Humans demonstrate a remarkable ability to parse complicated motion sequences into their constituent structures and motions. We investigate this problem, attempting to learn the st...
Important ecological phenomena are often observed indirectly. Consequently, probabilistic latent variable models provide an important tool, because they can include explicit model...
Rebecca A. Hutchinson, Li-Ping Liu, Thomas G. Diet...
This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for...
Online camera recalibration is necessary for long-term deployment of computer vision systems. Existing algorithms assume that the source of recalibration information is a set of f...
Andrew W. Fitzgibbon, Duncan P. Robertson, Antonio...
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 conditi...