Gender Classification from Pose-Based GEIs
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Scholar |
Otros documentos de la autoría: Martín Félez, Raúl; Mollineda, Ramón A.; Sánchez Garreta, Josep Salvador
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Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7038
comunitat-uji-handle3:10234/54899
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http://dx.doi.org/10.1007/978-3-642-33564-8_60 |
Metadatos
Título
Gender Classification from Pose-Based GEIsFecha de publicación
2012Editor
Springer Berlin HeidelbergISBN
978-3-642-33563-1ISSN
0302-9743; 1611-3349Cita bibliográfica
Martín Félez, Raúl ; Mollineda, Ramón; Sánchez, J. Salvador. " Gait Recognition by Ranking". En: Computer Vision and Graphics – International Conference, ICCVG 2012, Warsaw, Poland, September 24-26, 2012. Proceedings / Bolc, Leonard [et al.] (Eds.). Berlin : Springer, 2012. (Lecture Notes in Computer Science; 7594) . ISBN: 978-3-642-33563-1, pp. 501-508Tipo de documento
info:eu-repo/semantics/bookPartVersión de la editorial
http://link.springer.com/chapter/10.1007%2F978-3-642-33564-8_60Palabras clave / Materias
Resumen
This paper introduces a new approach for gait-based gender classification in which some key biomechanical poses of a gait pattern are represented by partial Gait Energy Images (GEIs). These pose-based GEIs can more ... [+]
This paper introduces a new approach for gait-based gender classification in which some key biomechanical poses of a gait pattern are represented by partial Gait Energy Images (GEIs). These pose-based GEIs can more accurately represent the shape of the body parts and some dynamic features with respect to the usually blurred depiction provided by a general GEI comprising all poses. Gait-based gender classification is based on the weighted decision fusion of the pose-based GEIs. Results of experiments on two large gait databases prove that this method performs significantly better than clasiffiers based on the original GEI. [-]
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