Visual Typo Correction by Collocative Optimization: A Case Study on Merchandize Images

@article{Wei2014VisualTC,
  title={Visual Typo Correction by Collocative Optimization: A Case Study on Merchandize Images},
  author={Xiao-Yong Wei and Zhen-Qun Yang and Chong-Wah Ngo and Wei Zhang},
  journal={IEEE Transactions on Image Processing},
  year={2014},
  volume={23},
  pages={527-540}
}
Near-duplicate retrieval (NDR) in merchandize images is of great importance to a lot of online applications on e-Commerce websites. In those applications where the requirement of response time is critical, however, the conventional techniques developed for a general purpose NDR are limited, because expensive post-processing like spatial verification or hashing is usually employed to compromise the quantization errors among the visual words used for the images. In this paper, we argue that most… CONTINUE READING

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Key Quantitative Results

  • The experimental results show that the proposed method can improve the efficiency of NDR by reducing vocabulary size by 1000% times, and under the scenario of merchandize image NDR, the expensive local interest point feature used in conventional approaches can be replaced by color-moment feature, which reduces the time cost by 9202% while maintaining comparable performance to the state-of-the-art methods.

Citations

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  • 2017
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