Higher order support tensor regression for head pose estimation

Conference paper


Guo, W., Kotsia, I. and Patras, I. 2011. Higher order support tensor regression for head pose estimation. 12th International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS 2011). Delft, The Netherlands 13 - 15 Apr 2011
TypeConference paper
TitleHigher order support tensor regression for head pose estimation
AuthorsGuo, W., Kotsia, I. and Patras, I.
Abstract

In this paper, we exploit the advantages of tensor representations and propose a Supervised Multilinear Learning Model for regression. The model is based on the Canonical (CAN-DECOMP)/Parallel Factors (PARAFAC) decomposition of tensors of multiple modes and allows the simultaneous projection of an input tensor to more than one discriminative directions along each mode. These projection weights are obtained by optimizing a ϵ-insensitive loss functions which leads to generalized Support Tensor Regression (STR). The methods are validated on the problems of head pose estimation using real data from publicly available databases.

Research GroupResearch Group on Development of Intelligent Environments
Conference12th International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS 2011)
Publication process dates
Deposited27 Nov 2012
Output statusPublished
LanguageEnglish
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https://repository.mdx.ac.uk/item/83wvz

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