PixTrack: Precise 6DoF Object Pose Tracking using NeRF Templates and Feature-metric Alignment
arxiv(2022)
摘要
We present PixTrack, a vision based object pose tracking framework using
novel view synthesis and deep feature-metric alignment. We follow an SfM-based
relocalization paradigm where we use a Neural Radiance Field to canonically
represent the tracked object. Our evaluations demonstrate that our method
produces highly accurate, robust, and jitter-free 6DoF pose estimates of
objects in both monocular RGB images and RGB-D images without the need of any
data annotation or trajectory smoothing. Our method is also computationally
efficient making it easy to have multi-object tracking with no alteration to
our algorithm through simple CPU multiprocessing. Our code is available at:
https://github.com/GiantAI/pixtrack
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关键词
object pose tracking,nerf templates,pixtrack,feature-metric
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