Human gait identification using persistent homology
This paper shows an image/video application using topological invariants for human gait recognition. Using a background subtraction approach, a stack of silhouettes is extracted from a subsequence and glued through their gravity centers, forming a 3D digital image I. From this 3D representation, the...
| Autores: | , , |
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| Tipo de documento: | capítulo de livro |
| Data de publicação: | 2012 |
| País: | España |
| Recursos: | Universidad de Sevilla (US) |
| Repositório: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/30814 |
| Acesso em linha: | http://hdl.handle.net/11441/30814 https://doi.org/10.1007/978-3-642-33275-3_30 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Pattern Recognition Image Processing and Computer Vision Artificial Intelligence (incl. Robotics) Biometrics Algorithm Analysis and Problem Complexity Information Systems Applications (incl. Internet) |
| Resumo: | This paper shows an image/video application using topological invariants for human gait recognition. Using a background subtraction approach, a stack of silhouettes is extracted from a subsequence and glued through their gravity centers, forming a 3D digital image I. From this 3D representation, the border simplicial complex ∂ K(I) is obtained. We order the triangles of ∂ K(I) obtaining a sequence of subcomplexes of ∂ K(I). The corresponding filtration F captures relations among the parts of the human body when walking. Finally, a topological gait signature is extracted from the persistence barcode according to F. In this work we obtain 98.5% correct classification rates on CASIA-B database. |
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