@article{ref1,
title="Improvement of infant's action recognition accuracy by Bayesian estimation method introducing Bayesian Network : Experimental evaluation with supersonic sensor and camera images",
journal="IEICE technical report (HCS)",
year="2011",
author="Ishikawa, Shouzou and Motomura, Yoichi and Nishida, Yoshifumi and Shouno, Hayaru",
volume="110",
number="461",
pages="137-142",
abstract="The purpose of this study is to prevent accident in infants. Therefore, we consider analysis the action of the behavior in the everyday life from several types of sensors. Conventional action recognition has been done only from the image. WWe propose applying additional information, which we treat as the prior distribution in the meaning of the Bayes inference, observed from the supersonic sensors. Prior distribution use Bayesian network formulation in the observation data. Likelihood function calculates maximum likelihood estimation method in feature extraction of images. In this paper, we consider feature extraction candidates as HLAC, SIFT, and 3D SIFT, and compare the performance of them. We estimate behavior labels by this method. Then, we performed a comparison experiment to inference a behavior labels by this method.Language: ja<p />",
language="",
issn="0913-5685",
doi="",
url="http://dx.doi.org/"
}