Compressive sensing (CS) has been proposed for signals with sparsity in a linear transform domain. We explore a signal dependent unknown linear transform, namely the impulse respo...
Learning-enhanced relevance feedback is one of the most promising and active research directions in recent year's content-based image retrieval. However, the existing approac...
Tracking 3D people from monocular video is often poorly constrained. To mitigate this problem, prior knowledge should be exploited. In this paper, the Gaussian process spatio-temp...
CAMs are the most popular practical method for implementing packet classification in high performance routers. Their principal drawbacks are high power consumption and inefficient...
Ed Spitznagel, David E. Taylor, Jonathan S. Turner
We analyze the problem of reconstructing a 2D function that approximates a set of desired gradients and a data term. The combined data and gradient terms enable operations like mod...
Pravin Bhat, Brian Curless, Michael F. Cohen, C. L...