Where You Look Matters in Group Photos: A Demo of GARGI iOS App - Kulkarni, Omkar N.; Lloyd-Jones, Thomas; Tran, My; Vincent, Gregory; Singh, Vivek K.; Atrey, Pradeep K. (Proceedings (IEEE Conference on Multimedia Information Processing and Retrieval. Online), 2024)
Capturing group photos at professional or social events is a prevalent practice nowadays. In such photos, the direction in which each individual looks plays a crucial role in determining the aesthetic appeal of the image. Generally, unless instructed otherwise, it's desirable for all individuals in the photo to look in the same direction, commonly towards the camera, a concept known as gaze uniformity. However, when multiple photographers are involved in taking a group photo, there's a higher likelihood of nonuniform gazes occurring with multiple subjects. The paper introduces 'GARGI', an iOS app for evaluating gaze uniformity in group photos, categorizing them as GOOD, BAD, or OK based on their aesthetic value. Utilizing Apple's Vision framework and SwiftUI, GARGI em-ploys face, eye, and landmark detection algorithms to detect and analyze gaze direction. It supports camera and gallery inputs, with custom algorithms to assess gaze uniformity in live photos. Equipped with functionality to use the high-quality on-device camera, intuitive user interface, and customization options, GARGI ensures aesthetically better group photo outcomes.