Performance and Portability of Cloud-based Computer vision: A Software Case Study

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dc.contributor.advisorMoussavi, Mahmood
dc.contributor.advisorFar, Behrouz Homayoun
dc.contributor.authorSalehian-Dardashti, Soheil
dc.contributor.committeememberKrishnamurthy, Diwakar
dc.contributor.committeememberHemmati, Hadi
dc.date2018-06
dc.date.accessioned2018-04-30T19:02:41Z
dc.date.available2018-04-30T19:02:41Z
dc.date.issued2018-04-25
dc.description.abstractThe proliferation of visual sensors in terms variety and magnitude, has commenced an era where rich extensive visual data can be extracted and analyzed with the goal of a better understanding of the world around us. The forefront of this visual data analysis, is the field of computer vision that traditionally has been utilized in centralized systems but in recent years, has experienced an evolution towards a distributed cloud environment. The objective of this work is to analyze the software engineering processes that allow a rapid conversion of a centralized computer vision system to a cloud based distributed one. The work entails in developing the centralized algorithm in the specific realm of driver fatigue detection, analyzing its properties and designing an engineering methodology along with implementing the conversion from centralized to distributed computer vision. The focus of the thesis is on the implementation and real world metrics that represent the challenges in performance and portability attributes of most distributed computer vision systems. The proposed methodology’s merit is demonstrated through the blink detection use case study. Using requirement gathering techniques, the metrics are defined and compared at different stages of development to ensure minimal effort in porting the blink detection system. A generalizable message based architecture is proposed and implemented for a subclass of computer vision algorithms as a stepping stone for future analysis of other computational patterns that are associated with computer vision algorithms and systems.en_US
dc.identifier.citationSalehian-Dardashti, S. (2018). Performance and Portability of Cloud-based Computer vision: A Software Case Study (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/31860en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/31860
dc.identifier.urihttp://hdl.handle.net/1880/106574
dc.language.isoeng
dc.publisher.facultyGraduate Studies
dc.publisher.facultySchulich School of Engineering
dc.publisher.institutionUniversity of Calgaryen
dc.publisher.placeCalgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subjectSoftware Engineering
dc.subject.classificationComputer Scienceen_US
dc.subject.classificationEngineeringen_US
dc.titlePerformance and Portability of Cloud-based Computer vision: A Software Case Study
dc.typemaster thesis
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameMaster of Science (MSc)
ucalgary.item.requestcopytrue
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