![]() ![]() Despite having structured vocal languages in every country, sign languages are still used primarily for communication with the deaf and hard-of-hearing community. Recent researchers have found around 6700 spoken languages 1 and several hundred sign languages 2, although a good number of them are not currently in use. Later, with the progress of civilization, people adopted structured languages and used hand gesture-based communication in special cases. However, the first mode of communication was not a structured vocal language but involved gestures, often using hands. At the same time, it created the social attributes among us which had been modified over the centuries and transformed us into civilized beings. Similar content being viewed by othersįrom the dawn of human civilization, communication between humans has been the single most important trait for our survival. The dataset used in this work has been made publicly available. ![]() ![]() Overall, this study demonstrates the promising performance of a generalized hand gesture recognition technique in hand gesture recognition. Our method produced an F1-score of 82.19% for static gestures and 97.35% for dynamic gestures from a leave-one-out-cross-validation approach. We also explored a parallel-path neural network architecture for handling multimodal data more effectively. Moreover, we proposed a novel Spatial Projection Image-based technique for dynamic hand gesture recognition. We have collected data from 25 subjects for 24 static and 16 dynamic American sign language gestures for validating our system. We have developed a cost-effective dataglove using five flex sensors, an inertial measurement unit, and a powerful microcontroller for onboard processing and wireless connectivity. In this paper, we evaluate the effectiveness of a low-cost dataglove for classifying hand gestures in the light of deep learning. Although various modalities of hand gesture recognition have been explored in the last three decades, in recent years, due to the availability of hardware and deep learning algorithms, hand gesture recognition research has attained renewed momentum. Hand gesture recognition is one of the most widely explored areas under the human–computer interaction domain. ![]()
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