光学学报, 2018, 38 (12): 1212002, 网络出版: 2019-05-10
基于语义目标匹配的三维跟踪注册方法 下载: 825次
Three-Dimensional Tracking Registration Method Based on Semantic Object Matching
测量 增强现实 语义分割 相机姿态估计 三维跟踪注册 measurement augmented reality semantic segmentation camera pose estimation three-dimensional tracking registration
摘要
提出了一种基于语义目标匹配的三维跟踪注册方法。通过改进的单发多框检测(SSD)深度卷积神经网络对图像进行语义分割,获取场景中不同目标的像素级语义分割结果。在求取相机姿态的目标函数时,融合了图像的灰度约束与几何约束对相机的姿态进行估计。所提方法减小了特征点的缺乏或误匹配问题对三维跟踪注册算法性能的影响,且能够适应不同结构的场景。研究结果表明,该方法的误差不超过2.2 pixel,基本满足了实时性的要求。
Abstract
A three-dimensional (3D) tracking registration method is proposed based on the semantic object matching. The improved single-shot multi-box detector (SSD) deep convolution neural network is used to segment images semantically and thus the pixel level semantic segmentation results for different objects in the scene are obtained. To solve the object function of the camera pose, the camera pose is estimated by the combination of the gray and the geometric constraints of images. The proposed method not only reduces the influence of the lack or mismatch of feature points on the performance of 3D tracking registration algorithm, but also it can adapt to the scenes with different structures. The research results show that the error of this proposed method is less than 2.2 pixel, which basically satisfies the requirement of real-time.
安喆, 徐熙平, 杨进华, 刘洋, 闫宇轩. 基于语义目标匹配的三维跟踪注册方法[J]. 光学学报, 2018, 38(12): 1212002. Zhe An, Xiping Xu, Jinhua Yang, Yang Liu, Yuxuan Yan. Three-Dimensional Tracking Registration Method Based on Semantic Object Matching[J]. Acta Optica Sinica, 2018, 38(12): 1212002.