This paper tackles the problem of fitting multiple instances of a model to data corrupted by noise and outliers. The proposed solution is based on random sampling and conceptual da...
This paper presents a probabilistic framework for off-line multiple object tracking. At each timestep, a small set of deterministic candidates is generated which is guaranteed to ...
W e present a simple and eficient scheme for using the Set Partitioning in Hierarchical Trees (SPIHT) image compression algorithm [l]in a generalized multiple description framewor...
Agnieszka C. Miguel, Alexander E. Mohr, Eve A. Ris...
In this paper, a novel method for simultaneously registering multiple images acquired from different imaging modalities is presented. The optimal alignment is computed as the set ...
This paper presents a prediction algorithm for estimating the upper bound of future Web traffic volume. Unlike traditional traffic predictions that are performed at a single time ...