Analyzing Images for Music Recommendation
This work addresses the need for enhanced user experiences in multimedia applications by providing music recommendations tailored to image types, though it appears incremental as it builds on existing deep-learning methods for image classification.
The paper tackles the problem of recommending music based on image content by classifying images as artworks or photographs using deep-learning models, and reports a Mean Opinion Score (MOS) from subjective assessments to support its effectiveness.
Experiencing images with suitable music can greatly enrich the overall user experience. The proposed image analysis method treats an artwork image differently from a photograph image. Automatic image classification is performed using deep-learning based models. An illustrative analysis showcasing the ability of our deep-models to inherently learn and utilize perceptually relevant features when classifying artworks is also presented. The Mean Opinion Score (MOS) obtained from subjective assessments of the respective image and recommended music pairs supports the effectiveness of our approach.