Department of Electrical Engineering, School of Electrical Engineering, Tel-Aviv University, Tel-Aviv, Israel.
IEEE Trans Pattern Anal Mach Intell. 2013 Oct;35(10):2513-25. doi: 10.1109/TPAMI.2013.46.
Image retargeting algorithms attempt to adapt the image content to the screen without distorting the important objects in the scene. Existing methods address retargeting of a single image. In this paper, we propose a novel method for retargeting a pair of stereo images. Naively retargeting each image independently will distort the geometric structure and hence will impair the perception of the 3D structure of the scene. We show how to extend a single image seam carving to work on a pair of images. Our method minimizes the visual distortion in each of the images as well as the depth distortion. A key property of the proposed method is that it takes into account the visibility relations between pixels in the image pair (occluded and occluding pixels). As a result, our method guarantees, as we formally prove, that the retargeted pair is geometrically consistent with a feasible 3D scene, similar to the original one. Hence, the retargeted stereo pair can be viewed on a stereoscopic display or further processed by any computer vision algorithm. We demonstrate our method on a number of challenging indoor and outdoor stereo images.
图像重定向算法试图在不扭曲场景中重要对象的情况下，将图像内容适配到屏幕上。现有的方法解决了单个图像的重定向问题。在本文中，我们提出了一种新的方法来重定向一对立体图像。简单地独立重定向每个图像会扭曲几何结构，从而损害场景的 3D 结构的感知。我们展示了如何扩展单个图像的 seam carving 来处理一对图像。我们的方法最小化了每个图像中的视觉失真以及深度失真。所提出方法的一个关键特性是，它考虑了图像对（遮挡和遮挡像素）之间的可见性关系。因此，我们的方法保证了，正如我们正式证明的那样，重定向后的对是与可行的 3D 场景一致的，类似于原始的。因此，可以在立体显示器上查看重定向的立体对，或者由任何计算机视觉算法进一步处理。我们在许多具有挑战性的室内和室外立体图像上展示了我们的方法。
