By Pavel Herrera-Domínguez, Leopoldo Altamirano-Robles (auth.), José Francisco Martínez-Trinidad, Jesús Ariel Carrasco-Ochoa, Josef Kittler (eds.)
This ebook constitutes the completely refereed court cases of the second one Mexican convention on trend attractiveness, MCPR 2010, held in Puebly, Mexico, in September 2010. The 39 revised papers have been rigorously reviewed and chosen from 89 submissions and are prepared in topical sections on laptop imaginative and prescient and robotics, photograph processing, neural networks and sign processing, development popularity, information mining, usual language and rfile processing.
Read or Download Advances in Pattern Recognition: Second Mexican Conference on Pattern Recognition, MCPR 2010, Puebla, Mexico, September 27-29, 2010. Proceedings PDF
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Additional resources for Advances in Pattern Recognition: Second Mexican Conference on Pattern Recognition, MCPR 2010, Puebla, Mexico, September 27-29, 2010. Proceedings
A. Carrasco-Ochoa et al. ): MCPR 2010, LNCS 6256, pp. 30–39, 2010. c Springer-Verlag Berlin Heidelberg 2010 Skeleton Simpliﬁcation by Key Points Identiﬁcation 31 which are valid and feasible results for image analysis. The algorithm was tested using two well-known skeletonisation algorithms in diﬀerent images obtained from diﬀerent sources by applying a pre-processing. This proposal is an initial step towards human activity recognition through the analysis of human poses represented by their skeletons.
So we write f −1 (Uα ) = i=1 V (α, i), where jα is the number of connected components in f −1 (Uα ). That is to say, we have located a covering f −1 (Uα ) for X, and we refer to f as a ﬁlter. Our aim in this paper is to represent facial shape using simplicial complexes. In other words, we reduce high dimensional data sets into simplicial complexes with a signiﬁcant reduction in the number of points needed to represent the topological and geometric information at a speciﬁed resolution. To this end, we subsample from the facial shape to reduce the number of points.
We can interpret these features by thinking of the graph as a scaﬀold for a higher-dimensional object. So to go from a point cloud to a simplicial complex is to embed the point cloud in a piecewise space constructed from simplicies identiﬁed (combinatorially) with the faces of the graph. The freedom of choice as to how to ﬁll in the higher dimensional simplicies of the proximity graph allows for diﬀerent global representations. A natural method for ˇ so doing is using Cech theory . To do so we make use of the Rips complex, which is the abstract simplicial complex whose k-simplices correspond to unordered (k + 1)-tuples of the point cloud which are within a pairwise distance .