CodeSLAM — Learning a Compact, Optimisable Representation for Dense Visual SLAM
Abstract
While each keyframe with a code can
produce a depth map, the code can be optimised efficiently jointly with pose variables and together with the codes of overlapping keyframes to attain global consistency
对关键帧进行编码,跟姿态和重叠的关键帧一起优化
contributions
- The derivation of a compact and optimisable representation of dense geometry by conditioning a depth autoencoder on intensity images.
- The implementation of the first real-time targeted
monocular system that achieves such a tight joint optimisation of motion and dense geometry
个人理解
- 使用光度信息进行code的自动编码,用RGB-D数据进行训练,然后得到每个code的深度,属于直接法的一种
- SLAM系统:利用滑动窗口的方式,重建利用了SFM
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