An Automatic Multi-Target Independent Analysis Framework for Non-Planar Infrared-Visible Registration

Sun, Xinglong; Xu, Tingfa; Zhang, Jizhou; Zhao, Zishu; Li, Yuankun

doi:10.3390/s17081696

Cited by 4 publications

(2 citation statements)

References 30 publications

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“…The geometric registration model from the spot image to the footprint image determines the corresponding position of the spot center on the footprint image. The projective mapping between the two images or planes is known as the homograph matrix [19,20]. The conversion from the image coordinates of the spot image to the image coordinates of the footprint image can be expressed as Equation (1).…”

Section: Geometric Registration Modelmentioning

confidence: 99%

Laser Spot Center Location Method for Chinese Spaceborne GF-7 Footprint Camera

Ren

Xie

Xiong³

et al. 2020

Sensors

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The Gaofen-7 (GF-7) satellite is equipped with two area array sensor footprint cameras to capture the laser altimeter spot. In order to establish a direct correspondence between the laser data and the stereo image data, a new method is proposed to fit the center of the spot using the brightness difference between the spot image and the footprint image. First, the geometric registration between the spot image and the footprint image is completed based on feature matching or template matching. Then, the brightness values between the two images are extracted from the corresponding image position to form a measurement, and the least squares adjustment method is used to calculate the parameters of the brightness conversion model between the spot image and the footprint image. Finally, according to the registration relationship, the center of the identified spots is respectively positioned in the footprint images, so that the laser spots are accurately identified in the along-track stereo footprint images. The experimental results show that the spot error of this method is less than 0.7 pixel, which has higher reliability and stability, and can be used for a GF-7 satellite footprint camera.

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Section: Geometric Registration Modelmentioning

confidence: 99%

Laser Spot Center Location Method for Chinese Spaceborne GF-7 Footprint Camera

Ren

Xie

Xiong³

et al. 2020

Sensors

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“…MMIR of visible and IR images is well studied in the literature for facial recognition, image fusion and other applications [ 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 ]. However, fever screening requires high registration accuracy at the canthi regions, instead of the whole face.…”

Section: Introductionmentioning

confidence: 99%

Free-Form Deformation Approach for Registration of Visible and Infrared Facial Images in Fever Screening

Chenna

Ghassemi

Pfefer

et al. 2018

Sensors

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Fever screening based on infrared (IR) thermographs (IRTs) is an approach that has been implemented during infectious disease pandemics, such as Ebola and Severe Acute Respiratory Syndrome. A recently published international standard indicates that regions medially adjacent to the inner canthi provide accurate estimates of core body temperature and are preferred sites for fever screening. Therefore, rapid, automated identification of the canthi regions within facial IR images may greatly facilitate rapid fever screening of asymptomatic travelers. However, it is more difficult to accurately identify the canthi regions from IR images than from visible images that are rich with exploitable features. In this study, we developed and evaluated techniques for multi-modality image registration (MMIR) of simultaneously captured visible and IR facial images for fever screening. We used free form deformation (FFD) models based on edge maps to improve registration accuracy after an affine transformation. Two widely used FFD models in medical image registration based on the Demons and cubic B-spline algorithms were qualitatively compared. The results showed that the Demons algorithm outperformed the cubic B-spline algorithm, likely due to overfitting of outliers by the latter method. The quantitative measure of registration accuracy, obtained through selected control point correspondence, was within 2.8 ± 1.2 mm, which enables accurate and automatic localization of canthi regions in the IR images for temperature measurement.

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ARCTIC: A knowledge distillation approach via attention-based relation matching and activation region constraint for RGB-to-Infrared videos action recognition

Quan,

Chen,

et al. 2023

Computer Vision and Image Understanding

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An Automatic Multi-Target Independent Analysis Framework for Non-Planar Infrared-Visible Registration

Cited by 4 publications

References 30 publications

Laser Spot Center Location Method for Chinese Spaceborne GF-7 Footprint Camera

Laser Spot Center Location Method for Chinese Spaceborne GF-7 Footprint Camera

Free-Form Deformation Approach for Registration of Visible and Infrared Facial Images in Fever Screening

ARCTIC: A knowledge distillation approach via attention-based relation matching and activation region constraint for RGB-to-Infrared videos action recognition

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