Video based hand gesture recognition dataset using thermal camera

Abstract

The dataset includes thermal videos of various hand gestures captured by the FLIR Lepton Thermal Camera. A large dataset is created to accurately classify hand gestures captured from eleven different individuals. The dataset consists of 9 classes corresponding to various hand gestures from different people collected at different time instances with complex backgrounds. This data includes flat/leftward, flat/rightward, flat/contract, spread/ leftward, spread/rightward, spread/contract, V-shape/leftward, V-shape/rightward, and V-shape/contract. There are 110 videos in the dataset for each gesture and a total of 990 videos corresponding to 9 gestures. Each video has data of three different (15/10/5) frame lengths.

Keywords

• Video hand gestures
• Thermal image
• Machine learning
• Neural network
• Jetson nano