The environmental 3-D reconstruction is a strategic task in many contexts, above all, in infrastructure inspection and vehicle/robot automatic motion. In this paper, we present a patented sensor capable to recover 3-D data with a very high profile acquisition rate and perform an omnidirectional highly accurate environmental reconstruction: these skills are allowed by a profilometric laser approach coupled to a catadioptric system. After a presentation of the sensor's functionality, its sensitivity is theoretically analyzed both in terms of maximum and medium error. This, not only for proving the sensor's accuracy (which, anyway, has been also experimentally tested), but also for defining a design strategy which optimally sets up its geometrical parameters. Performance of a prototypal implementation of the sensor, as well as a calibration technique, are presented, and several indoor and outdoor 3-D reconstructions are shown.

A high-resolution vision system for the inspection of drilling tools is presented. A triangulation-based laser scanner is used to extract a three-dimensional model of the target aimed to the fast detection and characterization of surface defects. The use of two orthogonal calibrated handlings allows the achievement of precisions of the order of few microns in the whole testing volume and the prevention of self-occlusions induced on the undercut surfaces of the tool. Point cloud registration is also derived analytically to increase to strength of the measurement scheme, whereas proper filters are used to delete samples whose quality is below a reference threshold. Experimental tests are performed on calibrated spheres and different-sized tools, proving the capability of the presented setup to entirely reconstruct complex targets with maximum absolute errors between the estimated distances and the corresponding nominal values below 12 μm.

In this paper, a real case study on a Goal Line Monitoring system is presented. The core of the paper is a refined ball detection algorithm that analyzes candidate ball regions to detect the ball. A decision making approach, by means of camera calibration, decides about the goal event occurrence. Differently from other similar approaches, the proposed one provides, as unquestionable proof, the image sequence that records the goal event under consideration. Moreover, it is non-invasive: it does not require any change in the typical football devices (ball, goal posts, and so on). Extensive experiments were performed on both real matches acquired during the Italian Serie A championship, and specific evaluation tests by means of an artificial impact wall and a shooting machine for shot simulation. The encouraging experimental results confirmed that the system could help humans in ambiguous goal line event detection.