计算机工程2016，Vol.42Issue(11)：261-266,6.DOI:10.3969/j.issn.1000-3428.2016.11.043
基于隐式模型表示的对称物体检测算法
Symmetric Object Detection Algorithm Based on Implicit Model Representation
摘要
Abstract
This paper proposes a novel image rotation object detection algorithm,which is especially suitable to detect objects having non-regular and random rotation symmetry characteristics in real-world images.Based on the implicit model representation,the algorithm counts the spatial distribution of the key points in the image and estimate the rotation center of the object.The algorithm extracts the visual interesting points from the image middle-level features.The unsupervised learning is employed in the key point feature space,aiming at labeling each position of the key points as one of the symmetry feature clusters.Thereby the probability map for center is gained by summing all the values voted in every cluster under some given radius.The maps are weighted summed together to obtain the global rotation center probability map,and the coordinates of the rotation center are achieved by saliency detection method on the map. Experimental results show that the algorithm can effectively detect the irregular rotational symmetry objects in real-world images,and it also has a higher accuracy for the estimation of the rotational symmetry center.关键词
素描令牌/旋转对称/隐式模型/视觉显著性/目标检测/旋转对称簇Key words
sketch token/rotational symmetry/implicit model/visual saliency/object detection/rotationally symmetric cluster分类
信息技术与安全科学引用本文复制引用
余水能,魏宁,董方敏..基于隐式模型表示的对称物体检测算法[J].计算机工程,2016,42(11):261-266,6.基金项目
国家自然科学基金“基于全投影域的医学图像多分辨率非刚性配准方法研究”（61202141）；国家自然科学基金资助面上项目（61272236，61272237）；湖北省自然科学基金（2015CFA025）。 （）
