3 citations · 3 across the 4 of their papers we have counts for
6 papers · 1 filter
Using phase instead of optical flow for action recognition
Omar Hommos, Silvia L. Pintea, Pascal S. M. Mettes +1
Currently, the most common motion representation for action recognition is optical flow. Optical flow is based on particle tracking which adheres to a Lagrangian perspective on dyn…
Hand-tremor frequency estimation in videos
Silvia L. Pintea, Jian Zheng, Xilin Li +3
We focus on the problem of estimating human hand-tremor frequency from input RGB video data. Estimating tremors from video is important for non-invasive monitoring, analyzing and d…
Recurrent knowledge distillation
Silvia L. Pintea, Yue Liu, Jan C. van Gemert
Knowledge distillation compacts deep networks by letting a small student network learn from a large teacher network. The accuracy of knowledge distillation recently benefited from…
Deja Vu: Motion Prediction in Static Images
Silvia L. Pintea, Jan C. van Gemert, Arnold W. M. Smeulders
This paper proposes motion prediction in single still images by learning it from a set of videos. The building assumption is that similar motion is characterized by similar appeara…
Featureless: Bypassing feature extraction in action categorization
Silvia L. Pintea, Pascal S. Mettes, Jan C. van Gemert +1
This method introduces an efficient manner of learning action categories without the need of feature estimation. The approach starts from low-level values, in a similar style to th…
Asymmetric kernel in Gaussian Processes for learning target variance
Silvia L. Pintea, Jan C. van Gemert, Arnold W. M. Smeulders
This work incorporates the multi-modality of the data distribution into a Gaussian Process regression model. We approach the problem from a discriminative perspective by learning,…