Date of Publication

12-3-2022

Document Type

Bachelor's Thesis

Degree Name

Bachelor of Science in Computer Engineering

Subject Categories

Electrical and Computer Engineering

College

Gokongwei College of Engineering

Department/Unit

Electronics And Communications Engg

Thesis Advisor

Reggie C. Gustilo

Defense Panel Chair

Melvin K. Cabatuan

Defense Panel Member

Maria Antonette C. Roque
Edwin Sybingco

Abstract/Summary

This paper aims to explore options for bringing innovations to another level, and that is with iOS development and computer vision. Making a commercial product that any regular music listener can utilize would be beneficial to achieve awareness of these technologies having more purpose in one’s day-to-day life. With music and technology that both work harmoniously to improve one’s listening experience, the developers did their research to piece up both computer vision and mainstream listening applications together. The different facial recognition technologies that the developers have explored, such as blendShapes and CNNEmotions, were thoroughly tested by various testing applications, such as proof-of-concept iOS applications and other acceptable methods. In line with the creation of the application, the developers have learned these technologies without prior experience. Hence, the application's design has brought many realizations that brought favorable data and results when the application has been completed, which is determined by user acceptance testing.

Abstract Format

html

Language

English

Format

Electronic

Keywords

Human face recognition (Computer science); Music—Computer programs

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Embargo Period

12-8-2022

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