Improving bag of visual words representations with genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{Escalante:2015:IJCNN,

• author = "Hugo Jair Escalante and Jose Martinez-Carraza and Sergio Escalera and Victor Ponce-Lopez and Xavier Baro",
• booktitle = "2015 International Joint Conference on Neural Networks (IJCNN)",
• title = "Improving bag of visual words representations with genetic programming",
• year = "2015",
• abstract = "The bag of visual words is a well established representation in diverse computer vision problems. Taking inspiration from the fields of text mining and retrieval, this representation has proved to be very effective in a large number of domains. In most cases, a standard term-frequency weighting scheme is considered for representing images and videos in computer vision. This is somewhat surprising, as there are many alternative ways of generating bag of words representations within the text processing community. This paper explores the use of alternative weighting schemes for landmark tasks in computer vision: image categorization and gesture recognition. We study the suitability of using well-known supervised and unsupervised weighting schemes for such tasks. More importantly, we devise a genetic program that learns new ways of representing images and videos under the bag of visual words representation. The proposed method learns to combine term-weighting primitives trying to maximize the classification performance. Experimental results are reported in standard image and video data sets showing the effectiveness of the proposed evolutionary algorithm.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/IJCNN.2015.7280799",
• ISSN = "2161-4393",
• month = jul,
• notes = "Also known as \cite{7280799}",

}

Genetic Programming entries for Hugo Jair Escalante Jose Martinez-Carraza Sergio Escalera Victor Ponce-Lopez Xavier Baro

Citations