Digital real-time collaboration is arguably the most environmentally-friendly way to conduct business with distributed teams, suppliers, and customers in many parts of the globe. Even with employees moving back to offices and factories, digital collaboration can undoubtedly minimize latency, cost, and carbon footprint due to the travel of personnel and equipment. On the other hand, we have also seen the negative effects of video-conferencing fatigue, lack of social interactions, and other challenges of working from home.
Over the last few months, we worked on some very interesting research with our brilliant AI/ML intern Zain Raza who just completed his undergraduate degree at the MakeSchool. We aptly named the project headsets goodbye envisioning a future where devices to consume and interact with 3D content will become ubiquitous.
Our immediate objective was to investigate the performance and reliability of hand and face tracking using a webcam for industrial collaboration and training applications. The advantage of using a webcam is that no additional trackers or complex equipment are required to enhance the human-virtual interface. Hand tracking is already gaining traction with mixed reality headsets such as Hololens and Oculus Quest. But even without these immersive devices, AI/ML-based body tracking opens up a huge potential space for applications.
Read more about Zain’s work on Roberto the empathetic robot and journey with iQ3Connect in this article.