Towards Complete Icon Labeling in Mobile Applications
AuthorsJieshan Chen, Amanda Swearngin, Jason Wu, Titus Barik, Jeffrey Nichols and Xiaoyi Zhang
Accurately recognizing icon types in mobile applications is integral to many tasks, including accessibility improvement, UI design search, and conversational agents. Existing research focuses on recognizing the most frequent icon types, but these technologies fail when encountering an unrecognized low-frequency icon. In this paper, we work towards complete coverage of icons in the wild. After annotating a large-scale icon dataset (327,879 icons) from iPhone apps, we found a highly uneven distribution: 98 common icon types covered 92.8% of icons, while 7.2% of icons were covered by more than 331 long-tail icon types. In order to label icons with widely varying occurrences in apps, our system uses an image classification model to recognize common icon types with an average of 3,000 examples each (96.3% accuracy) and applies a few-shot learning model to classify long-tail icon types with an average of 67 examples each (78.6% accuracy). Our system also detects contextual information that helps characterize icon semantics, including nearby text (95.3% accuracy) and modifier symbols added to the icon (87.4% accuracy). In a validation study with workers (n=23), we verified the usefulness of our generated icon labels. The icon types supported by our work cover 99.5% of collected icons, improving on the previously highest 78% coverage in icon classification work.
At Apple we use machine learning to teach our products to understand the world more as humans do. Of course, understanding the world better means building great assistive experiences. Machine learning can help our products be intelligent and intuitive enough to improve the day-to-day experiences of people living with disabilities. We can build machine-learned features that support a wide range of users including those who are blind or have low vision, those who are deaf or are hard of hearing, those with physical motor limitations, and also support those with cognitive disabilities.