Emotion-based music player using facial recognition
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-...
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oai:animorepository.dlsu.edu.ph:etdb_ece-10142022-12-20T05:21:07Z Emotion-based music player using facial recognition Co, Adrian Richton D. Delgado, Nathan Jonah D. Medalla, Jose V., III 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. 2022-12-03T08:00:00Z text application/pdf https://animorepository.dlsu.edu.ph/etdb_ece/26 https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1014&context=etdb_ece Electronics And Communications Engineering Bachelor's Theses English Animo Repository Human face recognition (Computer science) Music—Computer programs Electrical and Computer Engineering |
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Human face recognition (Computer science) Music—Computer programs Electrical and Computer Engineering Co, Adrian Richton D. Delgado, Nathan Jonah D. Medalla, Jose V., III Emotion-based music player using facial recognition |
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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. |
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text |
author |
Co, Adrian Richton D. Delgado, Nathan Jonah D. Medalla, Jose V., III |
author_facet |
Co, Adrian Richton D. Delgado, Nathan Jonah D. Medalla, Jose V., III |
author_sort |
Co, Adrian Richton D. |
title |
Emotion-based music player using facial recognition |
title_short |
Emotion-based music player using facial recognition |
title_full |
Emotion-based music player using facial recognition |
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Emotion-based music player using facial recognition |
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Emotion-based music player using facial recognition |
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emotion-based music player using facial recognition |
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Animo Repository |
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2022 |
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https://animorepository.dlsu.edu.ph/etdb_ece/26 https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1014&context=etdb_ece |
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