Attraction Betterment by Rule of Thirds for Nature Scene Picture
The ability to model composition for nature Scene Picture allows for a number of advantageous applications, for instance: object detection, object co-occurrence and memorability analysis. This paper presents an algorithm for automatically improving attraction of pictures taken for real scenes with consideration of picture composition. In our application a set of scene images are studied in the relationship between picture composition and the rule of thirds. As the rule diagnoses picture region that potentially raise human visual attention, the learning process supports to discover on which level the composition of a nature scene picture is complied with the rule. We then extract the region with potential visual attention, and improve attraction for the region. Here a set of picture features is used to describe picture composition. Each feature is weighted regarding to the rule of thirds and they are combined in a unique composition descriptor. The robustness of the algorithm to rich types of nature scene pictures and deviations from user-input data is tested considering other methods.
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