Real-time Indian Sign Language (ISL) Recognition
Kartik Shenoy, Tejas Dastane, Varun Rao, Devendra Vyavaharkar

TL;DR
This paper introduces a real-time ISL recognition system using grid-based features, achieving high accuracy without external hardware, to facilitate communication for the hearing impaired.
Contribution
The system uniquely combines grid-based feature extraction with remote processing, achieving high accuracy in static and gesture recognition without external devices.
Findings
99.7% accuracy for static hand poses
97.23% accuracy for gesture recognition
Real-time recognition on smartphone camera input
Abstract
This paper presents a system which can recognise hand poses & gestures from the Indian Sign Language (ISL) in real-time using grid-based features. This system attempts to bridge the communication gap between the hearing and speech impaired and the rest of the society. The existing solutions either provide relatively low accuracy or do not work in real-time. This system provides good results on both the parameters. It can identify 33 hand poses and some gestures from the ISL. Sign Language is captured from a smartphone camera and its frames are transmitted to a remote server for processing. The use of any external hardware (such as gloves or the Microsoft Kinect sensor) is avoided, making it user-friendly. Techniques such as Face detection, Object stabilisation and Skin Colour Segmentation are used for hand detection and tracking. The image is further subjected to a Grid-based Feature…
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Taxonomy
TopicsHand Gesture Recognition Systems · Hearing Impairment and Communication · Gait Recognition and Analysis
