Keyframe-based recognition and localization during video-rate parallel tracking and mapping
Keyframe-based recognition and localization during video-rate parallel tracking and mapping
复制标题
视频速率并行跟踪和映射过程中基于关键帧的识别和定位
DOI：
10.1016/j.imavis.2011.05.002
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发表时间：
2011
期刊：
影响因子：
--
通讯作者：
D. W. Murray
中科院分区：
文献类型：
--
作者：
R. Castle;D. W. Murray
通过增强实时图像和配置场景信息来产生态势感知，从游戏到军事指挥和控制都有应用。我们提出了一种利用3D地图中关键帧相机姿态的SIFT特征三角测量的目标识别、重建和定位方法。在并行跟踪和映射算法中，通过对FAST图像特征的捆绑调整，以视频速率恢复地图和关键帧姿态本身。检测到的对象使用预定义的注释自动标记在用户的显示器上。实验结果给出了实验室场景，并在更现实的应用。
Generating situational awareness by augmenting live imagery with collocated scene information has applications from game-playing to military command and control. We propose a method of object recognition, reconstruction, and localization using triangulation of SIFT features from keyframe camera poses in a 3D map. The map and keyframe poses themselves are recovered at video-rate by bundle adjustment of FAST image features in the parallel tracking and mapping algorithm. Detected objects are automatically labeled on the user's display using predefined annotations. Experimental results are given for laboratory scenes, and in more realistic applications.