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Sketch-Based Interaction for Planning-Based Interactive Storytelling
Drawings have been used for thousands of years as a visual complement to oral and written storytelling. The evolution of technology and the advent of interactive narratives brings the possibility of exploring drawings and storytelling in new ways. This paper presents a new sketch-based interaction m...
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description | Drawings have been used for thousands of years as a visual complement to oral and written storytelling. The evolution of technology and the advent of interactive narratives brings the possibility of exploring drawings and storytelling in new ways. This paper presents a new sketch-based interaction method for planning-based interactive storytelling systems, which uses a deep learning model based on a Convolutional Neural Network to recognize digital hand-drawn sketches. By combining real time sketch recognition with a planning-based plot generation algorithm, the proposed system allows users to interact with narratives by sketching objects on smartphones or tablet computers, which are then recognized by the system and converted into virtual objects in the story world, thereby affecting the plot of the narrative. Preliminary results show that the sketch recognition model has a remarkable accuracy for small sets of sketch classes (accuracy of 95.1 % for 14 classes), which are sufficient to provide a good variety of interaction options. In addition, it can also be extended to more complex scenarios while maintaining a considerable accuracy (87.4% for 172 classes and 71.6% for 345 classes). |
doi_str_mv | 10.1109/SBGames51465.2020.00029 |
format | conference_proceeding |
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The evolution of technology and the advent of interactive narratives brings the possibility of exploring drawings and storytelling in new ways. This paper presents a new sketch-based interaction method for planning-based interactive storytelling systems, which uses a deep learning model based on a Convolutional Neural Network to recognize digital hand-drawn sketches. By combining real time sketch recognition with a planning-based plot generation algorithm, the proposed system allows users to interact with narratives by sketching objects on smartphones or tablet computers, which are then recognized by the system and converted into virtual objects in the story world, thereby affecting the plot of the narrative. Preliminary results show that the sketch recognition model has a remarkable accuracy for small sets of sketch classes (accuracy of 95.1 % for 14 classes), which are sufficient to provide a good variety of interaction options. 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The evolution of technology and the advent of interactive narratives brings the possibility of exploring drawings and storytelling in new ways. This paper presents a new sketch-based interaction method for planning-based interactive storytelling systems, which uses a deep learning model based on a Convolutional Neural Network to recognize digital hand-drawn sketches. By combining real time sketch recognition with a planning-based plot generation algorithm, the proposed system allows users to interact with narratives by sketching objects on smartphones or tablet computers, which are then recognized by the system and converted into virtual objects in the story world, thereby affecting the plot of the narrative. Preliminary results show that the sketch recognition model has a remarkable accuracy for small sets of sketch classes (accuracy of 95.1 % for 14 classes), which are sufficient to provide a good variety of interaction options. In addition, it can also be extended to more complex scenarios while maintaining a considerable accuracy (87.4% for 172 classes and 71.6% for 345 classes).</description><subject>automated planning</subject><subject>Games</subject><subject>interactive narratives</subject><subject>interactive storytelling</subject><subject>Planning</subject><subject>Servers</subject><subject>sketch recognition</subject><subject>sketch-based interaction</subject><subject>Solid modeling</subject><subject>Tablet computers</subject><subject>Three-dimensional displays</subject><subject>Visualization</subject><issn>2159-6662</issn><isbn>1728184320</isbn><isbn>9781728184326</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2020</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNpdjMtKw0AUQEdBsNZ-gQvzA4n33sm8lrZqLRQUousymdzRaJpIMgj9ewu6cnUW53CEuEYoEMHdVMu13_OksNSqICAoAIDcibhAQxZtKQlOxYxQuVxrTediMU0fx0aiMa60M3FXfXIK7_nST9xkmz7x6ENqhz6Lw5g9d77v2_7tv_7mrErDeEjcdUd9Kc6i7yZe_HEuXh_uX1aP-fZpvVndbvOWQKYcm5qwrmtsmiYahuhdLG0MThnvMOqgApmSAlgyKAN5jDYYcNKr6NGwnIur32_LzLuvsd378bBz5FCjlT-Kh027</recordid><startdate>202011</startdate><enddate>202011</enddate><creator>de Lima, Edirlei Soares</creator><creator>Gheno, Felipe Joao</creator><creator>Viseu, Ana</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>202011</creationdate><title>Sketch-Based Interaction for Planning-Based Interactive Storytelling</title><author>de Lima, Edirlei Soares ; Gheno, Felipe Joao ; Viseu, Ana</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i203t-1db21bbb1dddf7e0fa9f48fc957a91f6c5c2742c082713c2a1f8c7093a5fa17e3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2020</creationdate><topic>automated planning</topic><topic>Games</topic><topic>interactive narratives</topic><topic>interactive storytelling</topic><topic>Planning</topic><topic>Servers</topic><topic>sketch recognition</topic><topic>sketch-based interaction</topic><topic>Solid modeling</topic><topic>Tablet computers</topic><topic>Three-dimensional displays</topic><topic>Visualization</topic><toplevel>online_resources</toplevel><creatorcontrib>de Lima, Edirlei Soares</creatorcontrib><creatorcontrib>Gheno, Felipe Joao</creatorcontrib><creatorcontrib>Viseu, Ana</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE/IET Electronic Library</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>de Lima, Edirlei Soares</au><au>Gheno, Felipe Joao</au><au>Viseu, Ana</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Sketch-Based Interaction for Planning-Based Interactive Storytelling</atitle><btitle>2020 19th Brazilian Symposium on Computer Games and Digital Entertainment (SBGames)</btitle><stitle>SBGAMES</stitle><date>2020-11</date><risdate>2020</risdate><spage>154</spage><epage>162</epage><pages>154-162</pages><eissn>2159-6662</eissn><eisbn>1728184320</eisbn><eisbn>9781728184326</eisbn><coden>IEEPAD</coden><abstract>Drawings have been used for thousands of years as a visual complement to oral and written storytelling. The evolution of technology and the advent of interactive narratives brings the possibility of exploring drawings and storytelling in new ways. This paper presents a new sketch-based interaction method for planning-based interactive storytelling systems, which uses a deep learning model based on a Convolutional Neural Network to recognize digital hand-drawn sketches. By combining real time sketch recognition with a planning-based plot generation algorithm, the proposed system allows users to interact with narratives by sketching objects on smartphones or tablet computers, which are then recognized by the system and converted into virtual objects in the story world, thereby affecting the plot of the narrative. Preliminary results show that the sketch recognition model has a remarkable accuracy for small sets of sketch classes (accuracy of 95.1 % for 14 classes), which are sufficient to provide a good variety of interaction options. In addition, it can also be extended to more complex scenarios while maintaining a considerable accuracy (87.4% for 172 classes and 71.6% for 345 classes).</abstract><pub>IEEE</pub><doi>10.1109/SBGames51465.2020.00029</doi><tpages>9</tpages></addata></record> |
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source | IEEE Xplore All Conference Series |
subjects | automated planning Games interactive narratives interactive storytelling Planning Servers sketch recognition sketch-based interaction Solid modeling Tablet computers Three-dimensional displays Visualization |
title | Sketch-Based Interaction for Planning-Based Interactive Storytelling |
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