Trilingual 3D Script Identification and Recognition using Leap Motion Sensor

Document identifier: oai:DiVA.org:ltu-77257
Access full text here:10.1109/ICDARW.2019.40076
Keyword: Natural Sciences, Computer and Information Sciences, Computer Sciences, Naturvetenskap, Data- och informationsvetenskap, Datavetenskap (datalogi), Air-writing, Leap motion, Word recognition, Script Identification, HMM, Maskininlärning, Machine Learning
Publication year: 2019
Relevant Sustainable Development Goals (SDGs):
SDG 9 Industry, innovation and infrastructure
The SDG label(s) above have been assigned by OSDG.ai

Abstract:

Recently, the development of depth sensing technologies such as Leap motion and Microsoft Kinect sensors facilitate a touch-less environment to interact with computers and mobile devices. Several research have been carried out for the air-written text recognition with the help of these devices. However, there are several countries (like India) where multiple scripts are used to write official languages. Therefore, for the development of an effective text recognition system, the script of the text has to be identified first. The task becomes more challenging when it comes to 3D handwriting. Since, the 3D text written in air is consists of single stoke only. This paper presents a 3D script identification and recognition system written in three languages, namely, Hindi, English and Punjabi using Leap motion sensor. In the first stage, script identification was carried out in one of the three language. Next, Hidden Markov Model (HMM) was used to recognize the words. An accuracy of 96.4% was recorded in script identification whereas accuracies of 72.99%, 73.25% and 60.5% were recorded in script identification of Hindi, English and Punjabi scripts, respectively.

Authors

Rajkumar Saini

Luleå tekniska universitet; EISLAB
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Pradeep Kumar

IIT Roorkee, India
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Shweta Patidar

IIT Roorkee, India
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Partha Roy

IIT Roorkee, India
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Marcus Liwicki

Luleå tekniska universitet; EISLAB
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