Name
Abstract | ||
|---|---|---|
•An effective multi-stage adaptive regression framework is proposed to address the partial activity observation problem in online activity recognition.•Multiple score functions are collaboratively learned via an adaptive label strategy to reinforce the capacity of distinguishing similar partial activities and the robustness to arbitrary activity fragments.•A challenging interaction database, Online Human Interaction (OHI), is collected in a realistic scenario to further evaluate the online activity recognition. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.patcog.2019.107053 | Pattern Recognition |
Keywords | Field | DocType |
Online activity recognition,Interaction recognition,Partial observation,Adaptive regression | Activity recognition,Regression,Pattern recognition,Robustness (computer science),Human interaction,Artificial intelligence,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
98 | 1 | 0031-3203 |
Citations | PageRank | References |
1 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bangli Liu | 1 | 11 | 2.85 |
| Haibin Cai | 2 | 38 | 6.46 |
| Zhaojie Ju | 3 | 284 | 48.23 |
| Honghai Liu | 4 | 1974 | 178.69 |