Name
Abstract | ||
|---|---|---|
This paper presents an active learning approach for recognizing human actions in videos based on multiple kernel combined method. We design the classifier based on Multiple Kernel Learning (MKL) through Gaussian Processes (GP) regression. This classifier is then trained in an active learning approach. In each iteration, one optimal sample is selected to be interactively annotated and incorporated into training set. The selection of the sample is based on the heuristic feedback of the GP classifier. To our knowledge, GP regression MKL based active learning methods have not been applied to address the human action recognition yet. We test this approach on standard benchmarks. This approach outperforms the state-of-the-art techniques in accuracy while requires significantly less training samples. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ICIP.2011.6116363 | 2011 18TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) |
Keywords | Field | DocType |
Human action recognition, Gaussian Processes, Multiple Kernel Learning, Active Learning | Active learning (machine learning),Computer science,Artificial intelligence,Gaussian process,Contextual image classification,Classifier (linguistics),Kernel (linear algebra),Computer vision,Heuristic,Active learning,Pattern recognition,Multiple kernel learning,Machine learning | Conference |
ISSN | Citations | PageRank |
1522-4880 | 7 | 0.45 |
References | Authors | |
4 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Liu, Xianghang | 1 | 13 | 1.27 |
| Jian Zhang | 2 | 1305 | 100.05 |