Open AccessA Comprehensive Video Dataset for Multi-Modal Recognition Systems
Author(s) -
Anand Handa,
Rashi Agarwal,
Narendra Kohli
Publication year - 2019
Publication title -
data science journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.358
H-Index - 21
ISSN - 1683-1470
DOI - 10.5334/dsj-2019-055
Subject(s) - computer science , facial recognition system , artificial intelligence , modal , pattern recognition (psychology) , speech recognition , face (sociological concept) , artificial neural network , machine learning , polymer chemistry , chemistry , social science , sociology
This paper presents a comprehensive, highly defined and fully labelled video dataset. This dataset consists of videos related to 67 different subjects. The videos contain similar text and the text contains digits from 1 to 20 recited by 67 different subjects using the same experimental setup. This dataset can be used as a unique resource for researchers and analysts for training deep neural networks to build highly efficient and accurate recognition models in various domains of computer vision such as face recognition model, expression recognition model, speech recognition model, text recognition, etc. In this paper, we also train models related to face recognition and speech recognition on our dataset and also compare the results with the publically available datasets to show the effectiveness of our dataset. The experimental results show that our comprehensive dataset is more accurate than other dataset on which the models are tested.
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