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Sketch recognition

About: Sketch recognition is a research topic. Over the lifetime, 1611 publications have been published within this topic receiving 40284 citations.


Papers
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Proceedings ArticleDOI
15 Dec 2014
TL;DR: An algorithm for robot navigation which combining gesture recognition with speech recognition is proposed, which reduces the computational complexity of algorithm and makes the human-computer interaction more simple, clear and natural.
Abstract: Human-computer interaction is a hot topic in artificial intelligence. Artificial navigation is an interesting application of human-computer interaction, which control the action of the target device by speech or gestures information. The main virtue of artificial navigation is that it can control target device within a distance without any remote control device. This technology can be used in the areas of robot navigation, vehicle navigation in the industrial site and virtual reality. This paper proposed an algorithm for robot navigation which combining gesture recognition with speech recognition. Firstly, use nine gesture instructions and nine voice commands to establish reference models. Secondly, extract real-time Skeleton information and the current speech messages by Kinect. Thirdly, evaluate the fitness of the current gesture and speech information of the reference model. Finally, deduce the navigation control instructions to command the robot's movement. Gestures and speech can compensate for each other's deficiencies, improve the recognition rate and robustness of the algorithm, reduce the computational complexity of algorithm, makes the human-computer interaction more simple, clear and natural.

10 citations

Proceedings ArticleDOI
01 Dec 2016
TL;DR: This work analyzes two main approaches for expression recognition and describes their applications in non-verbal human communication and research in several areas.
Abstract: The identification of facial expressions with human emotions plays a key role in non-verbal human communication and has applications in several areas. In this work, we analyze two main approaches for expression recognition.

10 citations

Proceedings ArticleDOI
12 Dec 1961
TL;DR: A particular hypothetical machine model for shape recognition provides means for detecting classes of patterns which would or would not be ambiguous with respect to any of the patterns that are recognizable.
Abstract: Graphic pattern recognition in the development of total systems for information selection and retrieval is considered. A particular hypothetical machine model for shape recognition is described. Examples are given of recognition of 12 to 20 categories of geometric shapes, by use of a contour-projection principle. Within certain limitations, the model identifies these graphic patterns, regardless of size, location, and certain rotational transformations. It provides means for detecting classes of patterns which would or would not be ambiguous with respect to any of the patterns that are recognizable. Problems in practical application, including possibilities for recognition of constrained handdrawn figures, are considered. Possible means of implementation are also discussed.

10 citations

Dissertation
01 Jan 2011
TL;DR: By developing more accurate recognisers, greater functionality can be supplied by computer-based sketch tools and automatic recognition of sketches enables benefits, such as the translation and execution of sketched models, and intelligent editing.
Abstract: Computer-based diagramming is often cumbersome to achieve with typical mouse and keyboard input. With recent advances in hardware, such as touch and stylus detection, computer-based sketch tools can offer a similar interaction experience to pen and paper. By imitating the pen and paper environment, sketch tools permit the quick construction of diagrams. Automatic recognition of sketches enables benefits, such as the translation and execution of sketched models, and intelligent editing (see Figure 1). By developing more accurate recognisers, greater functionality can be supplied by computer-based sketch tools.

10 citations

Proceedings ArticleDOI
10 Oct 2007
TL;DR: To simplify the creation of sketch recognition system, a language to describe how shapes in a domain are drawn, displayed, and edited for use in sketch recognition, and GUILD, a system to automatically generate user interfaces from LADDER descriptions are built.
Abstract: Instructors and students sketch graphical diagrams in a variety of classes from pre-K through higher education. Hand sketching the diagrams can engage students' creative processes as they watch the diagrams being created in real-time. Animations can help a students' functional understanding. However, hand-sketched diagrams currently remain static and uninterpreted, and animations currently have to be canned pre-made diagrams. Sketch recognition systems recognize hand drawn diagrams, but they take a lot of time and effort to build and require expertise in sketch recognition programming. To simplify the creation of sketch recognition system, we have built LADDER, a language to describe how shapes in a domain are drawn, displayed, and edited for use in sketch recognition, and GUILD, a system to automatically generate user interfaces from LADDER descriptions. The goal of this work is to facilitate the development of sketch recognition systems to allow non-experts in sketch recognition systems, such as teachers develop sketch systems for their classroom. The research is continuously being improved, but thus far, over twenty people have built sketch recognition systems using these technologies.

10 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202326
202271
202130
202029
201946
201827