Assessing Personally Perceived Image Quality via Image Features and Collaborative Filtering

During the past few years, different methods for optimizing the camera settings and post-processing techniques to improve the subjective quality of consumer photos have been studied extensively. However, most of the research in the priorart has focused on finding the optimal method for an average user. Since there is large deviation in personal opinions and aesthetic standards, the next challenge is to find the settings and post-processing techniques thatfit to the individualusers 'personaltaste. In this study, we aim to predict the personallyperceived image quality by combining classical imagefeature analysis and collaboration filtering approach known from the recommendation systems. The experimental resultsfor the proposed method show promising results. As a practical application, our work can be used for personalizing the camera settings orpost-processingparameterfsor different users and images.