Result Details
Effectiveness of the Bag-of-Words approach on the object search problem in 3D domain
Beran Vítězslav, doc. Ing., Ph.D., DCGM (FIT)
Smrž Pavel, doc. RNDr., Ph.D., DCGM (FIT)
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.
Bag-of-Words, object search, large-scale datasets
@inproceedings{BUT146364,
author="Vladimir {Privalov} and Vítězslav {Beran} and Pavel {Smrž}",
title="Effectiveness of the Bag-of-Words approach on the object search problem in 3D domain",
booktitle="Proceedings of SCCG 2017",
year="2017",
series="Proceedings - SCCG 2017: 33rd Spring Conference on Computer Graphics",
pages="138--145",
publisher="Association for Computing Machinery",
address="New York City, NY",
doi="10.1145/3154353.3154365",
isbn="978-1-4503-5107-2",
url="https://www.fit.vut.cz/research/publication/11640/"
}