基于遮挡区域建模和目标运动估计的动态遮挡规避方法

Dynamic Occlusion Avoidance Approach by Means of Occlusion Region Model and Object Motion Estimation

对于运动视觉目标,如何对遮挡区域进行规避是视觉领域一个具有挑战性的问题.本文提出了一种新颖的基于运动视觉目标深度图像利用遮挡信息实现动态遮挡规避的方法.该方法主要利用遮挡区域最佳观测方位模型和视觉目标运动估计方程,通过合理规划摄像机的观测方位逐渐完成对遮挡区域的观测.主要贡献在于:1)提出了深度图像遮挡边界中关键点的概念,利用其构建关键线段对遮挡区域进行快速建模; 2)基于关键线段和遮挡区域建模结果,提出了一种构建遮挡区域最佳观测方位模型的方法; 3)提出一种混合曲率特征,通过计算深度图像对应的混合曲率矩阵,增加了图像匹配过程中提取特征点的数量,有利于准确估计视觉目标的运动.实验结果验证了所提方法的可行性和有效性.

How to avoid the occlusion region of a moving visual object is a challenging problem in the visual field.Based on the occlusion information in the depth image of a moving visual object, this paper proposes a novel dynamic occlusion avoidance approach which plans the camera position by utilizing the best view model of occlusion area and the visual target motion estimation equation. This work has three contributions. The first one is the concept of key point,which constitutes the key line segment to construct the model of occlusion region. The second one is the approach for constructing the best view model of occlusion region based on the key line segment and the occlusion region model. The third one is the feature of mixed curvature. The number of feature points extracted in the process of image matching is increased by calculating the mixed curvature matrix corresponding to the depth image, which is conducive to estimating motion of visual object accurately. Experimental results demonstrate the feasibility and effectiveness of the proposed approach.