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	Object detection based on scale-invariant partial shape matching 期刊论文 OAI收割 Machine Vision and Applications, 2015, 卷号: 26, 期号: 6, 页码: 711-721 作者: Fan HJ(范慧杰); Cong Y(丛杨); Tang YD(唐延东) 收藏 \| 浏览/下载：24/0 \| 提交时间：2015/07/12 Shape descriptor Partial shape matching Object detection Shape category Scale-invariant
	Grassmann manifold based shape matching and retrieval under partial occlusions 会议论文 OAI收割 International Symposium on Optoelectronic Technology and Application 2014, Beijing, China, May 13-15, 2014 作者: Li CX(李晨曦); Shi ZL(史泽林); Liu YP(刘云鹏); Xu BS(徐保树) 收藏 \| 浏览/下载：27/0 \| 提交时间：2014/12/29 Grassmann manifold Partial shape matching contour matching partial occlusion affine invariant
	Global and Local Isometry-Invariant Descriptor for 3D Shape Comparison and Partial Matching 会议论文 OAI收割 San Francisco, California, 2010 作者: Huai-Yu Wu; Hongbin Zha; Tao Luo; Xu-Lei Wang; Songde MA \| 收藏 \| 浏览/下载：23/0 \| 提交时间：2016/10/20 Global And Local Isometry-invariant Descriptor For 3d Shape Comparison And Partial Matching
	Partial occlusion detection of object boundary (EI CONFERENCE) 会议论文 OAI收割 2009 IEEE Intrumentation and Measurement Technology Conference, I2MTC 2009, May 5, 2009 - May 7, 2009, Singapore, Singapore 作者: Zhang J.; Zhang K.; Zhang K.; Zhang K.; Zhang K. 收藏 \| 浏览/下载：28/0 \| 提交时间：2013/03/25 Partial occlusion is a difficult problem in computer vision since whether the object is changed or occluded is ambiguous especially when distinguishing it only from the object boundary. In this paper we proposed a novel idea to solve this problem by taking shape matching as a morphing processing. A mass-spring model is constructed from the point set which is sampled from a template (or reference) object boundary by moving it to a target object which is deformed and/or occluded. From the morphing processing sufficient information can be obtained and an accurate detection of occlusion is performed. By using of the proposed method the application scope of occlusion detection is expanded while other method cannot be performed which need color texture or motion information. The experiments performed on synthetic and real world images proved the satisfactory performance of the proposed method. 2009 IEEE.
	Integrated intensity, orientation code and spatial information for robust tracking (EI CONFERENCE) 会议论文 OAI收割 2007 2nd IEEE Conference on Industrial Electronics and Applications, ICIEA 2007, May 23, 2007 - May 25, 2007, Harbin, China 作者: Wang Y.; Wang Y.; Wang Y.; Wang Y.; Wang Y. 收藏 \| 浏览/下载：26/0 \| 提交时间：2013/03/25 real-time tracking is an important topic in computer vision. Conventional single cue algorithms typically fail outside limited tracking conditions. Integration of multimodal visual cues with complementary failure modes allows tracking to continue despite losing individual cues. In this paper we combine intensity orientation codes and special information to form a new intensity-orientation codes-special (IOS) feature to represent the target. The intensity feature is not affected by the shape variance of object and has good stability. Orientation codes matching is robust for searching object in cluttered environments even in the cases of illumination fluctuations resulting from shadowing or highlighting etc The spatial locations of the pixels are used which allow us to take into account the spatial information which is lost in traditional histogram. Histograms of intensity orientation codes and spatial information are employed for represent the target Mean shift algorithm is a nonparametric density estimation method. The fast and optimal mode matching can be achieved by this method. In order to reduce the compute time we use the mean shift procedure to reach the target localization. Experiment results show that the new method can successfully cope with clutter partial occlusions illumination change and target variations such as scale and rotation. The computational complexity is very low. If the size of the target is 3628 pixels it only needs 12ms to complete the method. 2007 IEEE.