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http://hdl.handle.net/10553/15753
Title: | Evaluation of LBP and HOG descriptors for clothing attribute description | Authors: | Lorenzo Navarro, José Javier Castrillón-Santana, Modesto Ramón Balmaseda, Enrique José Freire, David |
UNESCO Clasification: | 120304 Inteligencia artificial | Keywords: | LBP HOG Clothing description |
Issue Date: | 2014 | Publisher: | Springer | Journal: | Lecture Notes in Computer Science | Conference: | 1st International Workshop on Video Analytics for Audience Measurement (VAAM 2014) | Abstract: | In this work an experimental study about the capability of the LBP, HOG descriptors and color for clothing attribute classification is presented. Two different variants of the LBP descriptor are considered, the original LBP and the uniform LBP. Two classifiers, Linear SVM and Random Forest, have been included in the comparison because they have been frequently used in clothing attributes classification. The experiments are carried out with a public available dataset, the clothing attribute dataset, that has 26 attributes in total. The obtained accuracies are over 75% in most cases, reaching 80% for the necktie or sleeve length attributes. | URI: | http://hdl.handle.net/10553/15753 | ISBN: | 978-3-319-12810-8 | ISSN: | 0302-9743 | DOI: | 10.1007/978-3-319-12811-5_4 | Source: | Video Analytics for Audience Measurement. VAAM 2014. Lecture Notes in Computer Science, v. 8811 LNCS, p. 53-65 (2014) |
Appears in Collections: | Capítulo de libro |
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