  Viewing omnidirectional images (ODIs) in virtual reality (VR) represents a
novel form of media that provides immersive experiences for users to navigate
and interact with digital content. Nonetheless, this sense of immersion can be
greatly compromised by a blur effect that masks details and hampers the user's
ability to engage with objects of interest. In this paper, we present a novel
system, called OmniVR, designed to enhance visual clarity during VR navigation.
Our system enables users to effortlessly locate and zoom in on the objects of
interest in VR. It captures user commands for navigation and zoom, converting
these inputs into parameters for the Mobius transformation matrix. Leveraging
these parameters, the ODI is refined using a learning-based algorithm. The
resultant ODI is presented within the VR media, effectively reducing blur and
increasing user engagement. To verify the effectiveness of our system, we first
evaluate our algorithm with state-of-the-art methods on public datasets, which
achieves the best performance. Furthermore, we undertake a comprehensive user
study to evaluate viewer experiences across diverse scenarios and to gather
their qualitative feedback from multiple perspectives. The outcomes reveal that
our system enhances user engagement by improving the viewers' recognition,
reducing discomfort, and improving the overall immersive experience. Our system
makes the navigation and zoom more user-friendly.
