关键词: 编组元提取, 运动特征, 轮廓编组, 全局运动对比度

Abstract: In contour grouping computational models, the extraction of group-meta set has an important influence on the grouping result. In this paper, a group-meta set extraction algorithm based on global motion contrast is presented for the confusion of target and non-target edge fragments in complex scenes. It introduces similarity metrics for two edge segments based on motion features. Most of non-target edge fragments are removed from the original group-meta set on the basis of the definition for global motion contrast. And a group-meta set consisting of more target edge fragments and few non-target edge fragments is extracted. The method is tested on Moseg_dataset and it is compared with the methods based on edge detection and boundary detection. And the experiment results show substantial improvements in the scale and effectiveness for the extraction of group-meta set by this method. Further, it conducts groping experiments by the same grouping method for evaluation and comparison. Grouping results show that this method significantly outperforms previous algorithms.

Key words: extraction of group-meta, motion features, contour grouping, global motion contrast