[IPOL discuss] [IPOL announce] new article: Efficient Large-scale Image Search With a Vocabulary Tree
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A new article is available in IPOL: http://www.ipol.im/pub/art/2018/199/
Esteban Uriza, Francisco Gómez Fernández, and Martín Rais,
Efficient Large-scale Image Search With a Vocabulary Tree,
Image Processing On Line, 8 (2018), pp. 71–98.
https://doi.org/10.5201/ipol.2018.199
Abstract
The task of searching and recognizing objects in images has become an
important research topic in the area of image processing and computer
vision. Looking for similar images in large data sets given an input
query and responding as fast as possible is a very challenging task. In
this work the Bag of Features approach is studied, and an implementation
of the visual vocabulary tree method from Nistér and Stewénius is
presented. Images are described using local invariant descriptor
techniques and then indexed in a database using an inverted index for
further queries. The descriptors are quantized according to a visual
vocabulary, creating sparse vectors, which allows to compute very
efficiently, for each query, a ranking of similarity for indexed images.
The performance of the method is analyzed varying different factors,
such as the parameters for the vocabulary tree construction, different
techniques of local descriptors extraction and dimensionality reduction
with PCA. It can be observed that the retrieval performance increases
with a richer vocabulary and decays very slowly as the size of the
dataset grows.
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