and megapixels," Opt. Photon. News 17, 24-29 (2006). [CrossRef]
3. D. J. Brady and M. E. Gehm, "Compressive imaging spectrometers using coded apertures," Proc. SPIE 6246, 62460A, (2006).
4. M. A. Neifeld and P. Shankar, "Feature-specific imaging," Appl. Opt. 42, 3379-3389 (2003). [CrossRef]
5. D. Takhar, J. N. Laska, M. B. Wakin, M. F. Duarte, D. Baron, S. Sarvotham, K. F. Kelly, and R. G. Baraniuk, "A new compressive imaging camera architecture using optical-domain compression," Proc. SPIE 6065, 606509 (2006).
6. D. Donoho, "Compressed sensing," IEEE Trans. Inform. Theory 52, 1289-1306 (2006). [CrossRef]
7. E. J. Candés, "Compressive sampling," Proc. Intl. Cong. Mathematicians (2006).
8. M. D. Stenner, P. Shankar, and M. A. Neifeld, "Wide-field feature-specific imaging," in Frontiers in Optics, Optical Society of America, (2007).
9. D. Du and F. Hwang, Combinatorial group testing and its applications, Series on Applied Mathematics 12, (World Scientific, 2000).
10. C. M. Brown, "Multiplex imaging with random arrays," Ph.D. dissertation, Univ. of Chicago, (1972).
11. R. H. Dicke, "Scatter-hole cameras for x-rays and gamma rays," Astrophys J. 153, L101-L106,(1968).
12. A. Biswas, P. Guha, A. Mukerjee, and K. S. Venkatesh, "Intrusion detection and tracking with pan-tilt cameras," IET Intl. Conf. VIE 06, 565-571 (2006).
13. A. W. Senior, A. Hampapur, and M. Lu, "Image segmentation in video sequences: A probabilistic approach," WACV/MOTION’05, 433-438 (2005).
14. C. R. Wren, A. Azarbayejani, T. J. Darrell, and A. P. Pentland, "Pfinder: Real-time tracking of the human body," IEEE Trans. Pattern Anal. Mach. Intell 19, 780-785 (1997). [CrossRef]
15. N. Friedman and S. J. Russell, "Image segmentation in video sequences: A probabilistic approach," Proc. Uncertainty Artif. Intell. Conf. 175-181 (1997).
16. C. Stauffer and E. L. Grimson "Learning patterns of activity using real-time tracking," IEEE Trans. Pattern Anal. Mach. Intell 22, 747-757 (2000). [CrossRef]
17. A. Mittal and N. Paragios, "Motion-based background subtraction using adaptive kernel density estimation," Proc. IEEE Conf. Comput. Vis. Pattern Recognit. 302-309 (2004).
18. K. P. Karmann and A. Brandt, "Moving Object Recognition Using an Adaptive Background Memory," in Time varying image processing and moving object recognition Volume 2, V. Cappellini (ed.), (Elsevier, 1990).
19. P. Jodoin, M. Mignotte, and J. Konrad, "Statistical background subtraction using spatial cues," IEEE Circuits Syst. Video Technol 17, 1758-1763 (2007). [CrossRef]
20. R. Singh, "Advanced correlation filters for multi-class synthetic aperture radar detection and classification," Carnegie Mellon University, MS Rep. (2002).
21. M. Alkanhal and B. V. K. Vijaya Kumar, "Polynomial Distance Classifier Correlation Filter for Pattern Recognition," Appl. Opt. 42, 4688-4708 (2003). [CrossRef]
22. B. V. K. Vijaya Kumar, "Minimum-variance synthetic discriminant functions," J. Opt. Soc. Am. A 3, 1579-1584 (1986). [CrossRef]
23. B. V. K. Vijaya Kumar, D. W. Carlson, and A. Mahalanobis, "Optimal trade-off synthetic discriminant function filters for arbitrary devices," Opt. Lett. 19, 1556-1558 (1994). [CrossRef]
24. S. M. Kay, Fundamentals of Statistical Processing, Volume I: Estimation Theory. (Prentice Hall, 1993).

Author Affiliations

Changsoon Kim, Renu John, Jungsang Kim, David Brady

Duke University

Shikhar Uttam, Nathan A. Goodman, Mark A. Neifeld

University of Arizona

Multimedia

Cited By

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

Advanced Search

Recent ToC Categories (Beta)

• Jan 14 2010 : OSA wins SPARC Innovator award for Optics Express. Read the press release.
• Jan 14 2010 : The Journal of the Optical Society of Korea is now available in the Optics InfoBase!
• Jan 08 2010 : Optics InfoBase now supports export to Mendeley. Learn more about Mendeley for online citation management and sharing.

More News

• Journal of the Optical Society of Korea Added to OSA’s Optics InfoBase
  Feb 1, 2010 - The Optical Society (OSA) is pleased to announce that Optics... more
• OSA to Launch New Journal: Biomedical Optics Express
  Jan 20, 2010 - The Optical Society (OSA) today announced it is launching a new... more
• Invisibility Visualized
  Nov 12, 2009 - Scientists and curiosity seekers who want to know what a partially or... more