Joint segmentation and classification of actions using a conditional random field
Dimitrios Kosmopoulos, Ilias G. Maglogiannis · 2015
In this paper, we present results of joint segmentation and classification of sequences in the framework of conditional random field (CRF) models. We use a recently proposed dual-functionality CRF model: on the first level, the proposed model conducts sequence segmentation, while, on the second level, the whole observed sequences are classified into one of the available learned classes. We evaluate the efficacy of our approach considering a real-world application, and we compare its performance to popular alternatives.