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Improving the usability of hierarchical representations for interactively labeling large image data sets

Julia Moehrmann, Stefan Bernstein, Thomas Schlegel, Gunter Werner, Gunther Heidemann
Intelligent Systems Group, University of Stuttgart, Universitatsstr. 38, 70569 Stuttgart, Germany
Human-Computer Interaction. Design and Development Approaches, Lecture Notes in Computer Science, Volume 6761/2011, 618-627, 2011

@article{moehrmann2011improving,

   title={Improving the usability of hierarchical representations for interactively labeling large image data sets},

   author={Moehrmann, J. and Bernstein, S. and Schlegel, T. and Werner, G. and Heidemann, G.},

   journal={Human-Computer Interaction. Design and Development Approaches},

   pages={618–627},

   year={2011},

   publisher={Springer}

}

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Image recognition systems require large image data sets for the training process. The annotation of such data sets through users requires a lot of time and effort, and thereby presents the bottleneck in the development of recognition systems. In order to simplify the creation of image recognition systems it is necessary to develop interaction concepts for optimizing the usability of labeling systems. Semi-automatic approaches are capable of solving the labeling task by clustering the image data unsupervised and presenting this ordered set to a user for manual labeling. A labeling interface based on self-organizing maps (SOM) was developed and its usability was investigated in an extensive user study with 24 participants. The evaluation showed that SOM-based visualizations are suitable for speeding up the labeling process and simplifying the task for users. Based on the results of the user study, further concepts were developed to improve the usability.
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