Geometric 3D point cloud compression

The use of 3D data in mobile robotics applications provides valuable information about the robot’s environment but usually the huge amount of 3D information is unmanageable by the robot storage and computing capabilities. A data compression is necessary to store and manage this information but preserving as much information as possible. In this paper, we propose a 3D lossy compression system based on plane extraction which represent the points of each scene plane as a Delaunay triangulation and a set of points/area information. The compression system can be customized to achieve different data compression or accuracy ratios. It also supports a color segmentation stage to preserve original scene color information and provides a realistic scene reconstruction. The design of the method provides a fast scene reconstruction useful for further visualization or processing tasks.

Technologies for Anatomical and Geometric Characterization of the Corneal Structure and Anterior Segment: A Review

Corneal and anterior segment imaging techniques have become a crucial tool in the clinical practice of ophthalmology, with a great variety of applications, such as corneal curvature and pachymetric analysis, detection of ectatic corneal conditions, anatomical study of the anterior segment prior to phakic intraocular lens implantation, or densitometric analysis of the crystalline lens. From the Placido-based systems that allow only a characterization of the geometry of the anterior corneal surface to the Scheimpflug photography-based systems that provide a characterization of the cornea, anterior chamber, and crystalline lens, there is a great variety of devices with the capability of analyzing different anatomical parameters with very high precision. To date, Scheimpflug photography-based systems are the devices providing the more complete analysis of the anterior segment in a non-invasive way. More developments are required in anterior segment imaging technologies in order to improve the analysis of the crystalline lens structure as well as the ocular structures behind the iris in a non-invasive way when the pupil is not dilated.

Visual perception for the 3D recognition of geometric pieces in robotic manipulation

During grasping and intelligent robotic manipulation tasks, the camera position relative to the scene changes dramatically because the robot is moving to adapt its path and correctly grasp objects. This is because the camera is mounted at the robot effector. For this reason, in this type of environment, a visual recognition system must be implemented to recognize and “automatically and autonomously” obtain the positions of objects in the scene. Furthermore, in industrial environments, all objects that are manipulated by robots are made of the same material and cannot be differentiated by features such as texture or color. In this work, first, a study and analysis of 3D recognition descriptors has been completed for application in these environments. Second, a visual recognition system designed from specific distributed client-server architecture has been proposed to be applied in the recognition process of industrial objects without these appearance features. Our system has been implemented to overcome problems of recognition when the objects can only be recognized by geometric shape and the simplicity of shapes could create ambiguity. Finally, some real tests are performed and illustrated to verify the satisfactory performance of the proposed system.