This paper proposes a robust and highly efficient feature-based visual-inertial odometry (VIO) approach. In order to save the computational resource, a simplified stereo visual model is applied to reduce the dimension of visual measurements. Moreover, the speed of feature matching is improved by using prior information from the inertial sensor. And through the marginalization, optimization is limited in two sliding windows, which can meet the need for the real-time application. In addition, a high accuracy initialization method and the homogeneous extraction of image features are introduced to ensure excellent pose tracking. The proposed VIO system is implemented on open datasets to show its merit compared with other state-of-the-art algorithms. In addition, we also perform this system on a low-cost stereo visual-inertial sensor and validate its practicability and superiority. Furthermore, the comparative experiment shows that the proposed algorithm has a higher accuracy than the monocular VIO and a shorter running time than the stereo VIO.
The Supernova community has expressed an interest in so-called "rolling cadences", in order to achieve better sampling of SNe light curves. Here we explore how such rolling cadences would affect both the identification of AGNs and the science that can be derived from their resulting light curves. We present a metric that quantifies how well parameters of a particular variability model would be recovered for a given opSim cadence. We conclude that extreme rolling cadences (with few or no observations during some seasons) would be detrimental to AGN science. Less extreme rolling cadences require further investigation as the answer depends critically on both the science and the desired cadence.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.