Keywords
Progress bars are prevalent in modern user interfaces. Typically, a linear function is employed such that the progress of the bar is directly proportional to how much work has been completed. However, numerous factors cause progress bars to proceed at non-linear rates. Additionally, humans perceive time in a non-linear way. This paper explores the impact of various progress bar behaviors on user perception of process duration. The results are used to suggest several design considerations that can make progress bars appear faster and ultimately improve users' computing experience.
Asynchronous collaborators often use freeform ink annotations to point to visually salient perceptual features of line charts such as peaks or humps, valleys, rising slopes and declining slopes. We present a set of techniques for interpreting such annotations to algorithmically identify the corresponding perceptual parts. Our approach is to first apply a parts-based segmentation algorithm that identifies the visually salient perceptual parts in the chart. Our system then analyzes the freeform annotations to infer the corresponding peaks, valleys or sloping segments. Once the system has identified the perceptual parts it can highlight them to draw further attention and reduce ambiguity of interpretation in asynchronous collaborative discussions.
