Asadi-Aghbolaghi, M;
Clapes, A;
Bellantonio, M;
Escalante, HJ;
Ponce-Lopez, V;
Baro, X;
Guyon, I;
... Escalera, S; + view all
(2017)
A Survey on Deep Learning Based Approaches for Action and Gesture Recognition in Image Sequences.
In:
Proceedings of the 2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017).
(pp. pp. 476-483).
IEEE: Washington, D.C., USA.
Preview |
Text
Ponce Lopez_LARGE_bf_A_survey_on_deep_learning_based_approaches_for__action_and_gesture_recognition_in_image_sequencesthanks_An_extended_version_of_this_paper_wil.pdf - Accepted Version Download (302kB) | Preview |
Abstract
The interest in action and gesture recognition has grown considerably in the last years. In this paper, we present a survey on current deep learning methodologies for action and gesture recognition in image sequences. We introduce a taxonomy that summarizes important aspects of deep learning for approaching both tasks. We review the details of the proposed architectures, fusion strategies, main datasets, and competitions. We summarize and discuss the main works proposed so far with particular interest on how they treat the temporal dimension of data, discussing their main features and identify opportunities and challenges for future research.
| Type: | Proceedings paper |
|---|---|
| Title: | A Survey on Deep Learning Based Approaches for Action and Gesture Recognition in Image Sequences |
| Event: | 2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017) |
| Location: | Washington, DC |
| Dates: | 30 May 2017 - 03 June 2017 |
| ISBN-13: | 978-1-5090-4023-0 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/FG.2017.150 |
| Publisher version: | https://doi.org/10.1109/FG.2017.150 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Hidden Markov models, Three-dimensional displays, Machine learning, Gesture recognition, Solid modeling, Data models, Two dimensional displays |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10111955 |
Archive Staff Only
 |
View Item |
