论文标题
一种直接姿势估计的结构感知方法
A Structure-Aware Method for Direct Pose Estimation
论文作者
论文摘要
从单个图像中估算摄像头姿势是计算机视觉中的基本问题。解决此任务的现有方法属于两个不同的类别，我们将其称为直接和间接。直接方法（例如Posenet），将图像从图像中回归为固定函数，例如使用馈送卷积网络。这种方法是可取的，因为它们是确定性的，并且在恒定时间内运行。姿势回归的间接方法通常是非确定性的，具有各种外部依赖性，例如图像检索和假设采样。我们提出了一种直接的方法，该方法从基于结构的方法中获取灵感，以将显式3D约束纳入网络。我们的方法保持了其他直接方法的理想品质，同时总体上达到了较低的错误。
Estimating camera pose from a single image is a fundamental problem in computer vision. Existing methods for solving this task fall into two distinct categories, which we refer to as direct and indirect. Direct methods, such as PoseNet, regress pose from the image as a fixed function, for example using a feed-forward convolutional network. Such methods are desirable because they are deterministic and run in constant time. Indirect methods for pose regression are often non-deterministic, with various external dependencies such as image retrieval and hypothesis sampling. We propose a direct method that takes inspiration from structure-based approaches to incorporate explicit 3D constraints into the network. Our approach maintains the desirable qualities of other direct methods while achieving much lower error in general.
