Basic Search / Detailed Display

Author: 林姿廷
Tzu-Ting Lin
Thesis Title: 結合室內設計指南進行智慧空間規劃
Smart space planning with interior design guidelines
Advisor: 楊傳凱
Chuan-Kai Yang
Committee: 林伯慎
Bor-Shen Lin
Yuan-Cheng Lai
Degree: 碩士
Department: 管理學院 - 資訊管理系
Department of Information Management
Thesis Publication Year: 2023
Graduation Academic Year: 111
Language: 中文
Pages: 62
Keywords (in Chinese): 家具佈置室內設 計三維重建語義分割物件分類
Keywords (in other languages): Furniture arrangement, Interior design, 3D reconstruction, Semantic segmentation, Object classification
Reference times: Clicks: 196Downloads: 0
School Collection Retrieve National Library Collection Retrieve Error Report
  • 當一個新的傢俱物品要放入現有的環境中時,用戶通常沒有什麼依據的將物件隨意擺放,但是許多傢俱物品通常需要周圍有空間才能使用,而在用戶隨意擺放的情況下,很容易就造成空間不足的情況發生,或未來不易尋找的問題。為解決上述情況,本文希望可以結合室內設計指南給予用戶新的傢俱物品的擺放建議。
    本論文考量多種約束條件,透過搜尋常見傢俱組(如桌子、椅子等)來找到最常見的幾種擺放方式,通過一個成本函數 去計算各個位置的擺放成本,並依照成本做排序,找到能達成最低成本的擺放方式,給予使用者傢俱物品的擺放建議。

    When a new furniture item is to be placed in an existing environment, users may have no due about where to place the object. Furthermore, many furniture items typically require some space around them to be usable. In the case of random placement by users, it is easy to cause insufficient space or future searching difficulties. To address this issue, this paper aims to combine interior design guidelines to provide users with placement recommendations for new furniture items.
    This paper considers multiple constraints and searches for the most common
    placement methods for common furniture sets (such as tables, chairs, etc.). A cost
    function is used to calculate the placement cost of each position, and sorting is done
    according to the cost to find the placement method that can achieve the lowest cost,
    providing users with furniture placement recommendations.

    中 文 摘 要 III 英 文 摘 要 IV 誌 謝 V 目 錄 VI 表 目 錄 VIII 圖 目 錄 IX 第 一 章 緒 論 1 1.1 研究動機與目的 1 1.2 論文架構 2 第 二 章 文 獻 探 討 3 2.1 三維模型建模 3 2.2 三維模型分割 5 第 三 章 演 算 法 設 計 與 系 統 實 作 7 3.1 系統流程 7 3.2 系統輸入 8 3.3 圖像前處理 8 3.3.1 輸入來源為影片 8 3.3.2 輸入來源為圖片 8 3.4 點雲介紹 9 3.5 3D模型重建 10 3.5.1 COLMAP 架構 10 3.6 三維模型處理 11 3.6.1 PointNet++架構 12 3.6.2 物件分割 12 3.6.3 物件分類 22 3.7 家具佈置建議 24 3.7.1 家具布局指南 25 第 四 章 結 果 展 示 與 評 估 33 4.1 系統環境 33 4.2 資料集 34 4.2.1 三維模型處理資料集 34 4.2.2 3D-Front資料集 35 4.3 實驗結果 36 4.3.1 實驗一:三維模型重建結果 36 4.3.2 實驗二:語義辨識結果 36 4.3.3 實驗三:物件分類結果 37 4.3.4 實驗四:未使用家具指南限制的推薦結果 39 4.3.5 實驗五:基於家具指南的推薦結果 44 第 五 章 結 論 與 未 來 展 望 48 參 考 文 獻 49

    [1] T. Funkhouser, M. Kazhdan, P. Shilane, P. Min, W. Kiefer, A. Tal,S. Rusinkiewicz, and D. Dobkin, “Modeling by example,” ACM transactions on graphics (TOG), vol. 23, no. 3, pp. 652–663, 2004.
    [2] D. Wang, X. Cui, X. Chen, Z. Zou, T. Shi, S. Salcudean, Z. J. Wang, and R. Ward, “Multi-view 3d reconstruction with transformers,” in Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 5722–5731, 2021.
    [3] M. Attene, B. Falcidieno, and M. Spagnuolo, “Hierarchical mesh segmentation based on fitting primitives,” The Visual Computer, vol. 22, pp. 181–193, 2006.
    [4] A. Dai, D. Ritchie, M. Bokeloh, S. Reed, J. Sturm, and M. Nießner, “Scancom-plete: Large-scale scene completion and semantic segmentation for 3d scans,”
    in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4578–4587, 2018.
    [5] J. L. Schonberger and J.-M. Frahm, “Structure-from-motion revisited,” in Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 4104–4113, 2016.
    [6] A. Knapitsch, J. Park, Q.-Y. Zhou, and V. Koltun, “Tanks and temples: Benchmarking large-scale scene reconstruction,” ACM Transactions on Graphics,
    vol. 36, no. 4, 2017.
    [7] C. R. Qi, L. Yi, H. Su, and L. J. Guibas, “Pointnet++: Deep hierarchical
    feature learning on point sets in a metric space,” Advances in neural information
    processing systems, vol. 30, 2017.
    [8] C. R. Qi, H. Su, K. Mo, and L. J. Guibas, “Pointnet: Deep learning on point sets
    for 3d classification and segmentation,” in Proceedings of the IEEE conference
    on computer vision and pattern recognition, pp. 652–660, 2017.
    [9] R. B. Rusu and S. Cousins, “3D is here: Point Cloud Library (PCL),” in
    IEEE International Conference on Robotics and Automation (ICRA), (Shanghai, China), May 9-13 2011.
    [10] P. Merrell, E. Schkufza, Z. Li, M. Agrawala, and V. Koltun, “Interactive furniture layout using interior design guidelines,” ACM transactions on graphics (TOG), vol. 30, no. 4, pp. 1–10, 2011.
    [11] “How to space furniture in your room.”
    howtodecorate/2019/02/how-to-space-furniture-in-your-room/ . Ac-
    cessed on 08.05.2023.
    [12] “interior design course.”
    20/furniture-spacing-guidelines . Accessed on 08.05.2023.
    [13] C. Talbott and M. Matthews, Decorating for Good: A Step-by-step Guide to
    Rearranging What You Already Own. Clarkson Potter Publishers, 1999.
    [14] “The ultimate decorators’ guide to ideal living room layout measurements.” . Accessed on 08.05.2023.
    [15] “Minimum space in front of a bathroom vanity.” . Accessed on 08.05.2023.
    [16] “The 10 commandments of furniture placement.” . Accessed on 08.05.2023.
    [17] “Don’t make these mistakes when arranging your living room.” Accessed on 08.05.2023.
    [18] Q.-Y. Zhou, J. Park, and V. Koltun, “Open3d: A modern library for 3d data processing,” arXiv preprint arXiv:1801.09847, 2018.
    [19] Z. Wu, S. Song, A. Khosla, F. Yu, L. Zhang, X. Tang, and J. Xiao, “3d
    shapenets: A deep representation for volumetric shapes,” in Proceedings of the
    IEEE conference on computer vision and pattern recognition, pp. 1912–1920, 2015.
    [20] I. Armeni, O. Sener, A. R. Zamir, H. Jiang, I. Brilakis, M. Fischer, and
    S. Savarese, “3d semantic parsing of large-scale indoor spaces,” in Proceedings of
    the IEEE conference on computer vision and pattern recognition, pp. 1534–1543, 2016.
    [21] H. Fu, B. Cai, L. Gao, L.-X. Zhang, J. Wang, C. Li, Q. Zeng, C. Sun, R. Jia,
    B. Zhao, and H. Zhang, “3d-front: 3d furnished rooms with layouts and semantics,” in Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), pp. 10933–10942, October 2021.
    [22] Q. Xu, Z. Xu, J. Philip, S. Bi, Z. Shu, K. Sunkavalli, and U. Neumann, “Point-
    nerf: Point-based neural radiance fields,” arXiv preprint arXiv:2201.08845, 2022.

    無法下載圖示 Full text public date 2026/08/16 (Intranet public)
    Full text public date 2028/08/16 (Internet public)
    Full text public date 2028/08/16 (National library)