電気学会論文誌C(電子・情報・システム部門誌)
Online ISSN : 1348-8155
Print ISSN : 0385-4221
ISSN-L : 0385-4221
<音声画像処理・認識>
確率モデルと予測モデルを組み合わせたハイブリッド型動的背景モデルによる高速省メモリな物体検出
島田 敬士谷口 倫一郎
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ジャーナル フリー

2009 年 129 巻 5 号 p. 846-852

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抄録
We propose a new method to create adaptive background models. Traditionally, each pixel has an adaptive background model which consists of Gaussian mixtures. Each model can approximate small changes and periodic changes of pixel values and it helps us to detect moving objects. However, it cannot adapt to some illumination changes such as gradually varying illumination, precipitously varying illumination and so on. The other model such as using a texture or using prediction of pixel value is effective to handle these changes. Therefore, a hybrid background model which is combined with more than two kind of models. In our approach, we use two different types of the background model. The one is the stochastic background model. The other is the predictive background model based on the exponential smoothing.
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© 電気学会 2009
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