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Colour-Consistent Structure-from-Motion Models using Underwater Imagery

This paper presents an automated approach to correcting for colour inconsistency in underwater images collected from multiple perspectives during the construction of 3D structure-from-motion models. When capturing images underwater, the water column imposes several effects on images that are negligible in air such as colour-dependant attenuation and lighting patterns. These effects cause problems for human interpretation of images and also confound computer-based techniques for clustering and classification. Our approach exploits the 3D structure of the scene generated using structure-from-motion and photogrammetry techniques accounting for distance-based attenuation, vignetting and lighting pattern, and improves the consistency of photo-textured 3D models. Results are presented using imagery collected in two different underwater environments using an Autonomous Underwater Vehicle (AUV).

📈 Trend Setter - Multimodal Learning
🐣 Hot Topic Early Bird - domain adaptation

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