Wide-angle vision and sensing using artificial intelligence, machine learning and neural networks

该项目的工业合作伙伴ImmerVision专门从事新型广角**全景光学和软件技术的开发。在寻求为客户提供额外价值的过程中，他们**希望在他们的产品中加入更多的“智能”。特别令人感兴趣的是，他们希望能够**从一个相机估计深度，因此自然而然地转向深度学习方法，**最近在这项任务上取得了重大进展。不幸的是，所有这些技术**都是为具有更“传统”视场(即通常在60度至90度**的水平视场)的相机开发的，不能“按原样”应用于通常表现出**显著失真的广角图像，尤其是在图像的边缘。此外，它们不能直接在**广角图像上重新训练，因为不存在既有广角图像又有相应深度**信息的数据集。在这个项目中，我们的目标是开发一种新的深度学习算法，从室外场景的单目广角图像中估计**深度。

The industrial partner in this project, ImmerVision, specializes in the development of novel wide-angle**panoramic optical and software technologies. In their quest to provide additional value to their customers, they**wish to include additional "intelligence" to their products. Of particular interest, they wish to allow the**estimation of depth from a single camera, and are thus naturally turning towards deep learning approaches,**which have shown significant progress at this task in the recent. Unfortunately, all of these techniques have**been developed for cameras with more "traditional" fields of view (i.e. typically ranging from 60 to 90 degrees**of horizontal field of view), and cannot be applied "as is" for wide-angle images which typically exhibit**significant distortions, especially at the edges of the image. In addition, they cannot be re-trained directly on**wide-angle imagery, because there exists no dataset where both wide-angle images and corresponding depth**information is available. In this project, our objective is to develop a novel deep learning algorithm to estimate**depth from a monocular wide-angle image of an outdoor scene.