Crowdsourcing image segmentation using SVG

Edward Kim, Xiaolei Huang

Research output: Contribution to conferencePaperpeer-review


With the ubiquity of digital cameras, camera phones, web cams, etc., the amount of digital image data is exploding. However, to utilize this data for image annotation and recognition algorithms, a large amount of labeled data for training is required. But obtaining training data on large datasets of images is a very tedious and expensive process. To address this issue, we develop an online image annotation system that can collect annotation data from crowds. Additionally, we incorporate semi-automatic segmentation algorithms that are able to assist the user in creating accurate object boundaries. We show that our system is an effective and useful tool in collecting image annotation data.

Original languageEnglish (US)
StatePublished - 2011
Event9th International Conference on Scalable Vector Graphics, SVG Open 2011 - Cambridge, MA, United States
Duration: Oct 17 2011Oct 20 2011


Conference9th International Conference on Scalable Vector Graphics, SVG Open 2011
Country/TerritoryUnited States
CityCambridge, MA

All Science Journal Classification (ASJC) codes

  • Geometry and Topology


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