  This paper has introduced a novel approach for the real-time estimation of 3D
tactile forces exerted by human fingertips via vision only. The introduced
approach is entirely monocular vision-based and does not require any physical
force sensor. Therefore, it is scalable, non-intrusive, and easily fused with
other perception systems such as body pose estimation, making it ideal for HRI
applications where force sensing is necessary. The introduced approach consists
of three main modules: finger tracking for detection and tracking of each
individual finger, image alignment for preserving the spatial information in
the images, and the force model for estimating the 3D forces from coloration
patterns in the images. The model has been implemented experimentally, and the
results have shown a maximum RMS error of 8.4% (for the entire range of force
levels) along all three directions. The estimation accuracy is comparable to
the offline models in the literature, such as EigneNail, while, this model is
capable of performing force estimation at 30 frames per second.
