论文标题
跨摄像机视图反映识别
Cross-Camera View-Overlap Recognition
论文作者
论文摘要
我们提出了一个分散的视图范围识别框架，该框架在不需要参考3D地图的情况下自由移动的摄像机运行。每个摄像机都独立提取，汇总为层次结构，并随着时间的推移共享特征点描述符。视图匹配和几何验证可以丢弃错误匹配的视图来确认视图重叠。提出的框架是通用的，可以与不同的描述符一起使用。我们对公共可用序列以及使用手持摄像机收集的新序列进行实验。我们表明，与NetVlad，Rootsift和Superglue相比，在提议的框架内带有二进制单词的快速和旋转简短（ORB）特征，可提高精度和更高或类似的精度。
We propose a decentralised view-overlap recognition framework that operates across freely moving cameras without the need of a reference 3D map. Each camera independently extracts, aggregates into a hierarchical structure, and shares feature-point descriptors over time. A view overlap is recognised by view-matching and geometric validation to discard wrongly matched views. The proposed framework is generic and can be used with different descriptors. We conduct the experiments on publicly available sequences as well as new sequences we collected with hand-held cameras. We show that Oriented FAST and Rotated BRIEF (ORB) features with Bags of Binary Words within the proposed framework lead to higher precision and a higher or similar accuracy compared to NetVLAD, RootSIFT, and SuperGlue.
