We propose an algorithm to perform causal inference of the state of a dynamical model when the measurements are corrupted by outliers. While the optimal (maximumlikelihood) soluti...
Andrea Vedaldi, Hailin Jin, Paolo Favaro, Stefano ...
Informational Macrodynamics (IMD) presents a unified informational systemic approach with common information language for modeling, analysis and optimization of a variety of inter...
This paper proposes an advanced spatially scalable video coding approach that exploits the inter layer correlation between different resolution layers by classified patch learning...
—We present a discriminative part-based approach for human action recognition from video sequences using motion features. Our model is based on the recently proposed hidden condi...
While numerous algorithms have been proposed for object tracking with demonstrated success, it remains a challenging problem for a tracker to handle large change in scale, motion,...