@inproceedings{93d48c2f8d49452e8f21fce6430027ad,
title = "A large scale RGB-D dataset for action recognition",
abstract = "Human activity understanding from RGB-D data has attracted increasing attention since the first work reported in 2010. Over this period, many benchmark datasets have been created to facilitate the development and evaluation of new algorithms. However, the existing datasets are mostly captured in laboratory environment with small number of actions and small variations, which impede the development of higher level algorithms for real world applications. Thus, this paper proposes a large scale dataset along with a set of evaluation protocols. The large dataset is created by combining several existing publicly available datasets and can be expanded easily by adding more datasets. The large dataset is suitable for testing algorithms from different perspectives using the proposed evaluation protocols. Four state-of-the-art algorithms are evaluated on the large combined dataset and the results have verified the limitations of current algorithms and the effectiveness of the large dataset.",
keywords = "Action recognition, Evaluation protocol, Large scale RGB-D dataset",
author = "Jing Zhang and Wanqing Li and Pichao Wang and Philip Ogunbona and Song Liu and Chang Tang",
note = "Publisher Copyright: {\textcopyright} 2018, Springer International Publishing AG, part of Springer Nature.; 2nd International Workshop on Understanding Human Activities Through 3D Sensors, UHA3DS 2016 Held in Conjunction with the 23rd International Conference on Pattern Recognition, ICPR 2016 ; Conference date: 04-12-2016 Through 04-12-2016",
year = "2018",
doi = "10.1007/978-3-319-91863-1\_8",
language = "英语",
isbn = "9783319918624",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "101--114",
editor = "Pietro Pala and Francisco Florez-Revuelta and Hazem Wannous and Mohamed Daoudi",
booktitle = "Understanding Human Activities Through 3D Sensors - Second International Workshop, UHA3DS 2016, Held in Conjunction with the 23rd International Conference on Pattern Recognition, ICPR 2016, Revised Selected Papers",
address = "德国",
}