The simultaneous interpretation of object behaviour from real world image sequences is a highly desirable goal in machine vision. Although this is rather a sophisticated task, one ...
Jonathan H. Fernyhough, Anthony G. Cohn, David Hog...
We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...
In this work we deal with the problem of modelling and exploiting the interaction between the processes of image segmentation and object categorization. We propose a novel framewo...
Most tracking algorithms detect moving objects by comparing incoming images against a reference frame. Crucially, this reference image must adapt continuously to the current light...
Jonathan D. Rymel, John-Paul Renno, Darrel Greenhi...
In this paper, from the viewpoint of scene understanding, a 3-layer Bayesian hierarchical framework (BHF) is proposed for robust vacant parking space detection. In practice, the ch...