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

A review of the one-parameter division undistortion model

The one-parameter division undistortion model by (Lenz, 1987) and (Fitzgibbon, 2001) is a simple radial distortion model with beneficial algebraic properties that allows to reason about some problems analytically that can only be handled numerically in other distortion models. One property of this distortion model is that straight lines in the undistorted image correspond to circles in the distorted image. These circles are fully described by their center point, as the radius can be calculated from the position of the center and the distortion parameter only. This publication collects the properties of this distortion model from several sources and reviews them. Moreover, we show in this publication that the space of this center is projectively isomorphic to the dual space of the undistorted image plane, i.e. its line space. Therefore, projective invariant measurements on the undistorted lines are possible by the according measurements on the centers of the distorted circles. As an example of application, we use this to find the metric distance of two parallel straight rails with known track gauge in a single uncalibrated camera image with significant radial distortion

Omnidirectional video

Omnidirectional video enables direct surround immersive viewing of a scene by warping the original image into the correct perspective given a viewing direction. However, novel views from viewpoints off the camera path can only be obtained if we solve the 3D motion and calibration problem. In this paper we address the case of a parabolic catadioptric camera – a paraboloidal mirror in front of an orthographic lens – and we introduce a new representation, called the circle space, for points and lines in such images. In this circle space, we formulate an epipolar constraint involving a 4x4 fundamental matrix. We prove that the intrinsic parameters can be inferred in closed form from the 2D subspace of the new fundamental matrix from two views if they are constant or from three views if they vary. Three dimensional motion and structure can then be estimated from the decomposition of the fundamental matrix

DLT-Like Calibration of Central Catadioptric Cameras

International audienceIn this study, we present a calibration technique that is valid for all single-viewpoint catadioptric cameras. We are able to represent the projection of 3D points on a catadioptric image linearly with a 6 × 10 projection matrix, which uses lifted coordinates for image and 3D points. This projection matrix can be computed with enough number of 3D-2D correspondences (minimum 20 points distributed in three different planes). We show how to decompose it to obtain intrinsic and extrinsic parameters. Moreover, we use this parameter estimation followed by a non-linear optimization to calibrate various types of cameras. Our results are based on the sphere camera model which considers that every central catadioptric system can be modeled using two projections, one from 3D points to a unitary sphere and then a perspective projection from the sphere to the image plane. We tested our method both with simulations and real images

CONTRIBUTION A LA STEREOVISION OMNIDIRECTIONNELLE ET AU TRAITEMENT DES IMAGES CATADIOPTRIQUES : APPLICATION AUX SYSTEMES AUTONOMES

Computer vision and digital image processing are two disciplines aiming to endow computers with a sense of perception and image analysis, similar to that of humans. Artificial visual perception can be greatly enhanced when a large field of view is available. This thesis deals with the use of omnidirectional cameras as a mean of expanding the field of view of computer vision systems. The visual perception of depth (3D) by means of omnistereo configurations, and special processing algorithms adapted to catadioptric images, are the main subjects studied in this thesis. Firstly a survey on 3D omnidirectional vision systems is conducted. It highlights the main approaches for obtaining depth information, and provides valuable indications for the choice of the configuration according to the application requirements. Then the design of an omnistereo sensor is addressed, we present a new configuration of the proposed sensor formed by a unique catadioptric camera, dedicated to robotic applications. An experimental investigation of depth estimation accuracy was conducted to validate the new configuration.Digital images acquired by catadioptric cameras present various special geometrical proprieties, such as non-uniform resolution and severe radial distortions. The application of conventional algorithms to process such images is limited in terms of performance. For that, new algorithms adapted to the spherical geometry of catadioptric images have been developed.Gathered omnidirectional computer vision techniques were finally used in two real applications. The first concerns the integration of catadioptric cameras to a mobile robot. The second focuses on the design of a solar tracker, based on a catadioptric camera.The results confirm that the adoption of such sensors for autonomous systems offer more performance and flexibility in regards to conventional sensors.La vision par ordinateur est une discipline qui vise doter les ordinateurs d’un sens de perception et d’analyse d'image semblable à celui de l’homme. La perception visuelle artificielle peut être grandement améliorée quand un grand champ de vision est disponible. Cette thèse traite de l'utilisation des caméras omnidirectionnelles comme un moyen d'élargir le champ de vision des systèmes de vision artificielle. La perception visuelle de la profondeur (3D) par le biais de configurations omnistéréo, et les algorithmes de traitement adaptés aux images catadioptriques, sont les principaux sujets étudiés.Tout d'abord une étude des systèmes de vision omnidirectionnelle 3D est menée. Elle met en évidence les principales approches pour obtenir l’information sur la profondeur et fournit des indications précieuses sur le choix de la configuration en fonction des besoins de l'application. Ensuite, la conception d'un capteur omnistéréo est adressée ; nous présentons une nouvelle configuration du capteur proposé basé une caméra catadioptrique unique, et dédié à la robotique mobile. Des expérimentations sur la précision d’estimation de la profondeur ont été menées pour valider la nouvelle configuration. Les images catadioptriques présentent diverses propriétés géométriques particulières, telles que la résolution non-uniforme et de fortes distorsions radiales. L’application des algorithmes de traitement classiques à ce type d’images se trouve limité en termes de performances. Dans ce sens, de nouveaux algorithmes adaptés à la géométrie sphérique de ces images ont été développés.Les techniques de vision omnidirectionnelle artificielle recueillies ont été finalement exploitées dans deux applications réelles. La première concerne l’intégration des caméras catadioptriques à un robot mobile. La seconde porte sur la conception d’un suiveur solaire, à base d’une caméra catadioptrique.Les résultats obtenus confirment que l’adoption de tels capteurs pour les systèmes autonomes offre plus de performances et de flexibilité en regards aux capteurs classiques

Reconstruction active et passive en vision par ordinateur

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal

Structure and Motion from Uncalibrated Catadioptric Views

In this paper we present a new algorithm for structure from motion from point correspondences in images taken from uncalibrated catadioptric cameras with parabolic mirrors. We assume that the unknown intrinsic parameters are three: the combined focal length of the mirror and lens and the intersection of the optical axis with the image. We introduce a new representation for images of points and lines in catadioptric images which we call the circle space. This circle space includes imaginary circles, one of which is the image of the absolute conic. We formulate the epipolar constraint in this space and establish a new 4 × 4 catadioptric fundamental matrix. We show that the image of the absolute conic belongs to the kernel of this matrix. This enables us to prove that Euclidean reconstruction is feasible from two views with constant parameters and from three views with varying parameters. In both cases, it is one less than the number of views necessary with perspective cameras