  Visuotactile sensing technology has received much attention in recent years.
This article proposes a feature detection method applicable to visuotactile
sensors based on continuous marker patterns (CMP) to measure 3-d deformation.
First, we construct the feature model of checkerboard-like corners under
contact deformation, and design a novel double-layer circular sampler. Then, we
propose the judging criteria and response function of corner features by
analyzing sampling signals' amplitude-frequency characteristics and circular
cross-correlation behavior. The proposed feature detection algorithm fully
considers the boundary characteristics retained by the corners with geometric
distortion, thus enabling reliable detection at a low calculation cost. The
experimental results show that the proposed method has significant advantages
in terms of real-time and robustness. Finally, we have achieved the
high-density 3-d contact deformation visualization based on this detection
method. This technique is able to clearly record the process of contact
deformation, thus enabling inverse sensing of dynamic contact processes.
