Video based hand gesture recognition dataset using thermal camera
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Updated: Jun 29, 2025

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision
Published on: March 28, 2025
Simen Birkeland1, Lin Julie Fjeldvik1, Nadia Noori1
1ACPS Group, Department of Information and Communication Technology, University of Agder, 4879, Norway.
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 () frame lengths.

