Automated monocular vision based system for picking textureless objects

Developing 3D model for mobile robot environment using mono-vision system

Abstract: Mobile robot system will be an important asset in our future. Mobile robot not only has to execute predefined tasks programmed with, but also it must explore the unknown environment that might be pushed to work in. In this paper we propose, implement and test a new model for mobile robot environment using mono-vision system. This proposed system develops 3D environment model utilizing mono-vision system. The model is developed through capturing multiple shots from different locations. The 3D model describes the distance and the angle of objects with respect to the robot. Finally, the mobile robot will utilize this model to navigate its environment. This is achieved through projecting the 3D model into the motion floor and identifying the obstacles surrounding the robot. Then, the robot will avoid any object in its motion line. Most importantly, the model is updated continuously based on the changes in the environment and the location of the robot.

Multiple view geometry in computer vision

Abstract: From the Publisher: A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Recent major developments in the theory and practice of scene reconstruction are described in detail in a unified framework. The book covers the geometric principles and how to represent objects algebraically so they can be computed and applied. The authors provide comprehensive background material and explain how to apply the methods and implement the algorithms directly.

A flexible new technique for camera calibration

Abstract: We propose a flexible technique to easily calibrate a camera. It only requires the camera to observe a planar pattern shown at a few (at least two) different orientations. Either the camera or the planar pattern can be freely moved. The motion need not be known. Radial lens distortion is modeled. The proposed procedure consists of a closed-form solution, followed by a nonlinear refinement based on the maximum likelihood criterion. Both computer simulation and real data have been used to test the proposed technique and very good results have been obtained. Compared with classical techniques which use expensive equipment such as two or three orthogonal planes, the proposed technique is easy to use and flexible. It advances 3D computer vision one more step from laboratory environments to real world use.

Algorithms for the reduction of the number of points required to represent a digitized line or its caricature

Abstract: All digitizing methods, as a general rule, record lines with far more data than is necessary for accurate graphic reproduction or for computer analysis. Two algorithms to reduce the number of points required to represent the line and, if desired, produce caricatures, are presented and compared with the most promising methods so far suggested. Line reduction will form a major part of automated generalization. Regle generale, les methodes numeriques enregistrent des lignes avec beaucoup plus de donnees qu'il n'est necessaire a la reproduction graphique precise ou a la recherche par ordinateur. L'auteur presente deux algorithmes pour reduire le nombre de points necessaires pour representer la ligne et produire des caricatures si desire, et les compare aux methodes les plus prometteuses suggerees jusqu'ici. La reduction de la ligne constituera une partie importante de la generalisation automatique.