Martins André T, Aguiar Pedro M Q, Figueiredo Mário A T
Department of Electrical and Computer Engineering, Instituto Superior Técnico, Technical University of Lisbon, 1049-001 Lisboa, Portugal.
IEEE Trans Pattern Anal Mach Intell. 2005 May;27(5):822-7. doi: 10.1109/TPAMI.2005.107.
The problem of inferring 3D orientation of a camera from video sequences has been mostly addressed by first computing correspondences of image features. This intermediate step is now seen as the main bottleneck of those approaches. In this paper, we propose a new 3D orientation estimation method for urban (indoor and outdoor) environments, which avoids correspondences between frames. The scene property exploited by our method is that many edges are oriented along three orthogonal directions; this is the recently introduced Manhattan world (MW) assumption. The main contributions of this paper are: the definition of equivalence classes of equiprojective orientations, the introduction of a new small rotation model, formalizing the fact that the camera moves smoothly, and the decoupling of elevation and twist angle estimation from that of the compass angle. We build a probabilistic sequential orientation estimation method, based on an MW likelihood model, with the above-listed contributions allowing a drastic reduction of the search space for each orientation estimate. We demonstrate the performance of our method using real video sequences.
从视频序列推断相机三维方向的问题，大多是通过首先计算图像特征的对应关系来解决的。现在，这一步骤被视为这些方法的主要瓶颈。在本文中，我们提出了一种针对城市（室内和室外）环境的新的三维方向估计方法，该方法避免了帧之间的对应关系。我们的方法所利用的场景特性是，许多边缘沿着三个正交方向排列；这就是最近引入的曼哈顿世界（MW）假设。本文的主要贡献包括：定义等投影方向的等价类，引入新的小旋转模型，将相机平稳移动这一事实形式化，以及将仰角和扭转角估计与罗盘角估计解耦。我们基于MW似然模型构建了一种概率性顺序方向估计方法，上述贡献使得每次方向估计的搜索空间大幅减少。我们使用真实视频序列展示了我们方法的性能。
