Randomly Projected KD-Trees with Distance Metric Learning for Image Retrieval
Efficient nearest neighbor (NN) search techniques for highdimensional data are crucial to content-based image retrieval (CBIR). Traditional data structures (e.g., kd-tree) usually are only efficient for low dimensional data, but often perform no better than a simple exhaustive linear search when the...
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Main Authors: | WU, Pengcheng, HOI, Steven, NGUYEN, Duc Dung, HE, Ying |
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Format: | text |
Language: | English |
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Institutional Knowledge at Singapore Management University
2011
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Online Access: | https://ink.library.smu.edu.sg/sis_research/2356 https://ink.library.smu.edu.sg/context/sis_research/article/3356/viewcontent/Randomly_Projected_KD_Trees_with_Distance_Metric_Learning_for_Image_Retrieval.pdf |
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Institution: | Singapore Management University |
Language: | English |
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