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Optimizing Orthonormal Basis Bilinear Spatiotemporal Representation for Motion Data

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 391))

Abstract

The paper describes an attempt to estimate the optimal division of a number of base vectors between space (shape) and time (trajectory) for bilinear spatio-temporal representation of motion capture data. The spatiotemporal model is a matrix consisting of \(K_s \cdot K_t\) amount of coefficients. In the paper we discuss using of orthonormal spatial and temporal basis: PCA-PCA, DCT-DCT, PCA-DCT and DCT-PCA to represent real MoCap data.

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Acknowledgments

This research has been supported by Demonstrator \(+\) Programme of NCRD. Project UOD-DEM-1–183/001 “System inteligentnej analizy wideo do rozpoznawania zachowań i sytuacji w sieciach monitoring”.

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Correspondence to Przemysław Skurowski .

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Skurowski, P., Socała, J., Wojciechowski, K. (2016). Optimizing Orthonormal Basis Bilinear Spatiotemporal Representation for Motion Data. In: Gruca, A., Brachman, A., Kozielski, S., Czachórski, T. (eds) Man–Machine Interactions 4. Advances in Intelligent Systems and Computing, vol 391. Springer, Cham. https://doi.org/10.1007/978-3-319-23437-3_31

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  • DOI: https://doi.org/10.1007/978-3-319-23437-3_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23436-6

  • Online ISBN: 978-3-319-23437-3

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