This paper presents a successful connection of different sequence alignment algorithms with Bag of Visual Words concept for image classification. In particular, sequences were created on the basis of dense SIFT descriptors, for which different types of sequence orderings were proposed. Then, the similarities between images were calculated with two different sequence alignment algorithms. Finally, the SVM algorithm was proposed as a classifier. The obtained results showed that both sequence alignment algorithms obtain very similar results and that the type of ordering affects the accuracy very slightly. © 2014 Springer International Publishing.
CITATION STYLE
Drozda, P., Sopyła, K., & Górecki, P. (2014). Different orderings and visual sequence alignment algorithms for image classification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8467 LNAI, pp. 693–702). Springer Verlag. https://doi.org/10.1007/978-3-319-07173-2_59
Mendeley helps you to discover research relevant for your work.