Centros subcorticais dos sistemas visual primário e óptico acessório no mocó (kerodon rupestris): caracterização pela projeção retiniana e citoarquitetura.

The primary and accessory optic systems comprise two set of retinorecipient neural clusters. In this study, these visual related centers in the rock cavy were evaluated by using the retinal innervations pattern and Nissl staining cytoarchigtecture. After unilateral intraocular injection of cholera toxin B subunit and immunohistochemical reaction of coronal and sagittal sections from the diencephalon and midbrain region of rock cavy. Three subcortical centres of primary visual system were identified, superior colliculus, lateral geniculate complex and pretectal complex. The lateral geniculate complex is formed by a series of nuclei receiving direct visual information from the retina, dorsal lateral geniculate nucleus, intergeniculate leaflet and ventral lateral geniculate nucleus. The pretectal complex is formed by series of pretectal nuclei, medial pretectal nucleus, olivary pretectal nucleus, posterior pretectal nucleus, nucleus of the optic tract and anterior pretectal nucleus. In the accessory optic system, retinal terminals were observed in the dorsal terminal, lateral terminal and medial terminal nuclei as well as in the interstitial nucleus of the superior fasciculus, posterior fibres. All retinorecipient nuclei received bilateral input, with a contralateral predominance. This is the first study of this nature in the rock cavy and the results are compared with the data obtained for other species. The investigation represents a contribution to the knowledge regarding the organization of visual optic systems in relation to the biology of species.

Odometria visual baseada em técnicas de structure from motion

Visual Odometry is the process that estimates camera position and orientation based solely on images and in features (projections of visual landmarks present in the scene) extraced from them. With the increasing advance of Computer Vision algorithms and computer processing power, the subarea known as Structure from Motion (SFM) started to supply mathematical tools composing localization systems for robotics and Augmented Reality applications, in contrast with its initial purpose of being used in inherently offline solutions aiming 3D reconstruction and image based modelling. In that way, this work proposes a pipeline to obtain relative position featuring a previously calibrated camera as positional sensor and based entirely on models and algorithms from SFM. Techniques usually applied in camera localization systems such as Kalman filters and particle filters are not used, making unnecessary additional information like probabilistic models for camera state transition. Experiments assessing both 3D reconstruction quality and camera position estimated by the system were performed, in which image sequences captured in reallistic scenarios were processed and compared to localization data gathered from a mobile robotic platform