点评：一种基于深度的视频感兴趣区域提取方法，优点在于联合利用了时间上同步的纹理视频帧和纹理视频帧对应的深度视频帧，首先获取纹理视频帧的运动区域和轮廓纹理的二值掩模图像及深度视频帧的各个深度层和深度不连续区域的二值掩模图像，然后获取各个深度层的各个深度对象层的二值掩模图像，及各个深度层的轮廓特征区域的二值掩模图像，再以各个深度层的轮廓特征区域的二值掩模图像为特征，对各个深度对象层的二值掩模图像进行扫描，得到各个深度对象层的二值掩模图像中的感兴趣区域，最后叠加各个深度对象层的二值掩模图像中的感兴趣区域得到纹理视频帧的感兴趣区域，通过该方法获取的感兴趣区域符合语义特征，计算复杂度低且精度较高。

Comment: The invention discloses a video area-of-interest exacting method based on depth; the invention has the advantages of associatively utilizing texture video frame and depth video frame corresponding to the texture video frame, both of the texture video frame and the depth video frame are synchronous on time; the method comprises the steps as follows: firstly obtaining motion region of the texture video frame and binary mask image of contour texture, and each depth layer of the depth video frame and binary mask image of depth discontinuous regions, then obtaining the binary mask image of each depth object layer of each depth layer, and the binary mask image of contour feature region of each depth layer, then taking the binary mask image of contour feature region of each depth layer as feature, for scanning the binary mask image of each depth object layer, obtaining the area-of-interest in the binary mask image of each depth object layer, finally stacking the area-of-interest in the binarymask image of each depth object layer to obtain the area-of-interest of the texture video frame; the area-of-interest obtained by the method conforms to the semantic feature and has low calculating complexity and high precision.