Skip to main content Accessibility help
Hostname: page-component-55597f9d44-fnprw Total loading time: 0.588 Render date: 2022-08-12T13:17:00.474Z Has data issue: true Feature Flags: { "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true, "useRatesEcommerce": false, "useNewApi": true } hasContentIssue true

Article contents

Sketch-based interaction and modeling: where do we stand?

Published online by Cambridge University Press:  29 November 2019

Alexandra Bonnici*
Faculty of Engineering, University of Malta, Room 418, MsidaMSD2080, Europe
Alican Akman
Koç University, Istanbul, Turkey
Gabriel Calleja
Faculty of Engineering, University of Malta, Room 418, MsidaMSD2080, Europe
Kenneth P. Camilleri
Faculty of Engineering, University of Malta, Room 418, MsidaMSD2080, Europe
Patrick Fehling
Hochschule für Technik und Wirtschaft, Berlin, Germany
Alfredo Ferreira
Instituto Superior Técnico, Lisbon, Portugal
Florian Hermuth
Hochschule für Technik und Wirtschaft, Berlin, Germany
Johann Habakuk Israel
Hochschule für Technik und Wirtschaft, Berlin, Germany
Tom Landwehr
Hochschule für Technik und Wirtschaft, Berlin, Germany
Juncheng Liu
Peking University, Beijing, China
Natasha M. J. Padfield
Faculty of Engineering, University of Malta, Room 418, MsidaMSD2080, Europe
T. Metin Sezgin
Koç University, Istanbul, Turkey
Paul L. Rosin
Cardiff University, Cardiff, Wales, UK
Author for correspondence: Alexandra Bonnici, E-mail:


Sketching is a natural and intuitive communication tool used for expressing concepts or ideas which are difficult to communicate through text or speech alone. Sketching is therefore used for a variety of purposes, from the expression of ideas on two-dimensional (2D) physical media, to object creation, manipulation, or deformation in three-dimensional (3D) immersive environments. This variety in sketching activities brings about a range of technologies which, while having similar scope, namely that of recording and interpreting the sketch gesture to effect some interaction, adopt different interpretation approaches according to the environment in which the sketch is drawn. In fields such as product design, sketches are drawn at various stages of the design process, and therefore, designers would benefit from sketch interpretation technologies which support these differing interactions. However, research typically focuses on one aspect of sketch interpretation and modeling such that literature on available technologies is fragmented and dispersed. In this paper, we bring together the relevant literature describing technologies which can support the product design industry, namely technologies which support the interpretation of sketches drawn on 2D media, sketch-based search interactions, as well as sketch gestures drawn in 3D media. This paper, therefore, gives a holistic view of the algorithmic support that can be provided in the design process. In so doing, we highlight the research gaps and future research directions required to provide full sketch-based interaction support.

Review Article
Copyright © Cambridge University Press 2019

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)


Ablameyko, S and Pridmore, T (2000) The line drawing interpretation problem. In Ablameyko, S and Pridmore, T (eds), Machine Interpretation of Line Drawing Images: Technical Drawings, Maps and Diagrams. London: Springer, pp. 119.CrossRefGoogle Scholar
Adler, A and Davis, R (2007) Speech and sketching: an empirical study of multimodal interaction. Proceedings of the 4th Eurographics Workshop on Sketch-Based Interfaces and Modelling, Riverside, California, August 02–03, 2007. New York: ACM, pp. 83–90.CrossRefGoogle Scholar
Arora, R, Kazi, RH, Anderson, F, Grossman, T, Singh, K and Fitzmaurice, G (2017) Experimental evaluation of sketching on surfaces in VR. Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, Denver, Colorado, USA, May 06–11, 2017. New York: ACM, pp. 5643–5654.CrossRefGoogle Scholar
Barrera Machuca, MD, Asente, P, Lu, J, Kim, B and Stuerzlinger, W (2017) Multiplanes: assisted freehand VR drawing. Adjunct Publication of the 30th Annual ACM Symposium on User Interface Software and Technology, Québec City, QC, Canada, October 22–25, 2017. New York: ACM, pp. 1–3.CrossRefGoogle Scholar
Bessmeltsev, M and Solomon, J (2019) Vectorization of line drawings via polyvector fields. ACM Transactions on Graphics 38, 9.19.12CrossRefGoogle Scholar
Bonnici, A, Israel, JH, Muscat, AM, Camilleri, D, Camilleri, K and Rothenburg, U (2015) Investigating user response to a hybrid sketch-based interface for creating 3D virtual models in an immersive environment. Proceedings of the 10th International Conference on Computer Graphics Theory and Applications, Berlin, Germany, March 11–14, 2015. Berlin: SCITEPRESS, pp. 470–477.Google Scholar
Bonnici, A, Bugeja, D and Azzopardi, G (2018) Vectorisation of sketches with shadows and shading using COSFIRE filters. Proceedings of the ACM Symposium on Document Engineering, Halifax, NS, Canada, August 28–31, 2018, pp. 1–10.Google Scholar
Canny, J (1986) A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 8, 679698.CrossRefGoogle ScholarPubMed
Cao, L, Liu, J and Tang, X (2008) What the back of the object looks like: 3D reconstruction from line drawings without hidden lines. IEEE Transactions on Pattern Analysis and Machine Intelligence 30, 507517.Google ScholarPubMed
Chen, DY, Tian, XP, Shen, YT and Ouhyoung, M (2003) On visual similarity based 3D model retrieval. Computer Graphics Forum 22, 223232CrossRefGoogle Scholar
Chen, JZ, Lei, Q, Miao, YW and Peng, QS (2015) Vectorization of line drawing image based on junction analysis. Science China Information Sciences 58, 1.Google Scholar
Cherubini, M, Nüssli, MA and Dillenbourg, P (2008) Deixis and gaze in collaborative work at a distance (over a shared map): a computational model to detect misunderstandings. Proceedings of the 2008 Symposium on Eye Tracking Research & Applications, Savannah, Georgia, March 26–28, 2008. New York: ACM.Google Scholar
Chhabra, AK and Phillips, IT (1998) The Second International Graphics Recognition Contest Raster to Vector Conversion: A Report. Graphics Recognition Algorithms and Systems, pp. 390–410.CrossRefGoogle Scholar
Çığ, Ç and Sezgin, TM (2015) Gaze-based prediction of pen-based virtual interaction tasks. International Journal of Human-Computer Studies 73, 91106.CrossRefGoogle Scholar
Clowes, MB (1971) On seeing things. Artificial Intelligence 2, 76116.CrossRefGoogle Scholar
Cole, F, Golovinskiy, A, Limpaecher, A, Barros, HS, Finkelstein, A, Funkhouser, T and Rusinkiewicz, S (2008) Where do people draw lines? ACM Transactions on Graphics 27, 88:188:11.CrossRefGoogle Scholar
Cole, F, Sanik, K, DeCarlo, D, Finkelstein, A, Funkhouser, T, Rusinkiewicz, S and Singh, M (2009) How well do line drawings depict shape? ACM Transactions on Graphics 28, 19.CrossRefGoogle Scholar
Cook, MT and Agah, A (2009) A survey of sketch-based 3D modelling techniques. Interacting with Computers 21, 201211.CrossRefGoogle Scholar
Cooper, M (2008) A rich discrete labelling scheme for line drawings of curved objects. IEEE Transactions on Pattern Analysis and Machine Intelligence 30, 741745.CrossRefGoogle Scholar
Craft, B and Cairns, P (2009) Sketching sketching: outlines of a collaborative design method. Proceedings of the 23rd British HCI Group Annual Conference on People and Computers: Celebrating People and Technology (BCS-HCI ’09), Cambridge, United Kingdom, September 01–05, 2009. Swinton, UK: British Computer Society, pp. 65–72.CrossRefGoogle Scholar
Dai, G, Xie, J and Fang, Y (2018) Deep Correlated Holistic Metric Learning for Sketch-Based 3D Shape Retrieval. IEEE Transactions on Image Processing 27(7), 33743386CrossRefGoogle ScholarPubMed
D'Angelo, S and Gergle, D (2018) An eye for design: gaze visualizations for remote collaborative work. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI ’18), Montreal QC, Canada, April 21–26, 2018. New York, NY, USA: ACM, Paper 349, p. 12, doi:10.1145/3173574.3173923.CrossRefGoogle Scholar
DeCarlo, D, Finkelstein, A, Rusinkiewicz, S and Santella, A (2003) Suggestive contours for conveying shape. ACM Transactions on Graphics 22, 848855.CrossRefGoogle Scholar
Delanoy, J, Aubry, M, Isola, P, Efros, AA and Bousseau, A (2018) 3D sketching using multi-view deep volumetric prediction. Proc. ACM Comput. Graph. Interact. Tech. 1, 1, Article 21 (July 2018), p. 22. doi:10.1145/3203197.CrossRefGoogle Scholar
Dori, D and Wenyin, L (1999) Sparse pixel vectorization: an algorithm and its performance evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 21, No. 3, pp. 202–215.CrossRefGoogle Scholar
Drascic, D and Milgram, P (1996) Perceptual issues in augmented reality. SPIE Stereoscopic Displays and Virtual Reality Systems III, San Jose, CA, United States, Vol. 2653, pp. 123–135.Google Scholar
Eisenstein, J, Barzilay, R and Davis, R (2008) Gesture salience as a hidden variable for coreference resolution and keyframe extraction. Journal of Artificial Intelligence Research 31, 353398.CrossRefGoogle Scholar
Eissen, K and Steur, R (2007) Sketching. Drawing Techniques for Product Designers. Netherlands: BIS Publishers.Google Scholar
Eitz, M, Richter, R, Boubekeur, T, Hildebrand, K and Alexa, M (2012) Sketch-based shape retrieval. ACM Transactions on Graphics 31, 110.Google Scholar
Favreau, J-D, Lafarge, F and Bousseau, A (2016) Fidelity vs. simplicity: a global approach to line drawing vectorization. ACM Transactions on Graphics 35, 120:1120:10.CrossRefGoogle Scholar
Fiorentino, M, De Amicis, R, Stork, A and Monno, G (2002) Surface design in virtual reality as industrial application. Proceedings of the DESIGN Conference, May 14–17, 2002, Cavtat, Dubrovnik, Croatia, pp. 477–482.Google Scholar
Fonseca, MJ, Pimentel, C and Jorge, JA (2002) CALI: an online scribble recognizer for calligraphic interfaces. Sketch Understanding, Papers from the 2002 AAAI Spring Symposium, 25–27 March 2002, Stanford, California.Google Scholar
Gao, C, Tang, M, Liang, X, Su, Z and Zou, C (2018) PencilArt: a chromatic penciling style generation framework. Computer Graphics Forum 37, 395409.CrossRefGoogle Scholar
Heiser, J, Tversky, B and Silverman, M (2004) Sketches for and from collaboration. In Gero, JS, Tversky, B and Knight, T (eds), Visual and Spatial Reasoning in Design III, NSW, Australia: Key Centre of Design Computing and Cognition, University of Sydney, pp. 6978.Google Scholar
Hilaire, X and Tombre, K (2006) Robust and accurate vectorization of line drawings. IEEE Transactions on Pattern Analysis and Machine Interpretation 28, 890904.CrossRefGoogle ScholarPubMed
Huang, G, Liu, Z, Van Der Maaten, L and Weinberger, KQ (2017) Densely connected convolutional networks. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 21–26 July, Hawai, pp. 4700–4708.CrossRefGoogle Scholar
Huffman, D (1971) Impossible objects as nonsense sentences. Machine Intelligence 6, 295324.Google Scholar
Igarashi, T, Matsuoka, S and Tanaka, H (1999) Teddy: a sketching interface for 3D freeform design. Proceedings of the 26th Annual Conference on Computer Graphics and Interactive Techniques, August 8–13, 1999, Los Angeles, California, USA. ACM Press/Addison-Wesley Publishing Co, pp. 409–416.Google Scholar
Isikdogan, F, Bovik, A and Passalacqua, P (2015) Automatic channel network extraction from remotely sensed images by singularity analysis. IEEE Geoscience and Remote Sensing Letters 12, 22182221.CrossRefGoogle Scholar
Israel, JH, Wiese, E, Mateescu, M, Zöllner, C and Stark, R (2009) Investigating three-dimensional sketching for early conceptual design – results from expert discussions and user studies. Computers & Graphics 33, 462473.CrossRefGoogle Scholar
Iwata, H (1993) Pen-based haptic virtual environment. Proceedings of the IEEE Virtual Reality Annual International Symposium, September 18–22, 1993, Seatle, USA, pp. 287–292.CrossRefGoogle Scholar
Judd, T, Durand, F and Adelson, E (2007) Apparent ridges for line drawing. ACM Transactions on Graphics 26, 19.119.7CrossRefGoogle Scholar
Kang, H, Lee, S and Chui, CK (2007) Coherent line drawing. Proceedings of the 5th International Symposium on Non-Photorealistic Animation and Rendering, San Diego, California, August 04–05, 2007. New York: ACM, pp. 43–50.Google Scholar
Katz, RA and Pizer, SM (2004) Untangling the Blum medial axis transform. International Journal of Computer Vision 55, 139153.CrossRefGoogle Scholar
Keefe, DF, Feliz, DA, Moscovich, T, Laidlaw, DH and LaViola, JJ Jr (2001) Cavepainting: a fully immersive 3D artistic medium and interactive experience. Proceedings of the 2001 Symposium on Interactive 3D Graphics. New York: ACM, pp. 85–93.Google Scholar
Keefe, D, Zeleznik, R and Laidlaw, D (2007) Drawing on air: input techniques for controlled 3D line illustration. IEEE Transactions on Visualization and Computer Graphics 13, 10671081.CrossRefGoogle ScholarPubMed
Keysers, D and Breuel, T (2006) Optimal line and arc detection on run-length representations. Proceedings of the Graphics Recognition Workshop, Hong Kong, China, August 25–26, 2005. LNCS, Springer.CrossRefGoogle Scholar
Kiritsis, D (2011) Closed-loop PLM for intelligent products in the era of the Internet of things. Computer-Aided Design 43, 479501.CrossRefGoogle Scholar
Kirk, D, Rodden, T and Stanton Fraser, D (2007) Turn it this way: grounding collaborative action with remote gestures. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, San Jose, California, USA, April 28–May 03, 2007. New York: ACM, pp. 1039–1048.Google Scholar
Kyratzi, S and Sapidis, N (2009) Extracting a polyhedron from a single-view sketch: topological construction of a wireframe sketch with minimal hidden elements. Computers & Graphics 33, 270279.CrossRefGoogle Scholar
Landay, JA and Myers, BA (1995) Interactive sketching for the early stages of user interface design. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Denver, Colorado, USA, May 07–11, 1995. Denver, Colorado, USA: ACM Press/Addison-Wesley Publishing Co, pp. 43–50.CrossRefGoogle Scholar
Leopold, HA, Orchard, J, Zelek, JS and Lakshminarayanan, V (2019) PixelBNN: augmenting the pixelCNN with batch normalization and the presentation of a fast architecture for retinal vessel segmentation. Journal of Imaging 5, 26.CrossRefGoogle Scholar
Li, C, Liu, X and Wong, T (2017) Deep extraction of manga structural lines. ACM Transactions on Graphics 36, Article 117.CrossRefGoogle Scholar
Li, C, Pan, H, Liu, Y, Tong, X, Sheffer, A and Wang, W (2018) Robust flow-guided neural prediction for sketch-based freeform surface modeling. ACM Transactions on Graphics 37, Article 238. doi:10.1145/3272127.3275051.CrossRefGoogle Scholar
Lins, RD, de Almeida, MM, Bernardino, RB, Jesus, D and Oliveira, JM (2017) Assessing binarization techniques for document images. Proceedings of the 2017 ACM Symposium on Document Engineering, 4th–7th September 2017, Valletta, Malta. Malta: ACM, pp. 183–192.CrossRefGoogle Scholar
Lipson, H and Shpitalni, M (2007) Correlation-based reconstruction of a 3D object from a single freehand sketch. ACM SIGGRAPH 2007 Courses, San Diego, California, August 05–09, 2007. New York: ACM, p. 44.CrossRefGoogle Scholar
Liu, J, Chen, Y and Tang, X (2011) Decomposition of complex line drawings with hidden lines for 3D planar-faced manifold object reconstruction. IEEE Transactions on Pattern Analysis and Machine Intelligence 33, 315.Google ScholarPubMed
Lu, C, Xu, L and Jia, J (2012) Combining sketch and tone for pencil drawing production. Proceedings of the Symposium on Non-Photorealistic Animation and Rendering, Annecy, France, June 04–06, 2012. Germany: Eurographics Association, pp. 65–73.Google Scholar
Lugt, RVD (2002) Functions of sketching in design idea generation meetings. Proceedings of the 4th Conference on Creativity & Cognition. Loughborough, UK: ACM, pp. 72–79.Google Scholar
Lun, Z, Gadelha, M, Kalogerakis, E, Maji, S and Wang, R (2017) 3D shape reconstruction from sketches via multi-view convolutional networks. 2017 International Conference on 3D Vision (3DV), 10–12 October 2017, Qingdao, China. IEEE, pp. 67–77.CrossRefGoogle Scholar
Marin, D, Aquino, A, Gegundez-Arias, ME and Bravo, JM (2011) A new supervised method for blood vessel segmentation in retinal images by using grey-level and moment invariant-based features. IEEE Transactions on Medical Imaging 30, 146158.CrossRefGoogle Scholar
Masry, M and Lipson, H (2007) A sketch-based interface for iterative design and analysis of 3D objects. ACM SIGGRAPH 2007 Courses, San Diego, California, August 05–09, 2007. ACM, p. 31.CrossRefGoogle Scholar
Massie, TH and Salisbury, JK (1994) The PHANToM haptic interface: a device for probing virtual objects. Proceedings of the ASME Winter Annual Meeting, Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, November 1994, Chicago, USA, Vol. 55(1), pp. 295–300.Google Scholar
Mitani, J, Suzuki, H and Kimura, F (2002) 3D sketch: sketch-based model reconstruction and rendering. In Cugini, U and W ozny, M (eds), From Geometric Modelling to Shape Modelling, Kluwer International Federation For Information Processing Series, Vol. 208. Norwell, MA: Kluwer Academic Publishers, pp. 8598.CrossRefGoogle Scholar
Monk, AF and Gale, C (2002) A look is worth a thousand words: full gaze awareness in video-mediated conversation. Discourse Processes 33, 257278.CrossRefGoogle Scholar
Munehiro, N and Huang, TS (2001) An interactive 3D visualization for content-based image retrieval. Proceedings of the IEEE International Conference on Multimedia, 22–25 August 2001, Tokyo, Japan, Japan, pp. 22–25.Google Scholar
Nealen, A, Igarashi, T, Sorkine, O and Alexa, M (2007) Fibermesh: designing free-form surfaces with 3D curves. ACM Transactions on Graphics 26, 41.141.9CrossRefGoogle Scholar
Nguyen-Phuoc, TH, Li, C, Balaban, S and Yang, Y (2018) RenderNet: a deep convolutional network for differentiable rendering from 3D shapes. Advances in Neural Information Processing Systems, Montréal, Canada, December 03–08, 2018, pp. 7891–7901.Google Scholar
Noris, G, Hornung, A, Sumner, RW, Simmons, M and Gross, M (2013) Topology-driven vectorization of clean line drawings. ACM Transactions on Graphics 32, 111.CrossRefGoogle Scholar
Norman, DA (2010) Natural user interfaces are not natural. Interactions 17, 610.CrossRefGoogle Scholar
Olsen, L, Samavati, F, Sousa, MC and Jorge, J (2008) A Taxonomy of Modelling Techniques Using Sketch-Based Interfaces. Eurographics state of the art reports, 1 (1.4), 1.Google Scholar
Olsen, L, Samavati, F and Jorge, J (2011) NaturaSketch: modeling from images and natural sketches. IEEE Transactions on Computer Graphics and Applications 31, 2434.CrossRefGoogle ScholarPubMed
Oviatt, S, Cohen, P, Wu, L, Vergo, J, Duncan, L, Suhm, B, Bers, J, Holzman, T, Winograd, T, Landay, J, Larson, J and Ferro, D (2000) Designing the user interface for multimodal speech and pen-based gesture applications: state-of-the-art systems and future research directions. Human-Computer Interaction 15, 263322.CrossRefGoogle Scholar
Pham, T-A, Delalandre, M, Barrat, S and Ramel, J-Y (2014) Accurate junction detection and characterization in line-drawing images. Pattern Recognition 47, 282295.CrossRefGoogle Scholar
Pu, J and Ramani, K (2005) A 3D model retrieval method using 2D freehand sketches. Computational Science, ICCS 2005, Atlanta, GA, May 22–25, 2005. Springer Berlin Heidelberg, pp. 343–346.CrossRefGoogle Scholar
Ramel, JY, Vincent, N and Emptoz, H (1998) A coarse vectorization as an initial representation for the understanding of line drawing images. In Blostein, D and Kwon, Y-B (eds), Lecture Notes in Computer Science, Graphics Recognition – Algorithms and Applications, Vol. 1389. Berlin, Germany: Springer-Verlag, pp. 4857.Google Scholar
Ren, JS and Xu, L (2015) On vectorization of deep convolutional neural networks for vision tasks. Proceedings of the 29th AAAI Conference on Artificial Intelligence, January 25–30, 2015, Austin Texas, USA.Google Scholar
Ronneberger, O, Fischer, P and Brox, T (2015) U-net: Convolutional networks for biomedical image segmentation. In Navab, N, Hornegger, J, Wells, W and Frangi, A (eds), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015. MICCAI 2015. Lecture Notes in Computer Science, Vol. 9351. Cham: Springer, pp. 234241.Google Scholar
Ros, L and Thomas, F (2002) Overcoming superstrictness in line drawing interpretation. IEEE Transactions on Pattern Analysis and Machine Intelligence 24, 456466.CrossRefGoogle Scholar
Schkolne, S, Pruett, M and Schröder, P (2001) Surface drawing: creating organic 3D shapes with the hand and tangible tools. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, March 31–April 5 in Seattle, Washington, USA. New York: ACM, pp. 261–268.CrossRefGoogle Scholar
Schlösser, C (2018) Towards concise gaze sharing. Proceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications (ETRA ’18), Warsaw, Poland, June 14–17, 2018. New York, NY, USA: ACM, Article 78, p. 3, doi:10.1145/3204493.3207416.Google Scholar
Schütze, M, Sachse, P and Römer, A (2003) Support value of sketching in the design process. Research in Engineering Design 14, 8997.Google Scholar
Schweikardt, E and Gross, MD (2000) Digital clay: deriving digital models from freehand sketches. Automation in Construction 9, 107115.Google Scholar
Shilane, P, Min, P, Kazhdan, M and Funkhouser, T (2004) The Princeton shape benchmark. Proceedings on Shape Modelling Applications, 7–9 June 2004, Genova, Italy, pp. 167–178.CrossRefGoogle Scholar
Simo-Serra, E, Iizuka, S, Sasaki, K and Ishikawa, H (2016) Learning to simplify: fully convolutional networks for rough sketch cleanup. ACM Transactions on Graphics 35, Article 121.CrossRefGoogle Scholar
Skwarek, M (2013) CreatAR: Augmented reality app. ACM SIGGRAPH 2013 Mobile, Anaheim, California, July 21–25, 2013, pp. 21:1–21:1.CrossRefGoogle Scholar
Soares, JVB, Leandro, JJG, Cesar, RM, Jelinek, HF and Cree, MJ (2006) Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification. IEEE Transactions on Medical Imaging 25, 12141222.Google ScholarPubMed
Song, J, Su, F, Chen, J, Tai, C and Cai, S (2002) An object-oriented progressive-simplification-based vectorization system for engineering drawings: model, algorithm, and performance. IEEE Transactions on Pattern Analysis and Machine Intelligence 24, 10481060.CrossRefGoogle Scholar
Steger, C (1998) An unbiased detector of curvilinear structures. IEEE Transactions on Pattern Analysis and Machine Intelligence 20, 113125.CrossRefGoogle Scholar
Strasnick, E, Holz, C, Ofek, E, Sinclair, M and Benko, H (2018) Haptic links: Bimanual haptics for virtual reality using variable stiffness actuation. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, Montreal QC, Canada, April 21–26, 2018, Vol. 644. New York: ACM, pp. 1–12.CrossRefGoogle Scholar
Sudarsan, R, Fenves, SJ, Sriram, RD and Wang, F (2005) A product information modeling framework for product lifecycle management. Computer-Aided Design 37, 13991411.CrossRefGoogle Scholar
Szeliski, R (2010) Computer Vision: Algorithms and Applications. London: Springer-Verlag.Google Scholar
Tombre, K, Ah-Soon, C, Dosch, P, Masini, G and Tabbone, S (2000) Stable and robust vectorization: how to make the right choices. In Chhabra, AK and Dori, D (eds), Graphics Recognition Recent Advances. GREC 1999. Lecture Notes in Computer Science, Vol. 1941. Berlin, Heidelberg: Springer, pp. 318.Google Scholar
Tversky, B and Suwa, M (2009) Thinking with sketches. In Markman, AB and Wood, KL (eds), Tools for Innovation: The Science behind the Practical Methods That Drive New Ideas. New York, NY, USA: Oxford University Press, pp. 7584.Google Scholar
Varley, P (2009) The use of neighbourhood matching in constructing hidden object topology. Proceedings of the World Congress on Engineering, July 1–3, 2009, London, U.K., Vol. 1.Google Scholar
Wacker, P, Voelker, S, Wagner, A and Borchers, J (2018) Physical guides: an analysis of 3D sketching performance on physical objects in augmented reality. Proceedings of the Symposium on Spatial User Interaction - SUI ‘18, Berlin, Germany, October 13–14, 2018. New York, NY, USA: ACM Press, pp. 25–35, doi:10.1145/3267782.3267788.CrossRefGoogle Scholar
Waltz, D (1975) Understanding line drawings of scenes with shadows. In Winston, PH (ed.), The Psychology of Computer Vision. McGraw-Hill, pp. 1991, Chap. 2.Google Scholar
Wang, F, Kang, L and Li, Y (2015) Sketch-based 3D shape retrieval using convolutional neural networks. IEEE Conference on Computer Vision and Pattern Recognition, 7–12 June 2015, Boston, MA, USA.Google Scholar
Wiese, E, Israel, JH, Meyer, A and Bongartz, S (2010) Investigating the learnability of immersive free-hand sketching. Proceedings of the Seventh Sketch-Based Interfaces and Modeling Symposium, Annecy, France, June 07–10, 2010. Eurographics Association, pp. 135–142.Google Scholar
Xie, J, Dai, G, Zhu, F and Fang, Y (2017) Learning barycentric representations of 3D shapes for sketch-based 3D shape retrieval. 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, 2017, pp. 36153623.CrossRefGoogle Scholar
Xu, B, Chang, W, Sheffer, A, Bousseau, A, McCrae, J and Singh, K (2014) True2form: 3D curve networks from 2D sketches via selective regularization. ACM Transactions on Graphics 33, 131.1131.13CrossRefGoogle Scholar
Xu, Y, Xie, Z, Feng, Y and Chen, Z (2018) Road extraction from high-resolution remote sensing imagery using deep learning. Remote Sensing 10, 14611476CrossRefGoogle Scholar
Ye, M and Zhou, S (2019) DeepShapeSketch: Generating hand drawing sketches from 3D objects. International Joint Conference on Neural Networks, pg 1-8, 14-19 July 2019, Budapest, Hungary.CrossRefGoogle Scholar
Yoon, SM, Scherer, M, Schreck, T and Kuijper, A (2010) Sketch-based 3D model retrieval using diffusion tensor fields of suggestive contours. Proceedings of the 18th ACM International Conference on Multimedia, Firenze, Italy, October 25–29, 2010. New York: ACM, pp. 193–200.CrossRefGoogle Scholar
Zeleznik, RC, Herndon, KP and Hughes, JF (2006) SKETCH: An interface for sketching 3D scenes. ACM SIGGRAPH 2006 Courses, Boston, Massachusetts, July 30–August 03, 2006. New York: ACM.CrossRefGoogle Scholar
Zhu, Fan, Xie, Jin and Fang, Yi (2016) Learning cross-domain neural networks for sketch-based 3D shape retrieval. Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI'16), Phoenix, Arizona, USA, February 12–17, 2016, pp. 3683–3689.Google Scholar
Cited by

Save article to Kindle

To save this article to your Kindle, first ensure is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the or variations. ‘’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Sketch-based interaction and modeling: where do we stand?
Available formats

Save article to Dropbox

To save this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Dropbox account. Find out more about saving content to Dropbox.

Sketch-based interaction and modeling: where do we stand?
Available formats

Save article to Google Drive

To save this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Google Drive account. Find out more about saving content to Google Drive.

Sketch-based interaction and modeling: where do we stand?
Available formats

Reply to: Submit a response

Please enter your response.

Your details

Please enter a valid email address.

Conflicting interests

Do you have any conflicting interests? *