TY - GEN
T1 - Hand Gesture Recognition Using Convex Hull-Based Approach
AU - Wani, Kaustubh
AU - Ramya, S.
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2022
Y1 - 2022
N2 - Gesture recognition is a tool that can be used to control any common device by effortless hand gestures. The goal behind gesture recognition is to minimize the gap between the digital world and the physical world. This wireless interaction creates this algorithm much friendlier to the user. This paper tells the technological characteristics of gesture-controlled user interface (GCUI), and also recognizes its trend and application. It is observed that GCUI now offers practical opportunities for application-specific areas, especially for people who are not comfortable with input devices which are commonly used. This project implements an advanced image processing application to recognize the gestures and process them in real time for better and reliable results. To recognize the gesture the ratio of the percentage of area not covered by hand in the convex hull is found. The optimized code is easily integrated with a Raspberry-Pi processor or microcontroller for a fully functional robot.
AB - Gesture recognition is a tool that can be used to control any common device by effortless hand gestures. The goal behind gesture recognition is to minimize the gap between the digital world and the physical world. This wireless interaction creates this algorithm much friendlier to the user. This paper tells the technological characteristics of gesture-controlled user interface (GCUI), and also recognizes its trend and application. It is observed that GCUI now offers practical opportunities for application-specific areas, especially for people who are not comfortable with input devices which are commonly used. This project implements an advanced image processing application to recognize the gestures and process them in real time for better and reliable results. To recognize the gesture the ratio of the percentage of area not covered by hand in the convex hull is found. The optimized code is easily integrated with a Raspberry-Pi processor or microcontroller for a fully functional robot.
UR - https://www.scopus.com/pages/publications/85115074246
UR - https://www.scopus.com/pages/publications/85115074246#tab=citedBy
U2 - 10.1007/978-981-16-2911-2_17
DO - 10.1007/978-981-16-2911-2_17
M3 - Conference contribution
AN - SCOPUS:85115074246
SN - 9789811629105
T3 - Lecture Notes in Electrical Engineering
SP - 161
EP - 170
BT - Advances in Communication, Devices and Networking - Proceedings of ICCDN 2020
A2 - Dhar, Sourav
A2 - Mukhopadhyay, Subhas Chandra
A2 - Sur, Samarendra Nath
A2 - Liu, Chuan-Ming
PB - Springer Science and Business Media Deutschland GmbH
T2 - 4th International Conference on Communication, Device and Networking, ICCDN 2020
Y2 - 19 December 2020 through 20 December 2020
ER -