Abstract
In this paper we describe and discuss our existing PicSOM software framework from the point of view of context-adaptive analysis of image contents, especially its method for using automatic image segmentation. We describe and experimentally validate a modification to the segment-using procedure that both essentially reduces the computational cost and slightly improves classification accuracy. Finally, we apply the segment-using methodology in qualitatively investigating the roles of primary objects and their context in classifying the images of the Pascal VOC Challenge 2006 database.
Supported by the Academy of Finland in the projects Neural methods in information retrieval based on automatic content analysis and relevance feedback and Finnish Centre of Excellence in Adaptive Informatics Research.
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Viitaniemi, V., Laaksonen, J. (2006). Use of Image Regions in Context-Adaptive Image Classification. In: Avrithis, Y., Kompatsiaris, Y., Staab, S., O’Connor, N.E. (eds) Semantic Multimedia. SAMT 2006. Lecture Notes in Computer Science, vol 4306. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11930334_14
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DOI: https://doi.org/10.1007/11930334_14
Publisher Name: Springer, Berlin, Heidelberg
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