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Multiple metric learning for graph based human pose estimation
, Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Daegu, Korea ; Volume 8228 LNCS, Issue PART 3 , November , 2013 , Pages 200-208 ; 03029743 (ISSN) ; 9783642420504 (ISBN) ; Gozlou, M. G ; Shalmani, M. T. M ; Sharif University of Technology
2013
Abstract
In this paper, a multiple metric learning scheme for human pose estimation from a single image is proposed. Here, we focused on a big challenge of this problem which is; different 3D poses might correspond to similar inputs. To address this ambiguity, some Euclidean distance based approaches use prior knowledge or pose model that can work properly, provided that the model parameters are being estimated accurately. In the proposed method, the manifold of data is divided into several clusters and then, we learn a new metric for each partition by utilizing not only input features, but also their corresponding poses. The manifold clustering allows the decomposition of multiple manifolds into a...