Muna Almushyti
Recognising Human-Object Interactions Using Attention-based LSTMs
Almushyti, Muna; Li, Frederick W.B.
Authors
Dr Frederick Li frederick.li@durham.ac.uk
Associate Professor
Contributors
Franck P. Vidal
Editor
Gary K. L. Tam
Editor
Jonathan C. Roberts
Editor
Abstract
Recognising Human-object interactions (HOIs) in videos is a challenge task especially when a human can interact with multiple objects. This paper attempts to solve the problem of HOIs by proposing a hierarchical framework that analyzes human-object interactions from a video sequence. The framework consists of LSTMs that firstly capture both human motion and temporal object information independently, followed by fusing these information through a bilinear layer to aggregate human-object features, which are then fed to a global deep LSTM to learn high-level information of HOIs. The proposed approach applies an attention mechanism to LSTMs in order to focus on important parts of human and object temporal information.
Citation
Almushyti, M., & Li, F. W. (2019). Recognising Human-Object Interactions Using Attention-based LSTMs. In F. P. Vidal, G. K. . L. Tam, & J. C. Roberts (Eds.), Computer Graphics and Visual Computing (CGVC) (135-139). https://doi.org/10.2312/cgvc.20191269
Conference Name | Computer Graphics and Visual Computing (CGVC) |
---|---|
Conference Location | Bangor University, United Kingdom |
Acceptance Date | Jul 22, 2019 |
Online Publication Date | Sep 12, 2019 |
Publication Date | Sep 12, 2019 |
Deposit Date | Oct 30, 2019 |
Publicly Available Date | Mar 28, 2024 |
Pages | 135-139 |
Book Title | Computer Graphics and Visual Computing (CGVC). |
DOI | https://doi.org/10.2312/cgvc.20191269 |
Public URL | https://durham-repository.worktribe.com/output/1141631 |
Related Public URLs | https://diglib.eg.org/handle/10.2312/cgvc20191269 |
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