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Bundle adjustment is a central part of most visual SLAM and Structure from Motion systems and thus a relevant component of\udUAVs equipped with cameras. This paper makes two contributions to bundle adjustment. First, we present a novel approach which\udexploits trifocal constraints, i.e., constraints resulting from corresponding points observed in three camera images, which allows to\udestimate the camera pose parameters without 3D point estimation. Second, we analyze the quality loss compared to the optimal bundle\udadjustment solution when applying different types of approximations to the constrained optimization problem to increase efficiency.\udWe implemented and thoroughly evaluated our approach using a UAV performing mapping tasks in outdoor environments. Our results\udindicate that the complexity of the constraint bundle adjustment can be decreased without loosing too much accuracy

ON THE QUALITY AND EFFICIENCY OF APPROXIMATE SOLUTIONS TO BUNDLE ADJUSTMENT WITH EPIPOLAR AND TRIFOCAL CONSTRAINTS