Abstract. Oza’s Online Boosting algorithm provides a version of AdaBoost which can be trained in an online way for stationary problems. One perspective is that this enables the p...
Adam Pocock, Paraskevas Yiapanis, Jeremy Singer, M...
This paper describes a new approach to combine multiple modalities and applies it to the problem of affect recognition. The problem is posed as a combination of classifiers in a p...
We present a new data set encoding localized semantics for 1014 images and a methodology for using this kind of data for recognition evaluation. This methodology establishes protoc...
Action recognition methods suffer from many drawbacks in practice, which include (1)the inability to cope with incremental recognition problems; (2)the requirement of an intensive...
In this paper, we propose a general framework for fusing bottom-up segmentation with top-down object behavior classification over an image sequence. This approach is beneficial fo...