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© 2011 IBM Corporation Camera Roll-out and Optimization Rick Kjeldsen.

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Presentation on theme: "© 2011 IBM Corporation Camera Roll-out and Optimization Rick Kjeldsen."— Presentation transcript:

1 © 2011 IBM Corporation Camera Roll-out and Optimization Rick Kjeldsen

2 © 2012 IBM Corporation Camera Deployment Overview Configure in SVS Create Camera / View Calibrate - RoU - Object Type - Color - Camera Mvt Detect Alert Deployment and Optimization Select Profile On basis of use case Evaluation and Deployment Event Analysis Video Pre-processing RoU tweaks Customer IBM Select Cameras & Define Use Case

3 © 2012 IBM Corporation Alert Deployment and Optimization Select Cameras Test / Tune Collect perf data Evaluate Remediate Staged Event Testing Monitor Adjudicate Alerts Additional tuning Maintenance Deploy Reject Customer IBM Initial Configuration Classify view Select Initial Alert Configuration Define Alert

4 © 2012 IBM Corporation Initial Camera Configuration - details Initial Alert Configuration Select alert on basis of view characteristics e.g. Motion Detection vs Directional Motion vs Region Select initial alert parameters RoI Timeouts Size etc.

5 © 2012 IBM Corporation Test/Tune loop – details Iterate as needed (weekly) Alert Analysis -Estimate #FPs -Estimate # wild TPs -Determine trends/patterns FPR Evaluation -FPR & HR -Options remaining HR Tuning -As wild events available: -Detailed analysis of results -Select / Apply Remediation FP Tuning -Address primary cause of FPs -If HR impact, review w/ customer -Address primary cause of low HR Recommend Reject -High FP -Remediation not effective -No options remain -Review w/ customer Deploy -FP < Threshold -HR

6 © 2012 IBM Corporation Staged Event testing Needed when wild events are rare Customer stages events As many as reasonable Revisit cameras when possible IBM evaluates results and tunes as needed Options – depends on customers needs All cameras or Sample ? Only after FP tuning ? Cause to Reject Camera ? Absolute performance numbers unreliable without large numbers of events !

7 © 2012 IBM Corporation Typical Alert tuning success rate 70% deployed with minimal reduction in Hit Rate –35% minimal tuning (1-2 iterations) –15% with moderate tuning (2-3 iterations) –15% where tuning has minor HR impact 15% could be deployed with more severe HR impact 15% will be rejected

8 © 2012 IBM Corporation Backup Slides

9 © 2012 IBM Corporation Hit Rate acceptance testing Odds of failing acceptance test: –Assumptions: Actual Alert detection rate: 75% Minimum acceptable performance: 65% Message: –An alert which performs better than required has a good chance of failing an acceptance test with a small number of trials. –If your customer insists you test every camera, you must insist on a fair test – lots of trials. # trialsChance of failing 832% 1022% 2010% 505% 1001% %

10 © 2012 IBM Corporation Misc Camera management tools –Currently spreadsheet –based –Built-in support in future release


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