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Master’s Project Proposal Briefing Bill Champlin

Master’s Project Proposal Briefing Bill Champlin. Java Quasi-Connected Components (JQCC) Tracking System March 10, 2009 Advisor - Dr. Terrance Boult. LOTS Background [1][2]. LOTS was developed for tracking human motion in omnidirectional images, such as for sniper tracking.

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Master’s Project Proposal Briefing Bill Champlin

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  1. Master’s Project Proposal BriefingBill Champlin Java Quasi-Connected Components (JQCC) Tracking System March 10, 2009 Advisor - Dr. Terrance Boult

  2. LOTS Background[1][2] • LOTS was developed for tracking human motion in omnidirectional images, such as for sniper tracking • Has been and continues to be adapted to other domains such as tracking of navel ships and UAVs • Has been rehosted to various architectures and can optionally utilize MMX libraries for increased performance Image taken from [1]

  3. LOTS Background – Con’t • Employs a technique called Quasi-Connected Components (QCC) • Given target pixels above threshold, connects additional pixels to targets that are below threshold but above background and close in proximity to target pixels • Puts more pixels on target – increasing probability of detection • Allows for a higher threshold setting which reduces false alarms caused by background clutter

  4. LOTS Software • Current baseline is around 96 KSLOC of C++ • Numerous conditional compile statements to support various architectures i.e. Intel MMX and different input cameras • Drives large size somewhat as core functionality is replicated • Other non core functionality provided also contributes to size, such as image flattening to reduce convex mirror distortion • Undocumented and sparsely commented

  5. Objectives • Gain a general understanding of LOTS software and algorithm techniques including: backgrounding, thresholding, pixel labeling, clustering & centroiding, and tracking across time • Activities: • Obtain s/w baseline and study current functionality • Study existing source code and extract core functionality (QCC) • Develop requirements specification and design • Port LOTS core functionality to Java (JQCC), includes: • Creating front end interface to input image movies • Displaying processed images and ROI tracks • Generation of output tracking reports • Perform testing and develop certification specification • Verify execution under Windows and Linux platforms

  6. Objectives – Con’t • Learn how to adapt LOTS algorithm techniques to a new domain area • Activities: • Modify and tune JQCC to track objects in the night sky, such as satellites, the International Space Station (ISS), airplanes, meteors, etc. • Obtain image sequences – either via internet (i.e. NASA’s JPL) or capture with a camera and home telescope • Compare JQCC performance • Activities: • JQCC vs. LOTS (is pure Java fast enough?) • Compare and analyze results • Optimize as necessary OPTIONAL ACTIVITY TIME PERMITTING: • Compare JQCC vs. another publicly available tracking algorithm

  7. Tasks • Mid Feb – March 31 • Establish executable baseline • Study functionality • Strip out LOTS core functionality • April 1 - April 18 • Develop requirements specification • April 19 – May 31 • Translate and re-host core functionality in Java

  8. Tasks – Con’t • June 1 – June 30 • Modify & tune for night sky images • July 1 – July 31 • Analyze JQCC performance • August 1 – August 21 • Publish project report • Publish JQCC to the web • Publish all deliverables to UCCS Grad Studies repository • November • Project defense

  9. Deliverables • Per UCCS C.S. Guidelines: • Requirements spec • Certification spec • User’s handbook • Source code (including test drivers, images and outputs) • Short, informal project report (report is mandatory for research projects, but not software development efforts) • Summarize re-hosting activities • UML design • Performance • Analysis of adapting it to tracking night sky objects • Optionally, the results of comparison with an alternate tracking algorithm • Bi-weekly status reports to Dr. Boult (and any other committee members if requested) • All products uploaded to UCCS Grad Studies repository and posted on the web

  10. References • [1] T.E. Boult, R.J. Micheals, X. Gao, M. Eckmann, “Into the woods: visual surveillance of non-cooperative and camouflaged targets in complex outdoor settings”, in Proc. Of the IEEE, Oct. 2001 • [2] T.E. Boult, T. Zhang, R.C. Johnson, “Two threshold are better than one”, CVPR, pp.1-8, 2007 IEEE Conference on Computer Vision and Pattern Recognition

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