Object detection using local difference patterns

Authors:
Satoshi Yoshinaga;Atsushi Shimada;Hajime Nagahara;Rin-ichiro Taniguchi
Affiliations:
Graduate School of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Japan;Graduate School of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Japan;Graduate School of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Japan;Graduate School of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Japan
Venue:
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part IV
Year:
2010

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Abstract

We propose a new method of background modeling for object detection. Many background models have been previously proposed, and they are divided into two types: "pixel-based models" which model stochastic changes in the value of each pixel and "spatial-based models" which model a local texture around each pixel. Pixel-based models are effective for periodic changes of pixel values, but they cannot deal with sudden illumination changes. On the contrary, spatial-based models are effective for sudden illumination changes, but they cannot deal with periodic change of pixel values, which often vary the textures. To solve these problems, we propose a new probabilistic background model integrating pixel-based and spatial-based models by considering the illumination fluctuation in localized regions. Several experiments show the effectiveness of our approach.