Exploring latent class information for image retrieval using the bag-of-feature model
Recently, the Bag-of-Feature (BoF) model has shown promising performance in object and generic image retrieval. The similarity between two images is typically measured by the distance between the two histograms. Due to the imperfection of local descriptor and quantization error, visually similar image patches can be wrongly quantized into different visual words, making this distance-based measure less accurate. To address this issue, this paper explores the information of latent class, which is...[Show more]
|Collections||ANU Research Publications|
|Source:||Visual Memes in Social Media|
|01_Liu_Exploring_latent_class_2011.pdf||478.87 kB||Adobe PDF||Request a copy|
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