Abstract
Despite the recent advances of image object proposals (IOPs) and video object proposals (VOPs), it still remains a challenge to apply them to online video object/action detection. To address this problem, we propose a novel form of image object proposals, Temporally Enhanced Image Object Proposals (TE-IOPs), for online video object/action detection. The proposed TE-IOPs augment the existing IOPs at every frame by their temporal dynamics in the past few frames. We develop a dynamic programming scheme to efficiently search for such TE-IOPs in an online manner. Compared with existing VOPs that cannot run online, our TE-IOPs can be used for online detection. Compared with IOPs, our TE-IOPs bring rich temporal dynamics with minor computational cost. Experiments on benchmark datasets validate the superior performance of the proposed TE-IOPs over existing IOPs and VOPs, in terms of both the proposal re-ranking and the application of online action detection.
| Original language | English |
|---|---|
| Pages (from-to) | 245-256 |
| Number of pages | 12 |
| Journal | Journal of Visual Communication and Image Representation |
| Volume | 53 |
| DOIs | |
| State | Published - May 2018 |
Keywords
- Detection
- Online
- Proposal
- Temporal
- Video
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