Transductive Transfer Learning for Action Recognition in Tennis Games
Nazli Faraji Davar, Teo de Campos, Josef Kittler and Fei Yan
In: 3rd International Workshop on Video Event Categorization, Tagging and Retrieval for Real-World Applications (VECTaR2011), 13 Nov 2011, Barcelona, Spain.
This paper investigates the application of transductive
transfer learning methods for action classification.
The application scenario is that of off-line video annotation for
We show that if a classification system can analyze the
unlabeled test data in order to adapt its models, a
significant performance improvement can be achieved. We
applied it for action classification in tennis games for train
and test videos of different nature. Actions are described
using HOG3D features and for transfer we used a method
based on feature re-weighting and a novel method based on
feature translation and scaling.