Bingham Procrustean Alignment for Object Detection in Clutter

Jared Glover; Sanja Popovic

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arXiv · 1304.7399

Bingham Procrustean Alignment for Object Detection in Clutter

Jared Glover·Sanja Popovic

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Abstract

A new system for object detection in cluttered RGB-D images is presented. Our main contribution is a new method called Bingham Procrustean Alignment (BPA) to align models with the scene. BPA uses point correspondences between oriented features to derive a probability distribution over possible model poses. The orientation component of this distribution, conditioned on the position, is shown to be a Bingham distribution. This result also applies to the classic problem of least-squares alignment of point sets, when point features are orientation-less, and gives a principled, probabilistic way to measure pose uncertainty in the rigid alignment problem. Our detection system leverages BPA to achieve more reliable object detections in clutter.

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Jared Glover, Sanja Popovic. 2013-04-27. Bingham Procrustean Alignment for Object Detection in Clutter. https://arxiv.org/abs/1304.7399

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