RESUMO
Mobile AR applications benefit from fast initialization to display world-locked effects instantly. However, standard visual odometry or SLAM algorithms require motion parallax to initialize (see Figure 1) and, therefore, suffer from delayed initialization. In this paper, we present a 6-DoF monocular visual odometry that initializes instantly and without motion parallax. Our main contribution is a pose estimator that decouples estimating the 5-DoF relative rotation and translation direction from the 1-DoF translation magnitude. While scale is not observable in a monocular vision-only setting, it is still paramount to estimate a consistent scale over the whole trajectory (even if not physically accurate) to avoid AR effects moving erroneously along depth. In our approach, we leverage the fact that depth errors are not perceivable to the user during rotation-only motion. However, as the user starts translating the device, depth becomes perceivable and so does the capability to estimate consistent scale. Our proposed algorithm naturally transitions between these two modes. Our second contribution is a novel residual in the relative pose problem to further improve the results. The residual combines the Jacobians of the functional and the functional itself and is minimized using a Levenberg-Marquardt optimizer on the 5-DoF manifold. We perform extensive validations of our contributions with both a publicly available dataset and synthetic data. We show that the proposed pose estimator outperforms the classical approaches for 6-DoF pose estimation used in the literature in low-parallax configurations. Likewise, we show our relative pose estimator outperforms state-of-the-art approaches in an odometry pipeline configuration where we can leverage initial guesses. We release a dataset for the relative pose problem using real data to facilitate the comparison with future solutions for the relative pose problem. Our solution is either used as a full odometry or as a pre-SLAM component of any supported SLAM system (ARKit, ARCore) in world-locked AR effects on platforms such as Instagram and Facebook.
RESUMO
The mammalian target of rapamycin (mTOR) is a key regulator of cellular growth which associates with other proteins to form two multi-protein complexes called mTORC1 and mTORC2. Dysregulation of mTORC1 signalling in brain is implicated in neuropathological conditions such as autism spectrum or neurodegenerative disorders. Accordingly, allosteric mTOR inhibitors are currently in clinical trials for the treatment of such disorders. Here, we ablated either mTORC1 or mTORC2 conditionally in Purkinje cells of the mouse cerebellum to dissect their role in the development, function and survival of these neurons. We find that the two mouse models largely differ from each other by phenotype and cellular responses. Inactivation of mTORC2, but not of mTORC1, led to motor coordination deficits at an early age. This phenotype correlated with developmental deficits in climbing fibre elimination and impaired dendritic self-avoidance in mTORC2-deficient Purkinje cells. In contrast, inactivation of mTORC1, but not of mTORC2, affected social interest of the mice and caused a progressive loss of Purkinje cells due to apoptosis. This cell loss was paralleled by age-dependent motor deficits. Comparison of mTORC1-deficient Purkinje cells with those deficient for the mTORC1 inhibitor TSC1 revealed a striking overlap in Purkinje cell degeneration and death, which included neurofilamentopathy and reactive gliosis. Altogether, our study reveals distinct roles of mTORC1 and mTORC2 in Purkinje cells for mouse behaviour and the survival of neurons. Our study also highlights a convergence between the phenotypes of Purkinje cells lacking mTORC1 activity and those expressing constitutively active mTORC1 due to TSC1 deficiency.
