Metrics of a Hug


RGB/Thermal Photogrammetry, Python, OpenCV, Cinema4D
Carnegie Mellon University
2020

Metrics of a Hug is an investigation on how to measure our affective footprint on other beings and spaces using RGB and thermal imagery, computer vision, and photogrammetry.





This experimental capture system employs a DSLR-camera with a fixed lens and an Axis Q19-E surveillance thermal camera (connected as IP cameras to TouchDesigner) that simultaneously captured an RGB and a thermal map of a person after receiving a hug. After, the images were aligned using a Python and OpenCV algorithm that computed the homography matrix needed to adapt the perspective of one image into the other. The system was previously calibrated using a perforated dotted grid pattern visible by both the RGB and the thermal camera which allowed to determine each image's deformation.







Using high-contrast markers and a spinning platform I was able to capture enough frames to perform a 3d photogrammetry of the 'hugged' individual. After a hug, the thermal load stored in the clothing's fabric was easily visible with the thermal camera which images were used as the final texture of the reconstructed hug model in Cinema4D.





–Project supported by the Frank-Ratchye STUDIO for Creative Inquiry



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