Histogram of Body Poses and Spectral Regression Discriminant Analysis for Human Action Categorization

Shao, Ling and Chen, Xiuli (2010) Histogram of Body Poses and Spectral Regression Discriminant Analysis for Human Action Categorization. In: BMVC 2010 - 21st British Machine Vicion Conference, 31st August - 3rd September 2010, Aberystwyth, UK.

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Abstract

This paper explores a recently proposed and rarely reported subspace learning method, Spectral Regression Discriminant Analysis (SRDA), on silhouette based human action recognition. The recognition algorithm adopts the Bag of Words (BoW) model combined with the action representation based on Histogram of Body Poses sampled from silhouettes in the video sequence. In addition, we compare the performance of SRDA for dimensionality reduction with several traditional subspace learning methods, such as Principle Component Analysis (PCA), supervised Locality Preserving Projections (LPP), unsupervised LPP and Neighbourhood Preserving Embedding (NPE). Experimental results show that Histogram of Human Poses combined with SRDA or its kernel version, SRKDA, can achieve 100% recognition accuracy for the Weizmann human action dataset, which is better than any published results on the same dataset.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	G400 Computer Science
Department:	Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User:	Paul Burns
Date Deposited:	17 Jun 2015 10:13
Last Modified:	13 Oct 2019 00:31
URI:	http://nrl.northumbria.ac.uk/id/eprint/22980

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