Projective rectification from the fundamental matrix

This paper describes a direct, self-contained method for planar image rectification of stereo pairs. The method is based solely on an examination of the Fundamental matrix, where an improved method is given for the derivation of two projective transformations that horizontally align all the epipolar projections. A novel approach is proposed to uniquely optimise each transform in order to minimise perspective distortions. This ensures the rectified images resemble the original images as closely as possible. Detailed results show that the rectification precision exactly matches the estimation error of the Fundamental matrix. In tests the remaining perspective distortion offers on average less than one percent viewpoint distortion. Both these factors offer superior robustness and performance compared with existing techniques

Resource-Aware Image Mosaicking on Networks of Small-Scale UAVs

ABSTRACT In this approach we estimate the depth structure of images captured by small-scale UAVs to guide the mosaicking of an overview image. We focus on efficient methods where initially only metadata and descriptors of corresponding points are transferred over the network. The complete image is presented later when sufficient communication resources are available

Resource-Aware Image Mosaicking on Networks of Small-Scale UAVs

ABSTRACT In this approach we estimate the depth structure of images captured by small-scale UAVs to guide the mosaicking of an overview image. We focus on efficient methods where initially only metadata and descriptors of corresponding points are transferred over the network. The complete image is presented later when sufficient communication resources are available

Matching algorithm performance analysis for autocalibration method of stereo vision

Stereo vision is one of the interesting research topics in the computer vision field. Two cameras are used to generate a disparity map, resulting in the depth estimation. Camera calibration is the most important step in stereo vision. The calibration step is used to generate an intrinsic parameter of each camera to get a better disparity map. In general, the calibration process is done manually by using a chessboard pattern, but this process is an exhausting task. Self-calibration is an important ability required to overcome this problem. Self-calibration required a robust and good matching algorithm to find the key feature between images as reference. The purpose of this paper is to analyze the performance of three matching algorithms for the autocalibration process. The matching algorithms used in this research are SIFT, SURF, and ORB. The result shows that SIFT performs better than other methods

Towards real-time stereoscopic image rectification for 3D visualization

This paper describes a method for stereoscopic rectification with geometric distortion minimisation, to generate suitable image pairs for 3D viewing applications. The current state of the art technique is not optimal as it lacks appropriate mathematical constraints. We present a new approach that enforces the same distortion minimisation criterion with more computational e±ciency whilst also achieving superior distortion removal. Detailed mathematical expressions have been developed that fully constrain the system to facilitate the use of faster and more accurate non-linear optimisation algorithms. Appropriate rectification transforms can then be defined at speeds suitable for real-timeimplementation

Réalité augmentée à partir d'une séquence vidéo en utilisant la stéréoscopie dense.

International audienceCet article s'intéresse à la réalité augmentée, c'est à dire à l'intégration d'objets virtuels générés par ordinateur dans une séquence d'images en gérant les occultations. L'occultation est l'un des problèmes cruciaux en réalité augmentée. Il consiste à tenir compte des interactions entre les éléments virtuels insérés et la scène réelle: les parties occultées de ces éléments doivent être déterminées. La méthode proposée repose sur le calcul des cartes de disparité en utilisant les techniques de mise en correspondance denses. Afin de retrouver des cartes de disparité denses, nous présentons dans cet article deux techniques d'appariement. La première est basée sur la programmation dynamique. Bien que cette méthode donne des résultats satisfaisants, elle reste néanmoins très gourmande en temps de calcul. Afin améliorer le temps de calcul ainsi que la qualité des résultats, nous proposons une autre méthode dite hybride basée sur l'approche multi résolution et la programmation dynamique. Les cartes de disparité ainsi obtenues sont appliqués en réalité augmentée afin d'intégrer de manière réaliste des objets virtuels générées par ordinateur dans une séquence d'images. La méthode d'augmentation proposée réduit considérablement l'intervention de l'utilisateur. L'applicabilité de la méthode est démontrée sur de nombreuses séquences d'images

Depth and Zoom Estimation for PTZ Camera Using Stereo Vision

Depth perception comes naturally to humans. However in a Computer Vision scenario estimation of distance between object and camera is an area still under research. This thesis aims to use binocular stereo vision to reconstruct a 3D scene from 2D images of the scene taken by a pair of cameras and use it to estimate the distance of the object from the camera. Further, this estimated distance is used to calculate the Zoom of a PTZ camera. Although there are various ways to determine the distance of an object from the camera using Sensors, Lasers and other such external devices, the method used in this thesis is independent of the use of such external devices and uses only image processing techniques to determine the distance. Results obtained and the process are clearly outlined