Pose-Driven Generation and Optimization of Seating Furniture

Andreas Winkler
Pose-Driven Generation and Optimization of Seating Furniture
[poster] [thesis]

Information

Abstract

Modern furniture design systems provide seating solutions for various applications, ranging from general purpose solutions to specific environments. The central goal of furniture design is to create comfortable seating surfaces. To provide optimal comfort for a specific person and environment, personalized furniture design is required. As comfort is generally seen as the user’s subjective feeling, objective comfort measures are defined that approximate a person’s comfort for a given seating surface. Computational furniture design systems create seating solutions for a given scenario using interactive algorithms. Specialized seating surfaces often require extensive manual design effort. In this thesis, a computational furniture design framework to generate personalized seating surfaces is proposed. Utilizing a notation of sitting comfort based on equal pressure distribution, our algorithm generates seating surface models fitted to a person in a specific pose. We introduce an automated furniture design framework able to create comfortable seating surfaces for specific body shapes and poses. We developed a generic template model capable of supporting a large variety of sitting poses and human body shapes that is matched to an input pose in multi stage fitting process. Furthermore, we introduce a non-linear mesh optimization algorithm for further functional and visual improvements. In addition, the proposed framework serves as a fully automated solution to create specialized control meshes usable as input meshes in other design frameworks, thus eliminating the need for manual design effort.

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BibTeX

@mastersthesis{WINKLER-2019-PDG,
  title =      "Pose-Driven Generation and Optimization of Seating Furniture",
  author =     "Andreas Winkler",
  year =       "2019",
  abstract =   "Modern furniture design systems provide seating solutions
               for various applications, ranging from general purpose
               solutions to specific environments. The central goal of
               furniture design is to create comfortable seating surfaces.
               To provide optimal comfort for a specific person and
               environment, personalized furniture design is required. As
               comfort is generally seen as the user’s subjective
               feeling, objective comfort measures are defined that
               approximate a person’s comfort for a given seating
               surface. Computational furniture design systems create
               seating solutions for a given scenario using interactive
               algorithms. Specialized seating surfaces often require
               extensive manual design effort. In this thesis, a
               computational furniture design framework to generate
               personalized seating surfaces is proposed. Utilizing a
               notation of sitting comfort based on equal pressure
               distribution, our algorithm generates seating surface models
               fitted to a person in a specific pose. We introduce an
               automated furniture design framework able to create
               comfortable seating surfaces for specific body shapes and
               poses. We developed a generic template model capable of
               supporting a large variety of sitting poses and human body
               shapes that is matched to an input pose in multi stage
               fitting process. Furthermore, we introduce a non-linear mesh
               optimization algorithm for further functional and visual
               improvements. In addition, the proposed framework serves as
               a fully automated solution to create specialized control
               meshes usable as input meshes in other design frameworks,
               thus eliminating the need for manual design effort.",
  month =      oct,
  address =    "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
  school =     "Research Unit of Computer Graphics, Institute of Visual
               Computing and Human-Centered Technology, Faculty of
               Informatics, TU Wien ",
  keywords =   "optimization, fabrication",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2019/WINKLER-2019-PDG/",
}