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A real time video pipeline for computer vision using embedded GPUs

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dc.contributor.authorPatil, Rutuja, author
dc.contributor.authorBeveridge, Ross, advisor
dc.contributor.authorOlschanowsky, Catherine, advisor
dc.contributor.authorAzimi Sadjadi, Mahmood, committee member
dc.contributor.authorGuzik, Stephen, committee member
dc.date.accessioned2017-01-04T22:59:19Z
dc.date.available2017-01-04T22:59:19Z
dc.date.issued2016
dc.description.abstractThis thesis presents case study confirming the feasibility of real time Computer Vision applications on embedded GPUs. Applications that depend on video processing, such as security surveillance, can benefit from applying optimizations common in scientific computing. This thesis demonstrates the benefit of applying such optimizations to real time Computer Vision applications on embedded GPUs. The primary contribution of this thesis is an optimized implementation of ViBe targeting NVIDIA's Jetson TK1. ViBe is a commonly used background subtraction algorithm. Optimizing a background subtraction algorithm accelerates the task of reducing the field of view to only interesting patches of the frames of the video. Placing portable hardware close to capturing devices in the surveillance system reduces bandwidth requirements and cost. The goals of the optimizations proposed for this algorithm are to 1) reduce memory traffic 2) overlap CPU and GPU usage 3) reduce kernel overhead. The optimized implementation of ViBe achieves a frame rate of almost 55 FPS beating the real time goal standard of 30 FPS for real time video. This is a small portion of the real-time window leaving processing time for additional algorithms like object recognition.
dc.format.mediumborn digital
dc.format.mediummasters theses
dc.identifierPatil_colostate_0053N_13969.pdf
dc.identifier.urihttp://hdl.handle.net/10217/178925
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2000-2019
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectembedded graphics processing units
dc.subjectparallel computing
dc.subjectoptimizations
dc.subjectcomputer vision
dc.titleA real time video pipeline for computer vision using embedded GPUs
dc.typeText
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.grantorColorado State University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science (M.S.)

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