Abstract
To provide comprehensive evaluation of interactive image segmentation algorithms, we propose an automatic scribble simulation approach. We first analyze the variety of scribbles labelled by different users and its influence on segmentation result. Then, we describe the consistency and inconsistency of scribbles with normal distribution on superpixel level and superpixel group level, and analyze the effect of connection in scribble for interactive segmentation evaluation. Based on the above analysis, we simulate scribbles on foreground and background respectively by randomly selecting superpixel groups and superpixels with the previously determined coverage values. The experimental results show that the scribbles simulated by the proposed approach can obtain similar evaluation results to manually labelled scribbles and avoid serious deviation in precision and recall evaluation.
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Acknowledgments
This work is supported by the National Science Foundation of China (61321491, 61202320), Research Project of Excellent State Key Laboratory (61223003), National Undergraduate Innovation Project (G1410284075) and Collaborative Innovation Center of Novel Software Technology and Industrialization.
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Jiang, B., Ren, T., Bei, J. (2016). Automatic Scribble Simulation for Interactive Image Segmentation Evaluation. In: Tian, Q., Sebe, N., Qi, GJ., Huet, B., Hong, R., Liu, X. (eds) MultiMedia Modeling. MMM 2016. Lecture Notes in Computer Science(), vol 9516. Springer, Cham. https://doi.org/10.1007/978-3-319-27671-7_50
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DOI: https://doi.org/10.1007/978-3-319-27671-7_50
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