Sit & Relax: Interactive Design of Body‐Supporting Surfaces

Abstract

We propose a novel method for interactive design of well‐fitting body‐supporting surfaces that is driven by the pressure distribution on the body's surface. Our main contribution is an interactive modeling system that utilizes captured body poses and computes an importance field that is proportional to the pressure distribution on the body for a given pose. This distribution indicates where the body should be supported in order to easily hold a particular pose, which is one of the measures of comfortable sitting. Using our approximation, we propose the entire workflow for interactive design of C2 smooth surfaces which serve as seats, or generally, as body supporting furniture for comfortable sitting. Finally, we also provide a design tool for Rhinoceros/Grasshopper that allows for interactive creation of single designs or entire multi‐person sitting scenarios. We also test the tool with design students and present several results. Our method aims at interactive design in order to help designers to create appropriate surfaces digitally without additional empirical design passes.

Pose to Seat: Automated design of body-supporting surfaces

“…In pose driven design the goal is to fulfill much stricter human requirements. Research in this area considers a given pose as optimal for a specific situation and aims to design a seating surface to match a person in that pose as close as possible [8,1].…”

“…An entirely different approach at personalized furniture design is presented by Wu et al [28]: ActiveErgo is a monitored workplace environment that dynamically adjusts its parameters like desk height or chair position in accordance with ergonomic guidelines, adjusted to the user. In 2018, Leimer et al [1] presented Sit&Relax, a pose-driven, interactive furniture design approach. However, the accuracy of their results is mostly dependent on the quality of the control meshes used as input.…”

“…We used the dataset of poses provided by Leimer et al [1], who uses a Blender plugin [29] for the generation of body meshes with varying attributes, like gender, mass, size, stature, etc. The meshes are skinned and rigged to a skeleton and the poses can be adjusted either manually or can be created with a motion capturing device (for instance Perception Neuron system [30]).…”

“…The support mesh is then further optimized. The resulting control mesh can then serve as an initial design candidate that can be edited with conventional modeling tools, or used with the fitting algorithm of Leimer et al [1] to create a surface with an even better optimized fit.…”

“…Note that the mesh is generated to in order to optimally support the body in a given pose. Right: the surface fitting algorithm of Leimer et al [1] applied to the generated control mesh, again using the body model as guidance.…”