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Improving Large-Scale Image Retrieval using Geometric Weighting

Dmitry SezganovMoshe Porat

Dmitry Sezganov and Moshe Porat are with the Department of Electrical Engineering

摘要:The Bag-Of-Features (BOF) approaches are becoming central in large-scale image retrieval. The geometrical information is usually involved only in the post-processing spatial verification step usually implemented with the RANdom SAmple Consensus (RANSAC) algorithm. To enable visual search in real-time, RANSAC can be applied only to a relatively small number of top candidates due to its computational requirements. In this work, we propose an alternative method to perform accurate spatial verification with a significantly lower computational cost. Experimental results show that the proposed method outperforms the baseline BOF, and achieves similar performance as RANSAC based spatial verification, despite the major difference in complexity.
会议名称:

International Conference on Oil,Gas and PetrochemicalIssues(ICOGPI’2012)、International Conference on Environment,Agriculture and Food Sciences(ICEAFS’2012)、International Conference on Management,Humanity and Economics(ICMHE’2012)、International Conference on Automation,Mechatronics and Robotics(ICAMR’2012)、International Conference on Machine Learning and Computer Science(IMLCS’2012)、International Conference on Power and VLSI Engineering(ICPVE’2012)

会议时间:

2012-08-11;2012-08-11;2012-08-11;2012-08-11;2012-08-11;2012-08-11

会议地点:

Phuket,Thailand;Phuket,Thailand;Phuket,Thailand;Phuket,Thailand;Phuket,Thailand;Phuket,Thailand

  • 专辑:

    信息科技

  • 专题:

    计算机软件及计算机应用

  • 分类号:

    TP391.41

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