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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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Book ChapterDOI
04 Jun 2009
TL;DR: A new gesture recognition method is proposed which can get a recognition result of human gestures before the gestures have finished, and it is realized by using sparse codes of Self-Organizing Map.
Abstract: We propose a new gesture recognition method which is called "early recognition". Early recognition is a method to recognize sequential patterns at their beginning parts. Therefore, in the case of gesture recognition, we can get a recognition result of human gestures before the gestures have finished. We realize early recognition by using sparse codes of Self-Organizing Map.

11 citations

Proceedings ArticleDOI
12 Jun 2015
TL;DR: The proposed fusion algorithm provides a high recognition rate as compared to discrete approaches and is a part of the project that aims at designing a real time system that would recognize sign language accurately.
Abstract: Hand gestures serve as primary tools for man-machine interaction. Hand Gesture Recognition System provides a natural, innovative and modern way on non verbal communication. A wide area of applications in Human Computer Interaction and Sign Language Recognition are available over last decade. This paper is a part of the project that aims at designing a real time system that would recognize sign language accurately. The gestures are recognized through camera based and 5DT data glove based systems respectively and these are combined to increase the recognition rate. The proposed fusion algorithm provides a high recognition rate as compared to discrete approaches.

11 citations

Journal ArticleDOI
TL;DR: This is the first comprehensive survey of recognition tasks based on sketch generation, freehand sketch classification, sketch-based image retrieval (SBIR), fine-grained sketch- based image retrieval(s), and Sketch-based 3D shape image retrieval.

11 citations

Journal ArticleDOI
TL;DR: Pattern recognition and q-Bernstein polynomials have been combined to create computer software designed for the recognition of human speech, and the main principles of speech recognition have been explained in a systematic content.
Abstract: Recognition of human speech has long been a hot topic among artificial intelligence and signal processing researchers. In this paper, Pattern recognition and q-Bernstein polynomials have been combined to create computer software designed for the recognition of human speech, and the main principles of speech recognition have been explained in a systematic content. qBernstein polynomials, which are mathematical operators, have been applied for pattern recognition, and a new method has thus been developed. Software has been prepared using the Delphi 7 programming language, and with this software, this method has been applied for the processing of verbal expression recognition. In the program as developed, 16 000 samples of 8-bit stereo images were computerized. Speech recognition tests were conducted for six words, and information related to the results of this test is provided in this paper.

11 citations

Proceedings Article
01 Jan 2008
TL;DR: The work in the paper describes the geometric-based MPS1 recognition system, a system designed particularly for novice users of Mps1 symbols that gives reasonable vision-based recognition rates and provides useful feedback for symbols drawn with incorrect sketching technique such as stroke order.
Abstract: Inputting written Chinese, unlike written English, is a non-trivial operation using a standard keyboard. To accommodate this operation, numerous existing phonetic systems using the Roman alphabet were adopted as a means of input while still making use of a Western keyboard. With the growing prevalence of computing devices capable of pen-based input, naturally sketching written Chinese using a phonetic system becomes possible, and is also generally faster and simpler than sketching entire Chinese characters. One method for sketching Chinese characters for computing devices capable of pen-based input involves using an existing non-alphabetic phonetic system called the Mandarin Phonetic Symbols I (MPS1). The benefits of inputting Chinese characters by its corresponding MPS1 symbols – unlike letters from its alphabetic-based counterpart – is that it retains the phonemic components of the corresponding Chinese characters. The work in the paper describes our geometric-based MPS1 recognition system, a system designed particularly for novice users of MPS1 symbols that gives reasonable vision-based recognition rates and provides useful feedback for symbols drawn with incorrect sketching technique such as stroke order.

11 citations


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