HpEIS: Learning Hand Pose Embeddings for Multimedia Interactive Systems

• Published in: 2024 IEEE International Conference on Multimedia and Expo (ICME) pp. 1 - 6
• Main Authors: Xu, Songpei, Ge, Xuri, Kaul, Chaitanya, Murray-Smith, Roderick
• Format: Conference Proceeding
• Language: English
• Published: IEEE 15-07-2024
• Subjects: Cameras; Hand-pose embedding space; Hand-pose interactive system; Interactive systems; Multimedia systems; Smoothing methods; Stability analysis; Turning; User guidance window; Variational Autoencoders; Visualization
• ISSN: 1945-788X
• DOI: 10.1109/ICME57554.2024.10688341

We present a novel Hand-pose Embedding Interactive System (HpEIS) as a virtual sensor, which maps users' flexible hand poses to a two-dimensional visual space using a Variational Autoencoder (VAE) trained on a variety of hand poses. HpEIS enables visually interpretable and guidable support for user explorations in multimedia collections, using only a camera as an external hand pose acquisition device. We identify general usability issues associated with system stability and smoothing requirements through pilot experiments with expert and inexperienced users. We then design stability and smoothing improvements, including hand-pose data augmentation, an anti-jitter regularisation term added to loss function, stabilising post-processing for movement turning points and smoothing post-processing based on One Euro Filters. In target selection experiments (n=12), we evaluate HpEIS by measures of task completion time and the final distance to target points, with and without the gesture guidance window condition. Experimental responses indicate that HpEIS provides users with a learnable, flexible, stable and smooth mid-air hand movement interaction experience.