A 6-DoF pose estimation method for low-texture objects based on 3D Gaussian sputtering

Abstract

This invention relates to a 6-DoF pose estimation method for low-texture objects based on 3D Gaussian sputtering, belonging to the fields of computer vision and robotics. The steps are as follows: 1) Offline reference database construction: Acquire multi-view reference images of the low-texture object to obtain the object region. Train a 3D Gaussian model based on the object region and simultaneously construct a BOW initial pose retrieval library; 2) Online pose optimization: Acquire the query image and segment the object region. Assign an initial pose through BOW feature matching. Generate a rendered image using the 3D Gaussian model and the initial pose. Calculate the composite loss. Implement backpropagation of the loss gradient to the pose increment through differentiable rendering. Iteratively optimize the pose increment using the AdamW optimizer; 3) Continuous frame pose tracking: Design a Track mode for continuous frame scenes and output continuous frame tracking poses. This invention solves the problems of feature matching failure and insufficient pose estimation accuracy in low-texture scenes, and is suitable for practical applications such as industrial robot grasping and AR interaction.

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