Research Article
A Semi-Automated Usability Evaluation Framework for Interactive Image Segmentation Systems
Table 1
Overview of seed point location selection methods for a set of influential publications in the field of interactive image segmentation. Additional unordered seed information can be retrieved in arbitrary order by (a) manually drawn seeds or (b) randomly generated seeds. Seeds can be inferred rule-based from the ground truth segmentation by (c) sampling the binary mask image, (d) from provided bounding box mask images, (e) random sampling from tri-maps generated by erosion and dilation, or (f) by a robot user, i.e. user simulation. A tri-map specifies background, foreground, and mixed areas. Seeds can also be provided by real users via the (g) final seed masks after all interactions on one input image or (h) the ordered iterative scribbles. (i) Questionnaire data from Goals, Operators, Methods, and Selection rules (GO) as well as National Aeronautics and Space Administration Task Load Index (TL) may be retrieved by interviewing users after the segmentation process. Check marks indicate the usage of seeds in the publications listed. Publications with check marks in brackets display these seeds but do not utilize them for evaluation.
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