Abstract
In this paper, we present a learning photo composition for landscape images. The system will recommend the best image composed location by learning aesthetic features when a user arbitrarily inputs the beauty background image and foreground images (refine by image matting). It is difficult to find the best image composition location. In addition to different characteristics of images, the aesthetic assessments of users' subjective appreciations are needed to be considered and addressed. Although some rules like composition rules in photography, there are subjective assessments that are not appreciated or appropriate for some images. Our method is based on learning feature that we could find the implicitly shared knowledge and rules among the professional photographers that is not like composition rules. In this work, we classified all types of the images into different sub-groups, and then we used spatial and geometry texture features to learn the model in the different sub-group. There are some advantages as the following: 1) our system could be applied to different type of images by user inputting 2) it provided results with different implicit knowledge and rules in different sub-group. We proposed the learning photo composition for landscape images to find best location which can be adapted for different images. To prove this, in subjective aesthetic assessment for user studies showed our proposed method has better scores. This research has different applications. One of the applications is find the best composition location for image composition, and the other application is that it can provide the best object placed in view rectangular for photography. In summary, we proposed a learning system for image composition in which we provided general users and amateurs alike to make good composition images that are relatively professional by using the aesthetic feature system for image composition proposed in our work.