Tool for image annotation based on gaze
| Autor: | Mohan Raghavan, Satya Patel, Raghu Sesha Iyengar, Kousik Sarathy Sridharan, Kapardi Mallampalli |
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| Rok vydání: | 2020 |
| Předmět: |
Information retrieval
Computer science Supervised learning Object (computer science) Gaze 03 medical and health sciences Annotation 0302 clinical medicine Automatic image annotation Minimum bounding box 030220 oncology & carcinogenesis Eye tracking 030211 gastroenterology & hepatology Protocol (object-oriented programming) |
| Zdroj: | SPCOM |
| DOI: | 10.1109/spcom50965.2020.9179496 |
| Popis: | Supervised learning on image data demands availability of large amounts of annotated image data. Annotation is predominantly a tool assisted manual activity and increasingly accounts for a large share of budget in machine learning systems development. This is due to the time involved and the need for large manpower to annotate large databases. Instead of the predominantly bounding box drawing using mouse cursor, we propose a more natural human computer interface - the human gaze. We hereby propose a technique of image annotation by using a novel protocol for acquiring gaze data to create a polygon around the object rather than bounding boxes. In this study the method is outlined and the results are compared with manually created annotations. The technique can be used to annotate existing image databases or create new annotated databases by simultaneous image acquisition and annotation. |
| Databáze: | OpenAIRE |
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