SnapShare: AI Trained Mobile App to Share Snaps Automatically

• Main Authors: Waqas, Ahmad, Gilal, Abdul Rehman, Khan, Adil, Omar, Mazni, Chohan, Murk, Gilal, Ruqaya
• Format: Article
• Language: English
• Published: Science and Engineering Research Support Society 2020
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://repo.uum.edu.my/28275/1/IJAST%2029%208%202020%20393%20399.pdf; http://repo.uum.edu.my/28275/; http://sersc.org/journals/index.php/IJAST/article/view/17028
• Institution: Universiti Utara Malaysia

These days people take more than 1 million group or selfie photos per day. This goes very hectic for a mobile owner to identify photos of each individual and send them their photos separately. Sharing photos create extra burden for mobile owners. There are fewer applications available (i.e., 23Snaps, Cluster, Path, letmesee) to share photos with small circle of friends. Unfortunately, these developed apps require user’s interaction to identify individuals in the photo. This study proposes a SnapShare mobile application that uses Face Recognition Algorithms to classify individuals in the photos and automatically shares photos with recognized individuals. SnapShare basically uses Deep learning (DL) and Machine Learning (ML) techniques for Face Recognition from the captured images. Based on the results, the developed system achieves the standard performance accuracy (i.e., >90%). The aim of the SnapShare is to create comfort for mobile owners and people visible in-group photo to share and access photo automatically. Furthermore, SnapShare also facilitates user to back up their photo gallery on server storage.