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Sports Video Captioning via Attentive Motion Representation and Group Relationship Modeling.
- Source :
-
IEEE Transactions on Circuits & Systems for Video Technology . Aug2020, Vol. 30 Issue 8, p2617-2633. 17p. - Publication Year :
- 2020
-
Abstract
- Sports video captioning refers to the task of automatically generating a textual description for sports events (football, basketball, or volleyball games). Although a great deal of previous work has shown promising performance in producing a coarse and a general description of a video but lack of professional sports knowledge, it is still quite challenging to caption a sports video with multiple fine-grained player’s actions and complex group relationship between players. In this paper, we present a novel hierarchical recurrent neural network-based framework with an attention mechanism for sports video captioning, in which a motion representation module is proposed to capture individual pose attribute and dynamical trajectory cluster information with extra professional sports knowledge, and a group relationship module is employed to design a scene graph for modeling players’ interaction by a gated graph convolutional network. Moreover, we introduce a new dataset called sports video captioning dataset-volleyball for evaluation. The proposed model is evaluated on three widely adopted public datasets and our collected new dataset, on which the effectiveness of our method is well demonstrated. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10518215
- Volume :
- 30
- Issue :
- 8
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Circuits & Systems for Video Technology
- Publication Type :
- Academic Journal
- Accession number :
- 145130455
- Full Text :
- https://doi.org/10.1109/TCSVT.2019.2921655