Recognising Human-Object Interactions Using Attention-based LSTMs

No Thumbnail Available
Date
2019
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
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.
Description

        
@inproceedings{
10.2312:cgvc.20191269
, booktitle = {
Computer Graphics and Visual Computing (CGVC)
}, editor = {
Vidal, Franck P. and Tam, Gary K. L. and Roberts, Jonathan C.
}, title = {{
Recognising Human-Object Interactions Using Attention-based LSTMs
}}, author = {
Almushyti, Muna
and
Li, Frederick W. B.
}, year = {
2019
}, publisher = {
The Eurographics Association
}, ISBN = {
978-3-03868-096-3
}, DOI = {
10.2312/cgvc.20191269
} }
Citation