Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/137941
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dc.contributor.authorSim, Jun Kaien_US
dc.date.accessioned2020-04-20T04:53:40Z-
dc.date.available2020-04-20T04:53:40Z-
dc.date.issued2020-
dc.identifier.urihttps://hdl.handle.net/10356/137941-
dc.description.abstractFace Recognition has been one of the most popular topics in the industry over the past decades. It is a biometric software that has many creative usages, for example, the camera of a smartphone where it will automatically focus on the face of the person and in China, cameras are used to capture the face of those people who jaywalk. The goal of this report is to present a face recognition system that makes use of k-Nearest Neighbors to achieve a rapid recognition of everyone that appears on the screen. Moreover, it can also be used as a memory aid for users. The report provides a detailed explanation of the software used, these include face recognition API, python libraries, pre-trained model and the reasons for choosing such techniques and methods to achieve the goals of the project. In addition, the flow chart and decision tree of the program will be used to provide a better illustration of how the face recognition system works. Lastly, the report has also stated further improvements which allow the whole face recognition project to achieve better user satisfaction and performance enhancement of the system.en_US
dc.language.isoenen_US
dc.publisherNanyang Technological Universityen_US
dc.relationSCSE19-0352en_US
dc.subjectEngineering::Computer science and engineeringen_US
dc.subjectEngineering::Computer science and engineering::Computing methodologies::Image processing and computer visionen_US
dc.titleRapid facial recognition through wearable camerasen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorCham Tat Jenen_US
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.description.degreeBachelor of Engineering (Computer Science)en_US
dc.contributor.supervisoremailastjcham@ntu.edu.sgen_US
item.grantfulltextrestricted-
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Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)
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