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arXiv · 2209.03910

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

Prajwal Chidananda·Saurabh Nair·Douglas Lee·Adrian Kaehler
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Abstract

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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Prajwal Chidananda, Saurabh Nair, Douglas Lee, Adrian Kaehler. 2022-09-08. PixTrack: Precise 6DoF Object Pose Tracking using NeRF Templates and Feature-metric Alignment. https://arxiv.org/abs/2209.03910

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