ABSTRACT: The human face is an important organ of an individual‘s body and it especially plays an important role in extraction of an individual ‘s behaviour and emotional state. Manually segregating the list of songs and generating an appropriate playlist based on an individual‘s emotional features is a very tedious, time consuming, labour intensive and upheld task. Various algorithms have been proposed and developed for automating the playlist generation process. However, the proposed existing algorithms in use are computationally slow, less accurate. This proposed system based on facial expression extracted will generate a playlist automatically thereby reducing the effort and time involved in rendering the process manually. Thus, the proposed system tends to reduce the computational time involved in obtaining the results and the overall cost of the designed system, thereby increasing the overall accuracy of the system. Facial expressions are captured using an inbuilt camera. The accuracy of the emotion detection algorithm used in the system for real time images is around 85-90%, while for static images it is around 98- 100%. Thus, it yields better accuracy in terms of performance and computational time and reduces the designing cost, compared to the algorithms used in the literature survey. Based on the obtained emotion, playlist is created.
KEYWORDS: Music suggestion, Facial Recognition, SVM, OpenCV, Python.
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DOI:
10.17148/IJARCCE.2021.10682
