Data-driven season characteristic enhancement of natural image

We present a system of creating new scenes in different seasons from an input image captured in a particular season by stylizing it according to similar images in our library which includes a vast number of different season scenes and objects. Firstly, we transfer the color appearance of the input scene in accordance with the color style of other seasons scenes by using color transfer approach. Secondly, user scribbles are used to guide the detection of repeated elements in the input image and geometric information of these detected elements are obtained. Then context-sensitive objects of specified class that match most of the required properties are retrieved from our library and edited according to the geometric information of the specified elements in the scene, such as inserting new objects into the scene or replacing objects by new ones. After that, a repeated-elements-based modification duplication scheme is proposed and implemented to semi-automatically propagate the user-specified objects modification. Finally, blending is applied to the inserted objects to achieve consistency with the target scene in illumination. The main contribution of this work is that we present a complete system to create new scenes of different seasons.