Human-centric metrics for indoor scene assessment and synthesis

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

3 Scopus Citations
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Author(s)

  • Qiang Fu
  • Hai Yan
  • Bin Zhou
  • Xiaowu Chen
  • Xueming Li

Related Research Unit(s)

Detail(s)

Original languageEnglish
Article number101073
Journal / PublicationGraphical Models
Volume110
Online published21 May 2020
Publication statusPublished - Jul 2020

Abstract

In recent years, many approaches have been proposed to analyze the affordance of 3D objects and to facilitate the synthesis of aesthetic and realistic indoor scenes. However, how to assess the quality of such synthesized 3D scenes is still a challenging problem. To address this, we present a novel approach through so-called Human-Centric Metrics (HCMs) for quantitatively evaluating the layout quality of certain objects, and thus to facilitate indoor scene synthesis. Our HCMs consider both the human-object factors to assess the functional accessibility of indoor objects, and the human-environment factors to assess the subjective comfort in the scene. Given a 3D scene with arranged furniture objects, our method automatically places human agents and then use HCMs to assess both the object arrangement and indoor environment based on the position/direction of a certain human agent. The conducted user study shows that the assessment capability of HCMs well conforms to the interior design knowledge. We also use the HCMs based assessment results to synthesize 3D indoor scenes by suggesting indoor objects and their layout given an empty room. A series of experimental results and comparisons are presented to validate the usability and effectiveness of our HCMs for virtual scene assessment and synthesis.

Research Area(s)

  • 3D modeling, Environment assessment, Indoor scene synthesis

Citation Format(s)

Human-centric metrics for indoor scene assessment and synthesis. / Fu, Qiang; Fu, Hongbo; Yan, Hai; Zhou, Bin; Chen, Xiaowu; Li, Xueming.

In: Graphical Models, Vol. 110, 101073, 07.2020.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review