3D sketch-based 3D model retrieval with convolutional neural network

3D sketch-based 3D model retrieval is to retrieve similar 3D models using users' hand-drawn 3D sketches as input. Compared with traditional 2D sketch-based retrieval, 3D sketch-based 3D model retrieval is a brand new and challenging research topic. In this paper, we employ advanced deep learning method and propose a novel 3D sketch based 3D model retrieval system. Our system has been comprehensively tested on two benchmark datasets and compared with other existing 3D model retrieval algorithms. The experimental results reveal our approach outperforms other competing state-of-the-arts and demonstrate promising potential of our approach on 3D sketch based applications.

[1]  Bernard Chazelle,et al.  Shape distributions , 2002, TOGS.

[2]  Bernard Chazelle,et al.  A Reflective Symmetry Descriptor , 2002, ECCV.

[3]  Bo Li,et al.  3D Sketch-Based 3D Model Retrieval , 2015, ICMR.

[4]  Grgoire Montavon,et al.  Neural Networks: Tricks of the Trade , 2012, Lecture Notes in Computer Science.

[5]  Bo Li,et al.  SHREC'13 Track: Large Scale Sketch-Based 3D Shape Retrieval , 2013, 3DOR@Eurographics.

[6]  Bin Fang,et al.  A comparison of 3D shape retrieval methods based on a large-scale benchmark supporting multimodal queries , 2015, Comput. Vis. Image Underst..

[7]  Bo Li,et al.  3D Sketch-Based 3D Shape Retrieval , 2016, 3DOR@Eurographics.

[8]  Manuel J. Fonseca,et al.  Geometric matching for clip-art drawing retrieval , 2009, J. Vis. Commun. Image Represent..

[9]  Ivan E. Sutherland,et al.  Sketch pad a man-machine graphical communication system , 1964, DAC.

[10]  Fang Wang,et al.  Sketch-based 3D shape retrieval using Convolutional Neural Networks , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[11]  Ryutarou Ohbuchi,et al.  Ranking on Cross-Domain Manifold for Sketch-Based 3D Model Retrieval , 2013, 2013 International Conference on Cyberworlds.

[12]  Christopher F. Herot.  Graphical input through machine recognition of sketches , 1976, SIGGRAPH '76.

[13]  David P. Dobkin,et al.  A search engine for 3D models , 2003, TOGS.

[14]  Tao Xiang,et al.  Sketch-a-Net that Beats Humans , 2015, BMVC.

[15]  Lawrence D. Jackel,et al.  Handwritten Digit Recognition with a Back-Propagation Network , 1989, NIPS.

[16]  Nitish Srivastava,et al.  Improving neural networks by preventing co-adaptation of feature detectors , 2012, ArXiv.

[17]  Thomas A. Funkhouser,et al.  The Princeton Shape Benchmark , 2004, Proceedings Shape Modeling Applications, 2004..

[18]  Marc Alexa,et al.  Sketch-based shape retrieval , 2012, ACM Trans. Graph..

[19]  Fei-Fei Li,et al.  ImageNet: A large-scale hierarchical image database , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[20]  Thomas A. Funkhouser,et al.  Partial matching of 3D shapes with priority-driven search , 2006, SGP '06.

[21]  Tong Lu,et al.  A new recognition model for electronic architectural drawings , 2005, Comput. Aided Des..

[22]  Xiaogang Wang,et al.  Learning Semantic Signatures for 3D Object Retrieval , 2013, IEEE Transactions on Multimedia.

[23]  Randall Davis,et al.  ChemInk: a natural real-time recognition system for chemical drawings , 2011, IUI '11.

[24]  Geoffrey E. Hinton,et al.  ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.

[25]  Marc Alexa,et al.  How do humans sketch objects? , 2012, ACM Trans. Graph..

[26]  Tinne Tuytelaars,et al.  Sketch classification and classification-driven analysis using Fisher vectors , 2014, ACM Trans. Graph..

[27]  Zahabidin Jupri,et al.  A Comparative Study on Extraction and Recognition Method of CAD Data from CAD Drawings , 2009, 2009 International Conference on Information Management and Engineering.