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 ...
Kernel methods yield state-of-the-art performance in certain applications such as image classification and object detection. However, large scale problems require machine learning...
Sreekanth Vempati, Andrea Vedaldi, Andrew Zisserma...
This paper presents a cascaded scheme with block-based and pixel-based codebooks for background subtraction. The codebook is mainly used to compress information to achieve high ef...
Predicting human occupations in photos has great application potentials in intelligent services and systems. However, using traditional classification methods cannot reliably dis...
Abstract. We introduced an algorithm for sequence alignment, based on maximizing local space-time correlations. Our algorithm aligns sequences of the same action performed at diffe...