Characterizing Everyday Objects using Human Touch - Thermal Dissipation as a Sensing Modality

Abstract

We contribute MIDAS as a novel sensing solution for characterizing everyday objects using thermal dissipation. MIDAS takes advantage of the fact that anytime a person touches an object, it results in heat transfer. By capturing and modeling the dissipation of the transferred heat, e.g., through the decrease in the captured thermal radiation, MIDAS can characterize the object and determine its material. We validate MIDAS through extensive empirical benchmarks and demonstrate that MIDAS offers an innovative sensing modality that can recognize a wide range of materials – with up to 83% accuracy – and generalize to variations in the people interacting with objects.

Agustin Zuniga

Pervasive Data Science group

Dr. Agustin Zuniga works in the areas of pervasive data science and artificial intelligence of things, especially in low-cost sensing and intelligent sensing pipeline solutions.