Get location of panoramic camera in a 3D point cloud using color histograms with CPO

Get location of panoramic camera in a 3D point cloud using color histograms with CPO

CPO: Change Robust Panorama to Point Cloud Localization
arXiv paper abstract https://arxiv.org/abs/2207.05317v1
arXiv PDF paper https://arxiv.org/pdf/2207.05317v1.pdf

… present CPO, a fast and robust algorithm that localizes a 2D panorama with respect to a 3D point cloud of a scene possibly containing changes.

To robustly handle scene changes … propose efficient color histogram generation and subsequent robust localization using score maps.

… very fast color histogram generation for a large number of camera poses without explicitly rendering images for all candidate poses.

… accumulate the regional consistency of the panorama and point cloud as 2D/3D score maps, and use them to weigh the input color values to further increase robustness.

The weighted color distribution quickly finds good initial poses and achieves stable convergence for gradient-based optimization.

CPO is lightweight and achieves effective localization in all tested scenarios, showing stable performance despite scene changes, repetitive structures, or featureless regions, which are typical challenges for visual localization with perspective cameras.

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I apply innovative technologies like machine learning, computer vision, and physics to further an organization's goals. Am recognized innovator with 66 patents.