Scale invariant line matching on the sphere

International audienceThis paper proposes a novel approach of line matching across images captured by different types of cameras, from perspective to omnidirectional ones. Based on the spherical mapping, this method utilizes spherical SIFT point features to boost line matching and searches line correspondences using an affine invariant measure of similarity. It permits to unify the commonest cameras and to process heterogeneous images with the least distortion of visual information

Estimation de mouvement de caméras hybrides et reconstruction 3D à partir de points et droites

Structure from motion is a widely studied problem in computer vision. It refers to the estimation of camera motion and three-dimensional structure of the scene. There exist numerous solutions to structure from motion problems, varying in types of vision equipment, kinds of image feature and estimation process. Most of them coped with perspective or omnidirectional vision but very few with both. Combining the good resolution provided by perspective cameras and the wide field of view of omnidirectional ones has become an attractive trend. For this reason, we seek for an approach that is applicable to both of these vision sensors. We propose a structure from motion algorithm using lines as this feature possesses many advantageous characteristics over points, especially in urban environment. This method consists of linear motion estimation based on line correspondences, 3D reconstruction and bundle adjustment to refine the camera and structure parameters. Besides lines, points can be integrated in our translation estimation to improve its performance. The contributions of this thesis concern the applicability of the proposed method to any type of central projection cameras including fish-eye ones, the advantage of using line images, and the exploitation of both point and line features.L’estimation de mouvement de caméras et la reconstruction de structure 3D (Structure from Motion ou SfM) ont déjà beaucoup étudiées. Il existe de nombreuses méthodes de SfM qui diffèrent en fonction du type de capteurs et de primitives utilisés. La plupart de ces approches ont été développées pour la vision perspective ou omnidirectionnelle mais très peu pour les deux. Une combinaison de la bonne résolution fournie par les caméras perspectives et le large champ de vue des caméras omnidirectionnelles devient très utile dans plusieurs applications comme la surveillance, la reconstruction de scène, la navigation d’un robot mobile, etc. C’est la raison pour laquelle nous recherchons une méthode qui est applicable à ces deux systèmes de vision. Nous proposons une technique de SfM basée droites qui possèdent de nombreuses caractéristiques avantageuses, particulièrement en milieu urbain. Cette méthode se compose de l’estimation de mouvement en deux étapes (calcul des rotations à partir de points de fuite de droites parallèles dans la scène et calcul des translations à partir de ces mêmes droites), la reconstruction de structure 3D et l’ajustement de faisceaux afin de raffiner les paramètres de caméras et de structure 3D. De plus, les points peuvent être intégrés dans l’estimation de translations pour améliorer le résultat. Ainsi, nous avons développé dans cette thèse une approche originale qui permet d’estimer le mouvement et de reconstruire la scène avec tout type de caméras centrales ou fish-eye et en utilisant deux types de primitives (les droites et les points)

Real-time contrast medium detection in x-ray images by mathematical morphology operators

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COLOR CORRECTION THROUGH REGION MATCHING LEVERAGED BY POINT CORRESPONDENCES

International audienceThis paper addresses the problem of region-based color cor-rection. Our solution begins with the image segmentation by marker-controlled watershed transformation, which is faster and produces more uniform regions with better adherence to object boundaries than the segmentation in previous works. Next, regions between two images are matched using point feature correspondences which are invariant to geometric transformation and illumination changes. Finally, the color-corrected image is generated from the color transfer functions of corresponding regions. We demonstrate the results of this approach using different sets of images

Estimation de mouvement de caméras et reconstruction de structure 3D à partir de points et droites

L estimation de mouvement de caméras et la reconstruction de structure 3D (Structure from Motion ou SfM) ont déjà beaucoup étudiées. Il existe de nombreuses méthodes de SfM qui diffèrent en fonction du type de capteurs et de primitives utilisés. La plupart de ces approches ont été développées pour la vision perspective ou omnidirectionnelle mais très peu pour les deux. Une combinaison de la bonne résolution fournie par les caméras perspectives et le large champ de vue des caméras omnidirectionnelles devient très utile dans plusieurs applications comme la surveillance, la reconstruction de scène, la navigation d un robot mobile, etc. C est la raison pour laquelle nous recherchons une méthode qui est applicable à ces deux systèmes de vision. Nous proposons une technique de SfM basée droites qui possèdent de nombreuses caractéristiques avantageuses, particulièrement en milieu urbain. Cette méthode se compose de l estimation de mouvement en deux étapes (calcul des rotations à partir de points de fuite de droites parallèles dans la scène et calcul des translations à partir de ces mêmes droites), la reconstruction de structure 3D et l ajustement de faisceaux afin de raffiner les paramètres de caméras et de structure 3D. De plus, les points peuvent être intégrés dans l estimation de translations pour améliorer le résultat. Ainsi, nous avons développé dans cette thèse une approche originale qui permet d estimer le mouvement et de reconstruire la scène avec tout type de caméras centrales ou fish-eye et en utilisant deux types de primitives (les droites et les points).Structure from motion is a widely studied problem in computer vision. It refers to the estimation of camera motion and three-dimensional structure of the scene. There exist numerous solutions to structure from motion problems, varying in types of vision equipment, kinds of image feature and estimation process. Most of them coped with perspective or omnidirectional vision but very few with both. Combining the good resolution provided by perspective cameras and the wide field of view of omnidirectional ones has become an attractive trend. For this reason, we seek for an approach that is applicable to both of these vision sensors. We propose a structure from motion algorithm using lines as this feature possesses many advantageous characteristics over points, especially in urban environment. This method consists of linear motion estimation based on line correspondences, 3D reconstruction and bundle adjustment to refine the camera and structure parameters. Besides lines, points can be integrated in our translation estimation to improve its performance. The contributions of this thesis concern the applicability of the proposed method to any type of central projection cameras including fish-eye ones, the advantage of using line images, and the exploitation of both point and line features.AMIENS-BU Sciences (800212103) / SudocSudocFranceF

Extrinsic calibration of heterogeneous cameras by line images

International audienceThe extrinsic calibration refers to determining the relative pose of cameras. Most of the approaches for cameras with non-overlapping fields of view (FOV) are based on mirror reflection, object tracking or rigidity constraint of stereo systems whereas cameras with overlapping FOV can be calibrated using structure from motion solutions. We propose an extrinsic calibration method within structure from motion framework for cameras with overlapping FOV and its extension to cameras with partially non-overlapping FOV. Recently, omnidirectional vision has become a popular topic in computer vision as an omnidirectional camera can cover large FOV in one image. Combining the good resolution of perspective cameras and the wide observation angle of omnidirectional cameras has been an attractive trend in multi-camera system. For this reason, we present an approach which is applicable to heterogeneous types of vision sensors. Moreover, this method utilizes images of lines as these features possess several advantageous characteristics over point features, especially in urban environment. The calibration consists of a linear estimation of orientation and position of cameras and optionally bundle adjustment to refine the extrinsic parameters

Automatic color correction: region-based approach and performance evaluation using full reference metrics

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