Welcome To UTPedia

We would like to introduce you, the new knowledge repository product called UTPedia. The UTP Electronic and Digital Intellectual Asset. It stores digitized version of thesis, dissertation, final year project reports and past year examination questions.

Browse content of UTPedia using Year, Subject, Department and Author and Search for required document using Searching facilities included in UTPedia. UTPedia with full text are accessible for all registered users, whereas only the physical information and metadata can be retrieved by public users. UTPedia collaborating and connecting peoples with university’s intellectual works from anywhere.

Disclaimer - Universiti Teknologi PETRONAS shall not be liable for any loss or damage caused by the usage of any information obtained from this web site.Best viewed using Mozilla Firefox 3 or IE 7 with resolution 1024 x 768.

EMOTION BASED MUSIC PLAYER

TAN , SIEW CHING (2012) EMOTION BASED MUSIC PLAYER. UNIVERSITI TEKNOLOGI PETRONAS, UNIVERSITI TEKNOLOGI PETRONAS. (Unpublished)

[img]
Preview
PDF
Download (2766Kb) | Preview

Abstract

The work presents described the development of Emotion Based Music Player, which is a computer application meant for all type of users, specifically the music lovers. Due to the troublesome workloads in songs selection, most people will choose to randomly play the songs in the playlist. As a result, some of the songs selected not matching the users’ current emotion. Moreover, there is no commonly used music player which able to play the songs based on user’s emotion. The proposed model is able to extract user’s facial expression and thus detect user’s emotion. The music player in the proposed model will then play the songs according to the category of emotion detected. It is aimed to provide a better enjoyment to music lovers in music listening. The scope of emotions in the proposed model involve normal, sad, surprise and happy. The system involves the major of image processing and facial detection technologies. The input for this proposed model is the .jpeg format still images which available online. The performance of this model is evaluated by loading forty still images (ten for each emotion category) into the proposed model to test on the accuracy in detecting the emotions. Based on the testing result, the proposed model has the Recognition Rate of 85%.

Item Type: Final Year Project
Academic Subject : Academic Department - Management And Humanities - Business and Marketing
Subject: UNSPECIFIED
Divisions: Sciences and Information Technology > Computer and Information Sciences
Depositing User: Sharifah Fahimah Saiyed Yoep
Date Deposited: 01 Apr 2013 11:34
Last Modified: 25 Jan 2017 09:40
URI: http://utpedia.utp.edu.my/id/eprint/6334

Actions (login required)

View Item View Item

Document Downloads

More statistics for this item...