In this paper we present a principled Bayesian method for detecting and segmenting instances of a particular object category within an image, providing a coherent methodology for ...
M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserma...
The success of tensor-based subspace learning depends heavily on reducing correlations along the column vectors of the mode-k flattened matrix. In this work, we study the problem ...
Shuicheng Yan, Dong Xu, Stephen Lin, Thomas S. Hua...
We propose a new local learning scheme that is based on the principle of decisiveness: the learned classifier is expected to exhibit large variability in the direction of the test ...
In this paper, efficient and generic tools for calibration and 3D reconstruction are presented. These tools exploit geometric constraints frequently present in man-made environmen...
With the growing presence of high definition video content on battery-operated handheld devices such as camera phones, digital still cameras, digital camcorders, and personal medi...
Vivienne Sze, Anantha P. Chandrakasan, Madhukar Bu...