We propose a novel approach for modelling correlations
between activities in a busy public space captured by multiple
non-overlapping and uncalibrated cameras. In our approach,
...
Chen Change Loy (Queen Mary, University of London)...
The supervised learning paradigm assumes in general that both training and test data are sampled from the same distribution. When this assumption is violated, we are in the setting...
Foreground detection is at the core of many video processing tasks. In this paper, we propose a novel video foreground detection method that exploits the statistics of 3D space-tim...
— Context is critical for reducing the uncertainty in object detection. However, context modelling is challenging because there are often many different types of contextual infor...
Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....