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But Kesha's act encompasses fantastic chants on the choruses; her stylized whine-talking through verses in a half San Fernando Valley, half mid-South delivery; rag-bag visuals (a skanky-looking dance crew, a rumpled American flag against a skinny bank of lights); and a super-low sense of humor that comes with mysterious confidence and self-possession.
A new visual vocabulary for the bag of visual word model exploiting the SIFT descriptor [20] on HSV colour domain has been proposed.
To use the bag of "visual words" model, a visual vocabulary is built during the learning phase: all the local features extracted from the training images are clustered.
In this step, the parameters of the HDLA model are learned from the training images, and it proceeds in three stages: (i) visual dictionary learning (ii) generating Bag of Visual Word (BoVW) representation of the training images and (iii) layer-by-layer training of the HDLA model in an unsupervised fashion.
Typically, filter banks or local invariant descriptors are employed to capture image cues and to build the visual vocabulary to be used in a bag of visual words model.
In Computer Vision these patterns are usually referred to as "visual words" [5, 10, 17, 40]: an image may hence be considered as a bag of "visual words".
Bag of visual words.
This paper has presented an approach for scene categorization based on bag of visual words representation.
In order to model training data precisely, each image is represented as a bag of visual words.
To overcome these difficulties we augment the basic bag of visual words representation combining it with a hierarchical partitioning of the image.
The weighted distance that we use is founded on similarity between two corresponding subregions when the bag of visual words have been computed on the same vocabulary.
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