BiCE-HG: A Bi-Conditional Egocentric Hand Gesture Dataset for Intelligent Reality Systems

Robust egocentric hand-gesture recognition remains chal-lenging under the rapidly changing illumination typical of intelligent re-ality environments. Existing first-person gesture datasets rarely quantifylighting, limiting controlled analysis of illumination robustness. Unlikeprior egocentric datasets that describe lighting qualitatively (e.g., “in-door”, “bright”), BiCE-HG is the first to provide calibrated lux measure-ments at 80 spatial points, enabling reproducible illumination robustnessbenchmarking. BiCE-HG (Bi-Conditional Egocentric Hand Gestures)dataset addresses this gap as the first egocentric gesture dataset withmeasured bi-conditional lighting and spatial illuminance documentation.BiCE-HG contains 19 gestures performed by 23 participants across sixconditions combining sitting, standing, and walking with full and lowlighting setups. Walking trials capture realistic motion through a 4 mlighting corridor with transitions between bright and dim zones. Spatialilluminance is recorded every 25 cm using a calibrated meter, enablingprecise modelling of lighting gradients and reproducible experimentalconditions. Baseline evaluation reaches 81.24% validation accuracy (F1= 0.80) on the static (single-frame) release with a no-attention ST-GCN,the dynamic (temporal) release lifts accuracy to 88.57% with the identicalarchitecture, isolating a 7.3-percentage-point gain from temporal infor-mation alone, while adding tri-attention contributes a further marginalgain to 89.24% (F1 = 0.88). Lighting-robustness analysis shows stablespatial measurements, with a coefficient of variation below 5% for mostconditions across a 4.95× illuminance range (29-523 lux). BiCE-HG pro-vides quantified environmental metadata and realistic mobility lightinginteractions, supporting the development of illumination-robust egocen-tric gesture-recognition systems for AR/VR applications.The dataset ispublicly available at https://doi.org/10.15131/shef.data.32374137