Mobile photo recommendation system of continuous shots based on aesthetic ranking

摘要

Image aesthetics have been a popular topic in the recent years. The users can obtain aesthetic score of any image by using the computational approaches based on photography rules. However, most approaches consider the task as an off-line process because those methods usually require high computational complexity. On the other hand, mobile devices (tablet and smart phone) have become an indispensable tool in our daily life. Many users are more willing to take photos with them instead of digital cameras. Thus, developing practical camera applications (APPs) for mobile devices has high application potential. In this paper, respect to the issue of hardware computation limitation of mobile devices, we first design an instant photo aesthetics evaluation method. It adopts several simple and effective features to predict photo scores. The preliminary results conducted on benchmark datasets verify its performance and efficiency. Based on this achievement, we develop a continuous-shot photo recommendation system. It includes two steps: dominant photo selection performed in partially-decoded compression domain and instant photo aesthetics ranking. The system can automatically list the photos with higher scores, and help users to select desired ones. Crowd sourcing tests are employed to evaluate system performance, which show that our system is effective for instant aesthetic rating and photo recommendation.