BREMOND , Francois

Many supervised approaches report state-of-the-art results for recognizing short-term actions in manually clipped videos by utilizing fine body motion information. The main downside of these approaches is that they are not applicable in real world settings. The challenge is different when it comes to unstructured scenes and long-term videos....

This paper tackles data selection for training set generation in the context of nearreal-time pedestrian detection through the introduction of a training methodology: FairTrain.After highlighting the impact of poorly chosen data on detector performance, we will introduce anew data selection technique utilizing the expectation-maximization...

Appearance based person re-identification in real-world video surveillance systems is a challenging problem for many reasons, including ineptness of existing low level features under significant viewpoint, illumination, or camera characteristic changes to robustly describe a person's appearance. One approach to handle appearance variability is...

The bag-of-words approach with local spatio-temporal features have become a popular video representation for action recognition. Recent methods have typically focused on capturing global and local statistics of features. However, existing approaches ignore relations between the features, particularly space-time arrangement of features, and thus...