论文标题
以对象为中心的图像缝合
Object-centered image stitching
论文作者
论文摘要
图像缝合通常分解为三个阶段：注册，将源图像与共同的目标图像对齐；接缝查找，确定每个目标像素的源图像应来自的源图像；和混合，使缝隙过渡平滑。如[1]中所述，接缝查找阶段尝试将接缝在像素之间放置在源图像之间的过渡之间并不明显。在这里，我们观察到，当物体被裁剪，省略或重复时，这种方法最有问题的失败发生。因此，我们采用以对象为中心的方法来解决对象检测的最新进展[2,3,4]。我们通过修改接缝查找阶段中使用的能量函数来对候选解决方案进行惩罚。这会在具有挑战性的图像上产生更现实的缝线结果。另外，这些方法可用于确定输入数据中何时进行不可恢复的遮挡，还提出了一个简单的评估指标，可用于评估缝合算法的输出。
Image stitching is typically decomposed into three phases: registration, which aligns the source images with a common target image; seam finding, which determines for each target pixel the source image it should come from; and blending, which smooths transitions over the seams. As described in [1], the seam finding phase attempts to place seams between pixels where the transition between source images is not noticeable. Here, we observe that the most problematic failures of this approach occur when objects are cropped, omitted, or duplicated. We therefore take an object-centered approach to the problem, leveraging recent advances in object detection [2,3,4]. We penalize candidate solutions with this class of error by modifying the energy function used in the seam finding stage. This produces substantially more realistic stitching results on challenging imagery. In addition, these methods can be used to determine when there is non-recoverable occlusion in the input data, and also suggest a simple evaluation metric that can be used to evaluate the output of stitching algorithms.
