PROJECT TITLE :

Gesture Recognition Using Wearable Vision Sensors to Enhance Visitors’ Museum Experiences

ABSTRACT:

We tend to introduce a completely unique approach to cultural heritage experience: by means that of ego-vision embedded devices we tend to develop a system, which offers a more natural and entertaining way of accessing museum information. Our methodology relies on distributed self-gesture and design recognition, and will not need fastened cameras nor radio-frequency identifications sensors. We tend to propose the utilization of dense trajectories sampled round the hand region to perform self-gesture recognition, understanding the approach a user naturally interacts with an design, and demonstrate that our approach can profit from distributed coaching. We have a tendency to take a look at our algorithms on publicly available knowledge sets and we extend our experiments to each virtual and real museum eventualities, where our technique shows robustness when challenged with real-world knowledge. Furthermore, we tend to run an extensive performance analysis on our ARM-based wearable device.