• "Make it Home in 33 seconds", Oriental Daily, May 9, 2011. Reported by Shao-Kuen, Lam

  • "Automatic Furniture Arrangement Software 60 times faster than Human Design", Ta Kung Pao, May 9, 2011. Reported by Kylie, Lau

  • "Computer Program lets Users Click into Interior Design Mode", South China Morning Post, May 9, 2011. Reported by Maggie, Tam

  • "Furniture Arrangement Software makes Ideal Home in 20 seconds", Sing Tao Daily, May 9, 2011. Reported by Oi-Fong, Tsang

  • "Rearranging the furniture? Let software do it for you", NewScientist, April 23, 2011.

News Articles


Lai-Fai Yu

Assistant Professor of Computer Science

University of Massachusetts Boston

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Sai-Kit Yeung

Assistant Professor of Information Systems Technology and Design (ISTD)

Director of Vision, Graphics and Computational Design (VGD) Group

Singapore University of Technology and Design (SUTD)

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Chi-Keung Tang

Professor of Computer Science and Engineering

Hong Kong University of Science and Technology (HKUST)

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Demetri Terzopoulos

Distinguished Professor and Chancellor's Professor of Computer Science

Director, Computer Graphics & Vision Laboratory

University of California, Los Angeles (UCLA)

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Tony F. Chan

President and Professor of Mathematics & Computer Science and Engineering

Hong Kong University of Science and Technology (HKUST)

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Stanley J. Osher

Professor of Mathematics & Computer Science, Electrical Engineering & Chemical and Biomolecular Engineering

Director of Special Projects, Institute for Pure and Applied Mathematics (IPAM)

University of California, Los Angeles (UCLA)

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This paper presents a fully-automatic system for generating an optimized indoor scene populated by a variety of furniture objects. Given positive examples of furnished indoor scenes, our system extracts hierarchical and spatial relationships for different types of furniture objects. This step is done once, in advance. The extracted relationships are encoded into priors which are integrated into a cost function that optimizes ergonomic factors, such as visibility and accessibility. To deal with the prohibitively large search space, the cost function is optimized by simulated annealing with a Metropolis Hastings state-search step. We demonstrate that different furniture layouts can be automatically synthesized to decorate an indoor scene. A perceptual study is performed to validate that there is no significant difference in preference on functionality between our synthesized results and those produced by human designers.
Keywords: interior generation, interior modeling, spatial allocation, virtual reality


  • Make it Home: Automatic Optimization of Furniture Arrangement

       Lap-Fai Yu, Sai-Kit Yeung, Chi-Keung Tang, Demetri Terzopoulos, Tony F. Chan and Stanley Osher

       ACM Transactions on Graphics (Proceeding of SIGGRAPH 2011)

       Paper, Video

       Fast Forward Slides at Siggraph 2011 (Powerpoint) (21.5 MB), Presentation Slides at Siggraph 2011 (Keynote) (1.58 GB),

       Presentation Slides (Powerpoint with no video) (25.7 MB), Powerpoint media files (1.5 GB)

  • Rearranging the furniture? Let software do it for you

       NewScientist, Magazine Issue 2809, 23 April 2011,


  • 6 Newspapers at Hong Kong:
  • "Room to Move", HKUST Alumni News, July, 2011:
  • BibTex:


       author = {Lap-Fai Yu and Sai Kit Yeung and Chi-Keung Tang and Demetri Terzopoulos and Tony F. Chan and Stanley Osher},

       title = {Make it home: automatic optimization of furniture arrangement},

       journal = {ACM Transactions on Graphics},

       volume = {30},

       year = {2011},

       number = {4},

       pages = {86}



    We are grateful to anonymous reviewers for their constructive comments. We also thank Google 3D Warehouse for providing a rich source of 3D models which help tremendously in speeding up the modeling process. Special thanks to Shawn Singh for his professional advice and efforts on video-editing, scene-modeling and rendering; Yu-Wing Tai for his helpful suggestion on the draft of this paper and experiments; Michael S. Brown for narrating the video; Howard Alexander Greene for advice on video-editing; Jan Adamec for providing a modified version of his Room Arranger software which allows our early testing; Wenze Hu for technical advice on stochastic optimization; Lap-Fai Lee for advice on data analysis of the perceptual study. This research was partially supported by the Hong Kong Research Grant Council under grant number 620309, RICE/MURI Award 443948-SN-80050, NSF 443948- TH-22487 and ONR N00014-09-1-0105. Lap-Fai Yu is supported by the Sir Edward Youde Memorial Fellowship.