Data-driven adaptive history for image editing

Digital image editing is usually an iterative process; users repetitively perform short sequences of operations, undo them and then redo them using history navigation tools. In our collected data, these undo, redo and navigation constitute about 9 percent of the total commands and consume a significant amount of user time. Unfortunately, such activities also tend to be tedious and frustrating, especially for complex projects. We address this critical issue by adaptive history, an UI mechanism that groups relevant operations together to reduce user workloads. Such grouping can happen at various history granularities. We present two that have been found to be most useful: On a detailed level, we group repeating commands patterns together to facilitates the smart undo functions; On a coarser level, we segments commands history into chunks with similar semantic meaning for easier semantic navigation. The main advantages of our approach are that it is easy for users to learn and easy for ...

• Type: Journal
• Year: 2016
• Where: SI3D
• Authors: Hsiang-Ting Chen, Li-Yi Wei, Björn Hartmann, Maneesh Agrawala
• Keywords: Computer Graphics, SI3D 2016