Name
Title | ||
|---|---|---|
A Space-Time Graph Optimization Approach Based on Maximum Cliques for Action Detection |
Abstract | ||
|---|---|---|
We present an efficient action detection method that takes a space-time graph optimization approach for realworld videos. Given a space-time graph representing the entire action video, our method identifies a maximum-weight connected subgraph indicating an action region by applying an optimization approach based on clique information. We define an energy function based on maximum weight cliques for subregions of the graph, and formulate it using an optimization problem that can be represented as a linear system. Our energy function includes the maximum and connectivity properties for finding the maximum-weight connected subgraph, and its optimization solution indicates the probability of belonging to the maximum subgraph for each node. Our graph optimization method efficiently solves the detection problem by applying the cliquebased approach and simple linear system solver. We demonstrate that our detection method results in more accurate localization compared to conventional methods through our experimental results with real-world datasets, such as Hollywood and MSR action datasets. We also show that our method outperforms the state-of-the-art methods of action detection. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TCSVT.2015.2424054 | Circuits and Systems for Video Technology, IEEE Transactions |
Keywords | DocType | Volume |
action detection,maximum weight clique,maximum weight connected subgraph,optimization,space-time graph,sparse representation | Journal | PP |
Issue | ISSN | Citations |
99 | 1051-8215 | 5 |
PageRank | References | Authors |
0.41 | 35 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sunyoung Cho | 1 | 8 | 1.47 |
| Hyeran Byun | 2 | 505 | 65.97 |