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A Saliency-driven Video Magnifier for People with Low Vision
Ali Selman Aydin1, Shirin Feiz1, Vikas Ashok2
1Department of Computer Science, Stony Brook University, Stony Brook, NY, USA.
Proceedings of the 17Th International Web for All Conference
|August 2, 2021
Summary
Navigating videos is difficult for people with low vision using screen magnifiers. The SViM video magnifier system uses visual saliency to improve video accessibility for low-vision users.
Area of Science:
- Human-Computer Interaction
- Assistive Technology
- Computer Vision
Background:
- Screen magnifiers are essential assistive technology for individuals with low vision.
- Video consumption presents unique navigation challenges for low-vision users, even with screen magnification.
- Existing screen magnifier software often fails to adequately address video navigation difficulties.
Purpose of the Study:
- To develop an accessible video magnifier system, SViM, for users with low vision.
- To enhance the video consumption experience for low-vision individuals.
- To present the design and interaction methods of the SViM system.
Main Methods:
- Developed the SViM video magnifier system with three distinct interfaces.
- Utilized visual saliency as a guided signal to quantify content interestingness.
- Processed saliency information (heatmaps) to identify and track regions of interest over time.
Main Results:
- SViM provides an easy-to-use interface for navigating video content.
- The system leverages visual saliency to guide users to important video regions.
- Distinct regions of interest are tracked and displayed dynamically.
Conclusions:
- The SViM system offers a novel approach to making video content more accessible for low-vision users.
- Visual saliency-guided navigation significantly improves the video experience for screen magnifier users.
- The developed interfaces provide intuitive interaction for enhanced video accessibility.
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