3D Fusion of Infrared Images with Dense RGB Reconstruction from Multiple Views – with Application to Fire-fighting Robots

07/29/2020

∙

This project integrates infrared and RGB imagery to produce dense 3D environment models reconstructed from multiple views. The resulting 3D map contains both thermal and RGB information which can be used in robotic fire-fighting applications to identify victims and active fire areas.

READ FULL TEXT

3D Fusion of Infrared Images with Dense RGB Reconstruction from Multiple Views – with Application to Fire-fighting Robots

RGB-D And Thermal Sensor Fusion: A Systematic Literature Review

PST900: RGB-Thermal Calibration, Dataset and Segmentation Network

Multiview Aggregation for Learning Category-Specific Shape Reconstruction

Semantic Dense Reconstruction with Consistent Scene Segments

Spatio-thermal depth correction of RGB-D sensors based on Gaussian Processes in real-time

Assessing thermal imagery integration into object detection methods on ground-based and air-based collection platforms

The Use of AI for Thermal Emotion Recognition: A Review of Problems and Limitations in Standard Design and Data

3D Fusion of Infrared Images with Dense RGB Reconstruction from Multiple Views – with Application to Fire-fighting Robots

Related Research

RGB-D And Thermal Sensor Fusion: A Systematic Literature Review

PST900: RGB-Thermal Calibration, Dataset and Segmentation Network

Multiview Aggregation for Learning Category-Specific Shape Reconstruction

Semantic Dense Reconstruction with Consistent Scene Segments

Spatio-thermal depth correction of RGB-D sensors based on Gaussian Processes in real-time

Assessing thermal imagery integration into object detection methods on ground-based and air-based collection platforms

The Use of AI for Thermal Emotion Recognition: A Review of Problems and Limitations in Standard Design and Data