Notice of retraction
Vol. 32, No. 8(2), S&M2292

ISSN (print) 0914-4935
ISSN (online) 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

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S&M2352 Research Paper of Special Issue

Human and Robotic Fish Interaction Controlled Using Hand Gesture Image Processing

Amarnathvarma Angani, Jin-Wook Lee, Teressa Talluri, Jae-young Lee, and Kyoo Jae Shin

(Received April 17, 2020; Accepted August 11, 2020)

Keywords: aquarium robot, image sensors, biomimetic ornamental, hand gesture recognition, hand segmentation, human interactive control

This paper is about the control of robotic fish movement in an aquarium via human hand gestures detected by image sensors attached in the aquarium. In this study, sensors actively interact with humans and robotic fish. Image and radio frequency sensors are used to identify the position and color of robotic fish. Recently, we have studied human interactive control based on hand gesture recognition. Image sensors send the input signals of hand gestures obtained from real-time video images processed using tracking control algorithms, such as color mark, stop zone, and lead-lag tracking algorithms, to robotic fish. The movement of robotic fish is controlled via the movement of the two hands, where the left hand is for the fish to be controlled and the right hand for controlling the movement of the robotic fish. Hand gesture recognition consists of hand feature segmentation and gesture recognition from the hand features. Our results show that interactive human control using hand gestures successfully controls the movement of robotic fish.

Corresponding author: Kyoo Jae Shin

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