作者
Ren, Malik
发表日期
2003/10/13
期刊
Proceedings ninth IEEE international conference on computer vision
页码范围
10-17 vol. 1
出版商
IEEE
简介
We propose a two-class classification model for grouping. Human segmented natural images are used as positive examples. Negative examples of grouping are constructed by randomly matching human segmentations and images. In a preprocessing stage an image is over-segmented into super-pixels. We define a variety of features derived from the classical Gestalt cues, including contour, texture, brightness and good continuation. Information-theoretic analysis is applied to evaluate the power of these grouping cues. We train a linear classifier to combine these features. To demonstrate the power of the classification model, a simple algorithm is used to randomly search for good segmentations. Results are shown on a wide range of images.
引用总数
学术搜索中的文章
Ren, Malik - Proceedings ninth IEEE international conference on …, 2003