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In this paper, we use 2D object detections from multiple views tosimultaneously estimate a 3D quadric surface for each object and localize thecamera position. We derive a SLAM formulation that uses dual quadrics as 3Dlandmark representations, exploiting their ability to compactly represent thesize, position and orientation of an object, and show how 2D object detectionscan directly constrain the quadric parameters via a novel geometric errorformulation. We develop a sensor model for object detectors that addresses thechallenge of partially visible objects, and demonstrate how to jointly estimatethe camera pose and constrained dual quadric parameters in factor graph basedSLAM with a general perspective camera.

QuadricSLAM: Dual Quadrics from Object Detections as Landmarks in Object-oriented SLAM