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SPIE DSS 2013 Presentation

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PRCI Threat Detection Presentation
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  SPIE DSS 2013 Intrusion Detection on Oil Pipeline Right of  Way using Monogenic Signal Representation Binu M Nair, Varun Santhaseelan, Chen Cui and Vijayan K Asari  Objectives ã To detect intrusions on the Energy Pipeline ROW. ã To prevent any damage to underground energy pipelines due to heavy weight of vehicles ã To detect and classify various types of construction machinery on ROW ã To validate algorithms on each of database – New Era, ATE, GeoEye, American Aerospace ã To cross-validate the algorithm between the databases BackhoeSkid SteerTrencherExcavatorMini-ExcavatorExcavatorBackhoe New Era DatasetATE Dataset  Problem Statement ã To establish a novel object detection algorithm which satisfies different challenges (Real life problems)  – Low and overly exposed illumination; cast shadows  – Different viewpoint, scale and orientation  – Varying resolution, motion blur ã Purpose:  – Generalize the algorithm parameters for all the datasets  – Developed with the mindset for implementation on GPU’s and multi -core processor.  – Have a deployable real-time system which works on the fly Low IlluminationCast ShadowsDifferent ViewpointMotion BlurHigh IlluminationDifferent OrientationDifferent Scale GTX-680  – 1532 cores  Characteristics of Local Phase Domain ã Analysis is done local phase domain to tackle the issue of non-uniform illumination. ã This local phase will characterize a construction equipment from the surrounding background(trees, buildings etc..) ã It is illumination invariant  – Not affected by over exposure to lighting, very low illumination conditions  – Brings out the edges/corners of the machine Backhoe  – Flight 8Local Phase Backhoe  – Flight 6Local Phase

jumo.pdf

Jul 23, 2017
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