PixTrack: Precise 6DoF Object Pose Tracking using NeRF Templates and Feature-metric Alignment

Understand

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.