Exploring Appearance and Style in Heterogeneous Visual Content
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There are multiple ways to capture and represent the visual world; a drawing, a photograph, or a video are a few examples of visual data that are very frequent nowadays. Despite the different nature of each domain, there is a common need to process and edit these data after its production for different purposes. For example, we might want to modify the materials and the illumination of an object in a photograph, or we might want to explore a huge collection of non labeled images. The solutions to these problems mainly depend on the amount of information we have as input: it is not the same to process a plain set of colored pixels, like a photograph, than a scene captured with a 3D laser scan and multiple cameras. Thus, the nature of the visual data will also determine the complexity of the model we can use for processing. In this thesis, we focus on creating alternative representations of the visual content which will facilitate posterior editing and exploration tasks. In particular, we will focus on conventional visual data like pictures, video sequences , and light fields; and we will explore two different aspects or these data, the appearance in real scenes and the style in artistic scenes.