Topic
Sketch recognition
About: Sketch recognition is a research topic. Over the lifetime, 1611 publications have been published within this topic receiving 40284 citations.
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23 Mar 2022TL;DR: In this paper , an approach to recognize hand gestures is introduced, and a virtual mouse and keyboard with hand gesture recognition using Computer Vision techniques are implemented, and full keyboard features and mouse cursor movement and click events are implemented to control the computer virtually.
Abstract: Human-Computer Interaction (HCI) is the interface between humans and computers. Traditionally, mouse and keyboards are used to interact with computers. An approach recently introduced to interact with computers is hand gestures. In this research paper, an approach to recognize hand gestures is introduced, and a virtual mouse and keyboard with hand gesture recognition using Computer Vision techniques are implemented. Full keyboard features and mouse cursor movement and click events are implemented to control the computer virtually. The recognition rate and response rate of all the considered inputs are calculated and presented in the results. The accuracy of the presented approach is compared with the other state-of-the-art algorithms that show the method presented here performs better with the accuracy of 95%.
3 citations
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04 Dec 2008TL;DR: A powerful shape representation to recognize sketches drawn on a pen-based input device is proposed by using the combination of distance map and direction histogram, which represents rich information to recognize an input sketch.
Abstract: We propose a powerful shape representation to recognize sketches drawn on a pen-based input device. The proposed method is robust to the sketching order by using the combination of distance map and direction histogram. A distance map created after normalizing a freehand sketch represents a spatial feature of shape regardless of the writing order. Moreover, a distance map which acts a spatial feature is more robust to shape variation than chamfer distance. Direction histogram is also able to extract a directional feature unrelated to the drawing order by using the alignment of the spatial location between two neighboring points of the stroke. The combination of these two features represents rich information to recognize an input sketch. The experiment result demonstrates the superiority of the proposed method more than previous works. It shows 96% recognition performance for the experimental database, which consists of 28 freehand sketches and 10 on-line handwritten digits.
3 citations
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15 Oct 2012TL;DR: The system is designed to infer designers' intention and recognizes the input single strokes into more 2D geometric primitives including line-segments, polylines, circles, circular arcs, ellipses, elliptical arcs, hyperbolas and parabolas.
Abstract: This paper proposes a novel method using geometric-based classifiers, to recognize stroke as geometric primitives and develops a human-computer interface prototype system (FSR) for assisting designers during conceptual design stages, which make system interface easy and friendly to use. The system is designed to infer designers' intention and recognizes the input single strokes into more 2D geometric primitives including line-segments, polylines, circles, circular arcs, ellipses, elliptical arcs, hyperbolas and parabolas. The geometric features are invariant with rotation of figures, including polygonal approximation points, enclosing rectangle, least medium squares error. The filters and fuzzy classifiers are built from these geometric features. The human interaction can help to determine or revise the ambiguous results or misrecognitions. The test results showed that the proposed method can support freehand sketching based conceptual design with a satisfactory interpretation rate.
3 citations
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30 Aug 1992
TL;DR: The authors propose an approach to define objects qualitatively and hierarchically by generic shapes (primitives) arranged by generic relations so that a class of objects has the same description and to recognize them in a parallel and bottom-up way in the image.
Abstract: The authors propose an approach to define objects qualitatively and hierarchically by generic shapes (primitives) arranged by generic relations so that a class of objects has the same description and to recognize them in a parallel and bottom-up way in the image. >
3 citations