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Gait-based gender classification using persistent homology


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dc.creator Lamar León, Javier
dc.creator Cerri, Andrea
dc.creator García Reyes, Edel
dc.creator González Díaz, Rocío 2015-11-23T11:06:02Z 2015-11-23T11:06:02Z 2013
dc.description.abstract In this paper, a topological approach for gait-based gender recognition is presented. First, a stack of human silhouettes, extracted by background subtraction and thresholding, were glued through their gravity centers, forming a 3D digital image I. Second, different filters (i.e. particular orders of the simplices) are applied on ∂ K(I) (a simplicial complex obtained from I) which capture relations among the parts of the human body when walking. Finally, a topological signature is extracted from the persistence diagram according to each filter. The measure cosine is used to give a similarity value between topological signatures. The novelty of the paper is a notion of robustness of the provided method (which is also valid for gait recognition). Three experiments are performed using all human-camera view angles provided in CASIA-B database. The first one evaluates the named topological signature obtaining 98.3% (lateral view) of correct classification rates, for gender identification. The second one shows results for different human-camera distances according to training and test (i.e. training with a human-camera distance and test with a different one). The third one shows that upper body is more discriminative than lower body. es
dc.format application/pdf es
dc.language.iso eng es
dc.relation.ispartof Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, Lecture Notes in Computer Science, Vol. 8259 p. 366-373 es
dc.rights Atribución-NoComercial-CompartirIgual 4.0 Internacional *
dc.rights.uri *
dc.subject gait-based es
dc.subject recognition topology es
dc.subject persistent homology es
dc.subject gender classification es
dc.title Gait-based gender classification using persistent homology es
dc.type info:eu-repo/semantics/bookPart es
dc.rights.accessrights info:eu-repo/semantics/openAccess es
dc.contributor.affiliation Universidad de Sevilla. Departamento de Matemática Aplicada I es
dc.identifier.doi es
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