Abstract
The current skeletonisation algorithms, based on thinning, extract the morphological features of an object in an image but the skeletonized objects are coarsely presented. This paper proposes an algorithm which goes beyond that approach by changing the coarse line segments into perfect “straight” line segments, obtaining points, angles, line segment size and proportions. Our technique is applied in the post-processing phase of the skeleton, which improves it no matter which skeletonisation technique is used, as long as the structure is made with one-pixel width continuous line segments. This proposal is a first step towards human activity recognition through the analysis of human poses represented by their skeletons.
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Rojas-Albarracín, G., Carbajal, C.A., Fernández-Caballero, A., López, M.T. (2010). Skeleton Simplification by Key Points Identification. In: Martínez-Trinidad, J.F., Carrasco-Ochoa, J.A., Kittler, J. (eds) Advances in Pattern Recognition. MCPR 2010. Lecture Notes in Computer Science, vol 6256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15992-3_4
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