Interpretable Underwater Diver Gesture Recognition
Sudeep Mangalvedhekar Shreyas Nahar Sudarshan Maskare Kaushal Mahajan Dr. Anant Bagade
In recent years, usage and applications of Autonomous Underwater Vehicles has
grown rapidly. Interaction of divers with the AUVs remains an integral part of
the usage of AUVs for various applications and makes building robust and
efficient underwater gesture recognition systems extremely important. In this
paper, we propose an Underwater Gesture Recognition system trained on the
Cognitive Autonomous Diving Buddy Underwater gesture dataset using deep
learning that achieves 98.01\% accuracy on the dataset, which to the best of
our knowledge is the best performance achieved on this dataset at the time of
writing this paper. We also improve the Gesture Recognition System
Interpretability by using XAI techniques to visualize the model's predictions.