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An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition

Abstract: 

In this paper, we examine the problem of modeling overdispersed frequency vectors that are naturally generated by several machine learning and computer vision applications.
We consider a statistical framework based on a mixture of Multinomial Scaled Dirichlet (MSD) distributions that we have previously proposed in [1]. Given that the likelihood function plays a key role in statistical inference, e.g. in maximum likelihood estimation and Fisher information matrix investigation, we propose to improve the efficiency of computing the MSD log-likelihood by approximating its function based on Bernoulli polynomials. As compared to [1], the log-likelihood function is computed using the proposed mesh algorithm and a model selection approach is seamlessly integrated with the parameters estimation. The improved clustering framework offers a good compromise between other techniques and improves the approach used before for the same model. The merits of the proposed approach are validated via a challenging application that involves human action recognition.

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Paper Details

Authors:
Nuha Zamzami, and Nizar Bouguila
Submitted On:
9 November 2019 - 7:05am
Short Link:
Type:
Poster
Event:
Presenter's Name:
Nizar Bouguila
Paper Code:
1570561537
Document Year:
2019
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Document Files

MSD_Mesh.pdf

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[1] Nuha Zamzami, and Nizar Bouguila , "An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4939. Accessed: Nov. 11, 2019.
@article{4939-19,
url = {http://sigport.org/4939},
author = {Nuha Zamzami; and Nizar Bouguila },
publisher = {IEEE SigPort},
title = {An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition},
year = {2019} }
TY - EJOUR
T1 - An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition
AU - Nuha Zamzami; and Nizar Bouguila
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4939
ER -
Nuha Zamzami, and Nizar Bouguila . (2019). An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition. IEEE SigPort. http://sigport.org/4939
Nuha Zamzami, and Nizar Bouguila , 2019. An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition. Available at: http://sigport.org/4939.
Nuha Zamzami, and Nizar Bouguila . (2019). "An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition." Web.
1. Nuha Zamzami, and Nizar Bouguila . An Accurate Evaluation of MSD Log-likelihood and its Application in Human Action Recognition [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4939