Publication Details
Effectiveness of the Bag-of-Words approach on the object search problem in 3D domain
Beran Vítězslav, doc. Ing., Ph.D. (DCGM FIT BUT)
Smrž Pavel, doc. RNDr., Ph.D. (DCGM FIT BUT)
Bag-of-Words, object search, large-scale datasets
In this work, we investigate the application of the Bag-of-Words approach for object search task in 3D domain. Image retrieval
task solutions, operating on datasets of thousands and millions images, have proved the effectiveness of Bag-of-Words approach.
The availability of low cost RGB-D cameras is a rise of large datasets of 3D data similar to image corpuses (e.g. RoboEarth). The
results of such an investigation could be useful for many robot scenarios like place recognition from a large dataset of samples of
places acquired during the long-term observation of an environment. The first goal of our research presented in this paper is focused
on the sensitivity of the Bag-of-Words approach to various parameters (e.g. spacial sampling, surface description etc.) with respect
to precision, stability and robustness. The experiments are carry out on two widely-used datasets in object instance identification
task in 3D domain.
@INPROCEEDINGS{FITPUB11640,
author = "Vladimir Privalov and V\'{i}t\v{e}zslav Beran and Pavel Smr\v{z}",
title = "Effectiveness of the Bag-of-Words approach on the object search problem in 3D domain",
pages = "138--145",
booktitle = "Proceedings of SCCG 2017",
series = "Proceedings - SCCG 2017: 33rd Spring Conference on Computer Graphics",
year = 2017,
location = "New York City, NY, CZ",
publisher = "Association for Computing Machinery",
ISBN = "978-1-4503-5107-2",
doi = "10.1145/3154353.3154365",
language = "english",
url = "https://www.fit.vut.cz/research/publication/11640"
}