[IPOL announce] new article: Efficient Large-scale Image Search With a Vocabulary Tree

[announcements about the IPOL journal]

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.