Detail výsledku
Generating Face Image Dataset Using a 3D Head Model
Drahanský Martin, prof. Ing., Ph.D., UITS (FIT)
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.
dataset, face recognition,
@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"
}