Abstract
This paper presents methods for automatically rating and selecting digital photographs. The importance of each photograph is estimated by analyzing its content as well as its time-metadata. The presence of people is estimated by combining face and skin detection. Finally, the appeal of each photograph is calculated using a trained SVM classifier. The results of a conducted user study show that the automatically obtained rating coincides well with the perception of the test persons.
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Kormann, D., Dunker, P., Paduschek, R. (2009). Automatic Rating and Selection of Digital Photographs. In: Chua, TS., Kompatsiaris, Y., Mérialdo, B., Haas, W., Thallinger, G., Bailer, W. (eds) Semantic Multimedia. SAMT 2009. Lecture Notes in Computer Science, vol 5887. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10543-2_23
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DOI: https://doi.org/10.1007/978-3-642-10543-2_23
Publisher Name: Springer, Berlin, Heidelberg
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