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Human gait identification using persistent homology


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Author: Lamar León, Javier
García Reyes, Edel
González Díaz, Rocío
Department: Universidad de Sevilla. Departamento de Matemática Aplicada I
Date: 2012
Published in: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, Lecture Notes in Computer Science, Vol. 7441 p. 244-251
Document type: Chapter of Book
Abstract: 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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