Award Abstract # 0846750
CAREER: Observer Design for Intelligent Visual Tracking

NSF Org: ECCS
Division of Electrical, Communications and Cyber Systems
Recipient: GEORGIA TECH RESEARCH CORP
Initial Amendment Date: August 17, 2009
Latest Amendment Date: March 13, 2014
Award Number: 0846750
Award Instrument: Standard Grant
Program Manager: Radhakisan Baheti
ECCS
 Division of Electrical, Communications and Cyber Systems
ENG
 Directorate for Engineering
Start Date: September 1, 2009
End Date: August 31, 2015 (Estimated)
Total Intended Award Amount: $399,951.00
Total Awarded Amount to Date: $399,951.00
Funds Obligated to Date: FY 2009 = $399,951.00
ARRA Amount: $399,951.00
History of Investigator:
  • Patricio Vela (Principal Investigator)
    pvela@ece.gatech.edu
Recipient Sponsored Research Office: Georgia Tech Research Corporation
926 DALNEY ST NW
ATLANTA
GA  US  30318-6395
(404)894-4819
Sponsor Congressional District: 05
Primary Place of Performance: Georgia Institute of Technology
225 NORTH AVE NW
ATLANTA
GA  US  30332-0002
Primary Place of Performance
Congressional District:
05
Unique Entity Identifier (UEI): EMW9FC8J3HN4
Parent UEI: EMW9FC8J3HN4
NSF Program(s): EPCN-Energy-Power-Ctrl-Netwrks
Primary Program Source: 01R00910DB RRA RECOVERY ACT
Program Reference Code(s): 0000, 093E, 1045, 1187, 6890, OTHR
Program Element Code(s): 760700
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041

ABSTRACT

Proposal Number: 0846750

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).

The project described in this proposal seeks to improve the stability and robustness of computer vision algorithms used in closed-loop systems. The research Endeavour examines the role control theory may play in enhancing closed-loop computer vision algorithms. The concept of understanding the interplay between control and computer vision is achieving prominence as vision is increasingly sought for automating processes.

Intellectual Merit:

As a sensor, the imaging system can be wrought with noise, either through the actual sensing process or through the geometry of the imaged scene (e.g., through clutter, occlusions, variable hypotheses, etc.). Thus, the vision task can be interpreted as a signal processing task in the presence of noise and uncertainty. By deriving observers for visual tracking systems that seek to estimate both target location and target boundary, the PI proposes to systematically derive a highly stable and robust visual tracking algorithm. The research Endeavour involves the definition of a probabilistic shape state and associated measurement models; the derivation of a full state observer for dynamic objects and environments; and the use of machine learning to impose soft and hard geometric constraints on the measurement model. The main difficulties lie in the richness of the visual field coupled with the noise inherent to all visual sensors, and the fragility of imposing constraints on the measurement model when the target itself is both flexible and corrupted by imaging noise.

Broader Impact:

Application of the proposed work will reduce the amount of human labor involved in many monotonous, repetitive, or time-intensive tasks. Efforts will be specifically driven by two application areas: workforce tracking for safety analysis of airport ground operations, construction site operations, surface mining operations, and microscopic cellular tracking and analysis. Both of these application areas are related to the health and well-being of the populace, have the potential to save lives, and will have a positive economic impact.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 11)
H.A. Kingravi, G. Chowdhary, P.A. Vela, and E.N. Johnson "Reproducing Kernel Hilbert Space Approach for the Online Update of Radial Bases in Neuro-Adaptive Contro" IEEE Trans. on Neural Networks and Learning Systems , v.23 , 2012 , p.1130 10.1109/TNNLS.2012.2198889
H. Astley, C. Gong, M. Travers, M. Serrano, P. Vela, J.R. Mendelson III, H. Choset, D.L. Hu, D.I. Goldman "Modulation of Orthogonal Body Waves Enables High Maneuverability in Sidewinding Locomotion" Proceedings of the NAtional Academy of Sciences , v.112 , 2015 , p.6200-5 10.1073/pnas.1418965112
H. Kingravi, G. Chowdary, P.A. Vela, and E. Johnson "Reproducing Kernel Hilbert Space Approach for the Online Update of Radial Bases in Neuro-Adaptive Control" IEEE Trans. on Neural Networks and Learning Systems , v.23 , 2012 , p.1130
J. Yang, O. Arif, P.A. Vela, and Z. Shi "Tracking Multiple Workers on Construction Sites Using Video Cameras" Advanced Engineering Informatics , v.24 , 2010 , p.428 10.1016/j.aei.2010.06.008
O. Arif and P.A. Vela "Kernel Map Compression for Speeding Kernel-Based Methods" IEEE Trans. on Neural Networks , v.22 , 2011 , p.870
P. Karasev, I. Kolesov, K. Fritscher, P. Vela, P. Mitchell, and A. Tannenbaum "Interactive Medical Image Segmentation using PDE Control of Active Contours" IEEE Transactions on Medical Imaging , v.32 , 2013 , p.2127 10.1109/TMI.2013.2274734
Rebola, C., Ogunmakin, G., and Vela, P.A. "Design and Technologies for Understanding Older Adults Social Interactions in Retirement Communities" International Journal of Social Robotics , v.5 , 2013 , p.575 10.1007/s12369-013-0219-6
S.S. Sharpe, S.A. Koehler, R. Kuckuk, M. Serrano, P. Vela, D.I. Goldman "Locomotor Benefits of Being a Slender and Slick Sand-Swimmer" Journal of Experimantal Biology , v.218 , 2015 , p.440-450 10.1242/jeb.108357
T. Cheng, M. Venugopal, J. Teizer, and P.A. Vela "Performance Evaluation of Ultra Wideband Technology for Construction Resource Location Tracking in Harsh Environments" Automation in Construction , v.20 , 2011 , p.1173 10.1016/j.autcon.2011.05.001
Y. Lou, A. Irimia, P. Vela, M.C. Chambers, J. Van Horn, P.M. Vespa, and A. Tannenbaum. "Multimodal Deformable Registration of Traumatic Brain Injury MR Volumes via the Bhattacharyya Distance" IEEE Transactions on Bioengineering , v.60 , 2013 , p.2511 10.1109/TBME.2013.2259625
Y. Lou, X. Jia, T. Niu, P. Vela, L. Zhu, and A. Tannenbaum "Joint CT/CBCT Deformable Registration and CBCT Enhancement for Cancer Radiotherapy" Medical Image Analysis , v.17 , 2013 10.1016/j.media.2013.01.005
(Showing: 1 - 10 of 11)

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