Improvements of the Inverse Compositional Algorithm for Parametric Motion Estimation

Briand, Thibaud; Facciolo, Gabriele; Sánchez, Javier

doi:10.5201/ipol.2018.222

Cited by 10 publications

(5 citation statements)

References 19 publications

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“…For all objects of the MVTec dataset, we chose a single reference that is used to align all images from this category. As in [2], we aligned images using [5]. Contrary to the objects of the dataset, the textures were not aligned.…”

Section: Implementation and Training Detailsmentioning

confidence: 99%

GLAD: A Global-to-Local Anomaly Detector

Artola

Kolodziej²,

Morel

et al. 2023

2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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Section: Implementation and Training Detailsmentioning

confidence: 99%

GLAD: A Global-to-Local Anomaly Detector

Artola

Kolodziej²,

Morel

et al. 2023

2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

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“…This assures the pixel consistency of the aligned scenes before merging them into the S + 1 mosaic. The benefits of ICA to register push-frame satellite acquisitions has been previously studied by (Anger et al, 2020, Briand et al, 2018. Consider two scenes I and I ′ of S1 such that I ′ has to be aligned onto I to construct the mosaic S + 1 .…”

Section: Image Warping Refinementmentioning

confidence: 99%

L1b+: A Perfect Sensor Localization Model for Simple Satellite Stereo Reconstruction From Push-Frame Image Strips

Marí

Ehret²,

Anger³

et al. 2022

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. We propose a novel method to generate a single image product from a multi-image strip acquired by a push-frame satellite imaging system. The images of the push-frame strips are combined into a large scale mosaic simulating a perfect sensor geometry. The local camera models of the input images are leveraged to produce a new localization model that covers the output mosaic entirely. Among other applications, this simplifies the task of stereo reconstruction enormously: instead of treating multiple stereo pairs of small images, it is possible to reconstruct the entire area covered by the push-frame acquisition using a single pair of mosaics incorporating all the images. We test our method using strips of SkySat L1B scenes and denote the output images as L1B+. To evaluate the quality of the L1B+ images and their localization models, the stereo reconstructions obtained with L1B+ are compared with those obtained with L1B and with a lidar reference model.

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“…where we assume that J i = 1. The advantage of this formulation is that it leads to a linear system of equations on the parameters of A i and d. When A i = 1 the linearization could still be applied but an rough estimate of A i should be provided (for instance by aligning the frames [10]) from which the Jacobians can be extracted. We now detail how our linear system is built and solved.…”

Section: Plane Stabilizationmentioning

confidence: 99%

Parallax estimation for push-frame satellite imagery: application to super-resolution and 3D surface modeling from Skysat products

Anger¹,

Ehret²,

Facciolo³

2021

Preprint

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Recent constellations of satellites, including the Skysat constellation, are able to acquire burst of images. This new acquisition mode allows for modern image restoration techniques, including multiframe super-resolution. As the satellite moves during the acquisition of the burst, elevation changes in the scene translate into noticeable parallax. This parallax hinders the results of the restoration. To cope with this issue, we propose a novel parallax estimation method. The method is composed of a linear Plane+Parallax decomposition of the apparent motion and a multi-frame optical flow algorithm that exploits all frames simultaneously. Using SkySat L1A images, we show that the estimated perpixel displacements are important for applying multiframe super-resolution on scenes containing elevation changes and that can also be used to estimate a coarse 3D surface model.

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Improvements of the Inverse Compositional Algorithm for Parametric Motion Estimation

Cited by 10 publications

References 19 publications

GLAD: A Global-to-Local Anomaly Detector

GLAD: A Global-to-Local Anomaly Detector

L1b+: A Perfect Sensor Localization Model for Simple Satellite Stereo Reconstruction From Push-Frame Image Strips

Parallax estimation for push-frame satellite imagery: application to super-resolution and 3D surface modeling from Skysat products

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