Dr Ravi Kant Kumar, an Assistant Professor at the Department of Computer Science and Engineering, and his research scholar, Ms Gayatri Dhara, have come up with a patent titled “A System and Method for Enhancement Of Visual Saliency Of Intended Face In Group Photography.” The patent, with Application Number 202441040020, employs pathbreaking technology to enhance security and healthcare applications, with real-time face recognition and remote diagnostics.
Abstract:
Visual saliency is a way of figuring out which parts of a scene draw our attention the most. When looking at a crowd or a group of faces, our eyes naturally focus more on certain faces than others. This happens because some faces have dominant features that stand out more. For faces that don’t naturally catch our attention, there is a need to make them more noticeable. This new method and system are designed to do just that. The system calculates scores based on various factors like skin tone, colour, contrast, position, and other visual details. These scores help identify which face needs enhancement, making it more prominent in a group of faces. The primary advantage of this invention is its potential to improve user experience in various applications, such as photo editing, social media, security systems, and more. By giving users, the control to select and enhance a specific face, it allows for a more personalised and targeted approach to face recognition and enhancement. This could be particularly beneficial in scenarios where the user wants to highlight a specific individual in a group photo or in a crowd. Overall, this invention represents a significant advancement in the field of face recognition and image enhancement, offering a novel and user-centric approach to visual saliency. It opens up new possibilities for user interaction and control in image editing and face recognition technology.
Practical and Social Implications
The practical implementation of this research lies in its ability to identify and enhance faces within a group or crowd that do not naturally draw attention. This innovative method and system address this issue by calculating saliency scores based on factors such as skin tone, colour, contrast, position, and other visual details. These scores are then used to identify faces that need enhancement to become more prominent in a group. The system’s ability to enhance specific faces has significant practical applications in several fields.
Photo Editing: Users can easily enhance specific individuals in group photos, ensuring that everyone stands out as desired. This is particularly useful for personal photos, event photography, and professional photo editing.
Social media: Enhanced face recognition and saliency can improve user experience by allowing users to highlight specific people in their posts, making photos more engaging and personalised.
Security Systems: In surveillance and security applications, the ability to enhance less prominent faces can improve the accuracy of face recognition systems, aiding in the identification of individuals in crowded or low-visibility conditions.
Collaborations:
SRM University-AP,
Dr Ravi Kant Kumar,
Mrs Gayathri Dhara.
Future Research Plans:
Future plans for this visual saliency-based face enhancement system include refining algorithms for greater accuracy and efficiency, and integrating with popular photo editing software and social media platforms for seamless user experience. The technology will be expanded into security and healthcare applications, enhancing real-time face recognition and remote diagnostics. Emphasis will be placed on reducing biases, ensuring privacy protection, and enabling user customisation. Collaborations with academic institutions will drive further research, while commercialisation efforts will focus on launching products globally.