Hand Gesture Recognition in Low-Light Environments Using Deep Learning
Authors:-Sujal Suraywanshi, Ganesh Waje, Diya Jain, Prajyot Jagtap/strong>
Abstract- Hand gesture recognition has attracted enormous interest because of its extensive application in human-computer interaction, sign language understanding, and augmented reality. Recognizing hand gestures in low light conditions is a difficult task to achieve because the visibility is low, there are noises, and feature details get lost. Here, we propose a detailed survey of recent techniques in hand gesture recognition for low-light conditions by employing deep learning methods. We present the difficulties involved with low-light environments, such as illumination changes and background noise. In addition, we discuss different deep learning-based methods for hand detection and gesture classification and present their effectiveness in improving recognition accuracy under difficult lighting conditions. We conclude by offering a comparative assessment of these methods based on primary performance indicators like accuracy, processing time, and resistance to low-light conditions.
