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dc.contributor.authorHerrera-Camara, Jorge-Ivanen_US
dc.contributor.authorHammond, Tracyen_US
dc.contributor.editorHolger Winnemoeller and Lyn Bartramen_US
dc.date.accessioned2017-10-18T08:37:19Z
dc.date.available2017-10-18T08:37:19Z
dc.date.issued2017
dc.identifier.isbn978-1-4503-5080-8
dc.identifier.issn1812-3503
dc.identifier.urihttp://dx.doi.org/10.1145/3092907.3092911
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/sbim2017a03
dc.description.abstractFlowcharts play an important role when learning to program by conveying algorithms graphically and making them easy to read and understand. Computer-based owchart design requires the user to learn the so ware rst, which o en results in a steep learning curve. Paper-drawn owcharts don't provide feedback. We propose a system that allows users to draw their owcharts directly on paper combined with a mobile phone app that takes a photo of the owchart, interprets it, and generates and executes the resulting code. Flow2Code uses o -line sketch recognition and computer vision algorithms to recognize owcharts drawn on paper. To gain practice and feedback with owcharts, the user needs only a pencil, white paper, and a mobile device. e paper describes a tested system and algorithmic model for recognizing and interpreting o ine owcharts as well as a novel geometric feature, Axis Aligned Score (AAS), that enables fast accurate recognition of various quadrilaterals.en_US
dc.publisherAssociation for Computing Machinery, Inc (ACM)en_US
dc.subjectHuman
dc.subjectcentered computing
dc.subjectInteractive systems and tools
dc.subjectApplied computing
dc.subjectComputer
dc.subjectassisted instruction
dc.subjectSketch
dc.subjectbased interface
dc.subjectsketch recognition
dc.subjecteducational so ware
dc.subjectsketching
dc.titleFlow2Code: From Hand-drawn Flowcharts to Code Executionen_US
dc.description.seriesinformationSketch-Based Interfaces and Modeling
dc.description.sectionheadersSketching
dc.identifier.doi10.1145/3092907.3092911


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