Publication Details
Generating Face Image Dataset Using a 3D Head Model
Drahanský Martin, prof. Ing., Ph.D.
dataset, face recognition,
Many classification algorithms depend on a training dataset to be able to find
appropriate parameters. The training dataset can significantly affect the
resulting quality of the classifier hence it is necessary to use as good dataset
for given task as possible. Either there already is an available ready-to-use
dataset or a new one must be created. It is rather tedious and time consuming
process to create a new dataset from scratch because many algorithms usually
require a large amount of tagged data. For many specific tasks the only way is to
create a new dataset simply because there are no sets available. For the purposes
of training and testing face detection and recognition algorithms we created
a generator producing large number of images containing human head in various
poses and positions placed in a predefined scene. The synthetically generated
dataset may complement the dataset generated by the real data or may be used
separately.
@inproceedings{BUT176365,
author="Tomáš {Goldmann} and Martin {Drahanský}",
title="Generating Face Image Dataset Using a 3D Head Model",
booktitle="2021 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2)",
year="2021",
pages="1--4",
publisher="Institute of Electrical and Electronics Engineers",
address="Rajshahi",
doi="10.1109/IC4ME253898.2021.9768496",
isbn="978-1-6654-0638-3"
}