Point cloud management techniques for a multihit ladar imaging camera system
Tutor / director / evaluatorRoyo Royo, Santiago
Document typeMaster thesis
Rights accessOpen Access
With the incorporation of optical sensors into the machine vision technology, a full new field has emerged to revolutionize different technologies such as self-driving, 3D scanners and printers or virtual reality. However, new technologies come with new techniques and methodologies to manipulate them. Point Clouds were born as the data storage system and a collection of challenges came with them. One of these challenges consists in processing them in order to obtain the best description of the real world. Hence, it is necessary to have a tool to evaluate the quality of those Point Cloud in order to analyze their quality. In this MSc thesis we developed a mathematical approach for Point Cloud quality evaluation and implanted by Matlab. The full mathematical development as well as the structure of the code and the different tools used to acquire and manipulate Point Clouds are described and introduced along the thesis. A final analysis of the methodology showed there is still a lot of work to do. Several questions appeared and need to be solved in order to grow in this field.
Lidar imaging is a powerful measurement technique where a laser pulse is shone onto an object and the beam reflected back is recovered at some solid-state detector. The time elapsed is counted so an automated measurement of the distance to the target is obtained, without any further calculation. The concept is also referred to as ladar or time of-flight imaging. Different scanning mechanisms have been proposed to recover complete 3D images out of this pointwise approach. Most popular recent applications involve landing aids, object recognition, self-guided vehicles and safe