Advertisement
Published in:
2011 | OriginalPaper | Chapter
Object Detection Using Local Difference Patterns
Authors : Satoshi Yoshinaga, Atsushi Shimada, Hajime Nagahara, Rin-ichiro Taniguchi
Published in: Computer Vision – ACCV 2010
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
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.