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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 1 .

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