A Featured-Based Strategy for Stereovision Matching in Sensors with Fish-Eye Lenses for Forest Environments

This paper describes a novel feature-based stereovision matching process based on a pair of omnidirectional images in forest stands acquired with a stereovision sensor equipped with fish-eye lenses. The stereo analysis problem consists of the following steps: image acquisition, camera modelling, feature extraction, image matching and depth determination. Once the depths of significant points on the trees are obtained, the growing stock volume can be estimated by considering the geometrical camera modelling, which is the final goal. The key steps are feature extraction and image matching. This paper is devoted solely to these two steps. At a first stage a segmentation process extracts the trunks, which are the regions used as features, where each feature is identified through a set of attributes of properties useful for matching. In the second step the features are matched based on the application of the following four well known matching constraints, epipolar, similarity, ordering and uniqueness. The combination of the segmentation and matching processes for this specific kind of sensors make the main contribution of the paper. The method is tested with satisfactory results and compared against the human expert criterion

Under vehicle perception for high level safety measures using a catadioptric camera system

In recent years, under vehicle surveillance and the classification of the vehicles become an indispensable task that must be achieved for security measures in certain areas such as shopping centers, government buildings, army camps etc. The main challenge to achieve this task is to monitor the under frames of the means of transportations. In this paper, we present a novel solution to achieve this aim. Our solution consists of three main parts: monitoring, detection and classification. In the first part we design a new catadioptric camera system in which the perspective camera points downwards to the catadioptric mirror mounted to the body of a mobile robot. Thanks to the catadioptric mirror the scenes against the camera optical axis direction can be viewed. In the second part we use speeded up robust features (SURF) in an object recognition algorithm. Fast appearance based mapping algorithm (FAB-MAP) is exploited for the classification of the means of transportations in the third part. Proposed technique is implemented in a laboratory environment

Panoramic Stereovision and Scene Reconstruction

With advancement of research in robotics and computer vision, an increasingly high number of applications require the understanding of a scene in three dimensions. A variety of systems are deployed to do the same. This thesis explores a novel 3D imaging technique. This involves the use of catadioptric cameras in a stereoscopic arrangement. A secondary system aims to stabilize the system in the event that the cameras are misaligned during operation. The system provides a stark advantage due to it being a cost effective alternative to present day standard state-of-the-art systems that achieve the same goal of 3D imaging. The compromise lies in the quality of depth estimation, which can be overcome with a different imager and calibration. The result was a panoramic disparity map generated by the system

Advances in Stereo Vision

Stereopsis is a vision process whose geometrical foundation has been known for a long time, ever since the experiments by Wheatstone, in the 19th century. Nevertheless, its inner workings in biological organisms, as well as its emulation by computer systems, have proven elusive, and stereo vision remains a very active and challenging area of research nowadays. In this volume we have attempted to present a limited but relevant sample of the work being carried out in stereo vision, covering significant aspects both from the applied and from the theoretical standpoints

Calibrage et modélisation d’un système de stéréovision hybride et panoramique

Dans cette thèse nos contributions à la résolution de deux problématiques rencontrées en vision numérique et en photogrammétrie, qui sont le calibrage de caméras et la stéréovision, sont présentées. Ces deux problèmes font l’objet de très nombreuses recherches depuis plusieurs années. Les techniques de calibrage existantes diffèrent beaucoup suivant le type de caméras à calibrer (classique ou panoramique, à focale fixe ou à focale variable, ..). Notre première contribution est un banc de calibrage, à l’aide des éléments d’optique diffractive, qui permet de calibrer avec une bonne précision une très grande partie des caméras existantes. Un modèle simple et précis qui décrit la projection de la grille formée sur l’image et une méthode de calibrage pour chaque type de caméras est proposé. La technique est très robuste et les résultats pour l’ensemble des caméras calibrées sont optimaux. Avec la multiplication des types de caméras et la diversité des modèles de projections, un modèle de formation d'image générique semble très intéressant. Notre deuxième contribution est un modèle de projection unifié pour plusieurs caméras classiques et panoramiques. Dans ce modèle, toute caméra est modélisée par une projection rectiligne et des splines cubiques composées permettant de représenter toutes sortes de distorsions. Cette approche permet de modéliser géométriquement les systèmes de stéréovision mixtes ou panoramiques et de convertir une image panoramique en une image classique. Par conséquent, le problème de stéréovision mixte ou panoramique est transformé en un problème de stéréovision conventionnelle. Mots clés : calibrage, vision panoramique, distorsion, fisheye, zoom, panomorphe, géométrie épipolaire, reconstruction tridimensionnelle, stéréovision hybride, stéréovision panoramique.This thesis aims to present our contributions to the resolution of two problems encountered in the field of computer vision and photogrammetry, which are camera calibration and stereovision. These two problems have been extensively studied in the last years. Different camera calibration techniques have been developed in the literature depending on the type of camera (classical or panoramic, with zoom lens or fixed lens..). Our first contribution is a compact and accurate calibration setup, based on diffractive optical elements, which is suitable for different kind of cameras. The technique is very robust and optimal results were achieved for different types of cameras. With the multiplication of camera types and the diversity of the projection models, a generic model has become very interesting. Our second contribution is a generic model, which is suitable for conventional and panoramic cameras. In this model, composed cubic splines functions provide more realistic model of both radial and tangential distortions. Such an approach allows to model either hybrid or panoramic stereovision system and to convert panoramic image to classical image. Consequently, the processing challenges of a hybrid stereovision system or a panoramic stereovision system are turned into simple classical stereovision problems. Keywords: Calibration, panoramic vision, distortions, fisheye, zoom, panomorph, epipolar geometry, three-dimensional reconstruction, hybrid stereovision, panoramic stereovision

THINK Robots

Retailers rely on Kiva Systems’ warehouse robots to deliver order-fulfillment services, but current systems are frequently interrupted and require physical barriers to ensure compliance with safety regulations since Kiva does not currently rely on the obstacle detection system to contribute to the functional safety of its overall system. After evaluating operating scenarios and detection technologies, a solution comprised of a stereo vision system to detect static objects and a radio ranging system to identify humans in the vicinity was designed, built, and verified, with the aim of reducing undue downtime and allowing humans and robots to safely interact without physical restrictions