摘要
将基于轮廓曲率的帧间几何形状约束势能,与目标区域信息和边缘梯度信息相结合,定义新的主动轮廓跟踪模型.该模型可以克服弱边缘及强背景等噪声对轮廓的吸引和干扰,同时保持目标的基本形状,实现和改善对具有尖角、深凹等不规则形状目标的边缘跟踪.采用基于块匹配的边界仿射变换方法对主动轮廓的初始位置进行估计,使其更接近目标的真实边缘.实验结果表明,该算法具有较好的边缘跟踪和抗复杂背景的能力.
A novel active contour model for object tracking based on shape restriction is presented in this paper. Contour curvature prior is used to define potential energy of shape restriction and then integrated with region and gradient information of image to formulate the active contour model for tracking. With curvature restriction, this model can correct the wrong deformation caused by weak gradient of object boundary and cluttered background. It also maintains the overall structure of object and tracks object with irregular shape in image sequences. Furthermore, the initial contour is estimated using affine transformation based on the block-matching. The model is applied to tracking IR car target in cluttered background and aircraft target in image sequences. Experimental results show that the proposed model has robust tracking performance in cluttered background and shape-preserving.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2006年第2期161-166,共6页
Pattern Recognition and Artificial Intelligence
基金
中国科学院科技创新基金(No.A010416)
关键词
主动轮廓模型
曲率
目标跟踪
形状约束势能
Active Contour Model, Curvature, Object Tracking, Potential Energy of Shape Restriction
