Details

Autor(en) / Beteiligte

• Amatya, Smriti
• Ishika
• Kumar, M. V. Manoj
• Prashanth, B. S.
• Sneha, H. R.
• Thomas, Likewin
• Yarlagadda, Vishnu
• Patnaik, L. M.
• Hamsavath, Prasad N.
• Nagaraj, H. C.
• Shetty, N. R.
• Nalini, N.

Titel

Real-Time Hand Gesture Detection Using Convex Hull and Contour Edge Detection

Ist Teil von

• Emerging Research in Computing, Information, Communication and Applications, 2021, Vol.790, p.325-335

Ort / Verlag

Singapore: Springer Singapore Pte. Limited

Erscheinungsjahr

2021

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Hand gesture is a way of communicating through sign languages and presently it has been a hot research topic in the field of Artificial intelligence and Data Science. Contemporary methods for detecting the hand gesture uses optical/mechanical sensors, actuator & accelerometer attached with the glove. This paper proposes a novel method for gesture identification for various hand gestures without using additional equipment (such as sensors or gloves). The proposed method captures the image of the hand gesture then segments it. The real-time hand gesture is tracked down by the convex hull. Convolutional Neural Network is used to detect the area of hand gestures in real-time. The results of the experimental evaluation of the proposed method gave 80% accuracy.