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Assisted Target Detection for Search & Rescue. James Elder Department of Computer Science and Engineering Department of Psychology & Centre for Vision Research York University. Project Overview. Improved sensing technologies have the potential to improve search and rescue performance.
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Assisted Target Detection for Search & Rescue James Elder Department of Computer Science and Engineering Department of Psychology & Centre for Vision Research York University
Project Overview • Improved sensing technologies have the potential to improve search and rescue performance. • The degree of improvement depends on how accurately the data generated by these technologies are interpreted, either by computer or by the human visual system. • The goal of the proposed project is to develop assisted target detection (ATD) algorithms that will improve human target detection rates by drawing visual attention to locations in the data stream where target probability is higher. • The SAR simulator at DRDC Toronto will serve as a test-bed for evaluating the efficacy of all image enhancements. • Project Start: Jan 1, 2006 • Project Finish: OCE Funding expected to March 31, 2008
Industrial Partner • Array Systems Computing • Specializes in computationally intensive, real-time digital signal processing systems using multiple parallel processors. • Provides high-performance software solutions in diverse application areas including sonar, radar and remote sensing, 3D modelling and simulation, and Software Defined Radio (SDR). • Located in Toronto, close to DRDC Downsview and York University. • Participants: • Rajesh Jha • Ray Obidowski • Steven Truelove
Funding Projection Contributors: 7 - Dec - 05 to 1 - Apr - 06 to 1 - Apr - 07 to Total of all 31 - Mar - 06 31 - Mar - 07 31 - Mar - 08 confirmed (confirmed) (propo sed) (proposed) and proposed c ontributions by sponsor : OCE cash $8 0,000 $8 0,000 $8 0,000 $24 0,000 Array cash $0 $0 $0 $ 0 in - kind $ 68,400 $163,000 $163,000 $3 94,400 DRDC $ 50,000 cash $1 10 ,000 $ 80 ,000 $ 240 ,000 in - kind $20 9,000 $10,000 $10,000 $22 9,000 Total contributions by $ 4 5 2,400 $ 363 , 000 $ 333 ,000 $1, 148 ,400 project year:
Milestones Tasks Resources Start End Update Recruit postdoctoral Nov Delayed due Recruit Funding Jan 06 fellow 05 to funding personnel delay Recruit computer vision Nov Feb V. Magdin Fu nding graduate student 05 06 started Sept 06 Recruit psychophysics Nov Mar Y . Funding graduate student 05 06 Morgenstern? Prepare and sign NDAs Time with Nov Dec Complete Completed and IP agreements institutional 05 05 legal between York and lawyers agreements Array, allowing sharing of source code. Milestones
Milestones Tasks Resources Start End Update Transfer C++ code for Array Dec Mar Establish Completed indoor surveillance to engineer 05 06 understan ding Array for integration of problem and testing on GSP and hardware. performance benchmarks Review DND Nov Mar Completed documents on SAR and 05 06 AIMS, and review general literature on searc h - and - rescue Obtain existing search - Existing DND Nov Dec Completed and - rescue datasets with database 05 0 5 ground truth for system development and evaluation Milestones
Milestones Tasks Resources Start End Update Single - frame Develop and evaluate Dec Jan 06 Completed algorithm single - frame st atistical 0 5 development target models. and testing Develop and evaluate Jan Completed - - Feb 06 single - frame adaptive 06 Discuss background models. Test frame - by - frame Feb Mar Completed ATD algorithm in 06 06 MATLAB on reserved flight data using ROC analysis Evaluate statistical Dec In Progress - Jan 07 algorithm against 06 Discuss AdaBoost methods Refine frame - by - frame Jan Feb 07 In Progress algorithm 07 Transfer MATLAB Feb Mar Array engineer code to Array for 07 07 integration and testing on GSP hardware Milestones
Milestones Tasks Resources Start End Update Acquire new sear ch - New DND Apr Mar Continuous and - rescue datasets database 07 07 algorithm with ground truth. development and testing Develop or adapt Georeferencing Mar Jun 07 georeferencing tools from 07 algorithms for search - AIMS project and - rescue data streams. Incorporate motion Jun Jul 07 cues and temporal 07 integratio n into foreground and background models. Test continuous ATD Aug Jul 07 algorithm in 07 MATLAB on reserved flight data using ROC analysis. Refine continuous Aug Sept algorithm 07 07 Transfer MATLAB Sept Dec Array engineer code to Array for 07 07 integration and t esting on GSP hardware Complete report on Sept Oct07 ATD algorithms 07 Complete publication Sept Dec on ATD results 07 07 Milestones
Milestones Tasks Resources Start End Update Develop candidate Dec Mar Develop and evaluate visualization methods 06 07 visualization for overlaying target methods probability data onto incoming visual data stream Develop Mar Jun 07 psychophysical 07 methodology for visualization evaluation using DRDC SAR Simulator Conduct human - in - DRDC Jun S ept the - loop SAR simulator 07 07 simulator experiments Complete report on Sept Dec visualization 07 07 methodologies and results of SAR simulation experiments. Complete publication Dec Mar on SAR simulation 07 08 results Milestones
Milestones Tasks Resources Start End Update Refine complete Dec Final system Jan 08 integration software system, 07 incl uding ATD and and reporting visualization algorithms Transfer final Jan Array engineer Feb 08 MATLAB/C++ code 08 to Array for integration and testing on GSP hardware Complete final report Feb Mar on ATD system 08 08 Milestones
Deliverables • Assisted target detection algorithms • Assisted target detection software (MATLAB and/or C++) • A demonstration of ATD software integrated with Array Systems Scalable Generic Signal Processor technology for real-time operation. • Results of human-in-the-loop experiments using the ATD technology and the DRDC SAR simulation system.
Ground Truth Labeling • Labeled over 30,000 objects • Invested over 100 man-hours, split between 6 people • Labeled portions of all 7 video sequences that contain targets
Ground Truth – Example Frame NIGHT EXERCISE_IR
Algorithm Evaluation • Selected subset of ground truth data from a single IR video (Night Exercise) • Not representative of search & rescue scenario • Training set • 100 frames • 5000 +ve examples • 5000 -ve examples • Test set • 185 frames • 9000 targets
1 0.9 Pixel-wise bayes 0.8 Zero-mean Target Model Normal Model 0.7 Static AdaBoost Linear SVM 0.6 Hit Rate 0.5 0.4 0.3 0.2 0.1 0 0 5 10 15 20 False Positives per Frame Algorithm Evaluation
Cross-Validation • An effort is underway to evaluate the reliability of the ground truth data by cross-validating across human subjects.
Search and Rescue Simulator • York is running a copy of the DRDC Search & Rescue simulator • Do we need a Flybox? • May need to buy higher-end computer.