We present a novel framework for multiple object tracking in which the problems of object detection and data association are expressed by a single objective function. The framewor...
Zheng Wu, Ashwin Thangali, Stan Sclaroff, Margrit ...
Efficient use of an optimized custom memory hierarchy to exploit temporal locality in the memory accesses on array signals can have a very large impact on the power consumption i...
Tanja Van Achteren, Rudy Lauwereins, Francky Catth...
Many computer vision problems can be formulated in
a Bayesian framework with Markov Random Field (MRF)
or Conditional Random Field (CRF) priors. Usually, the
model assumes that ...
We present a new algorithm for color image quantization based on human color perception properties. We construct two kinds of map by analyzing the spatial color distributions to t...
A new framework is presented for both understanding and developing graph-cut based combinatorial algorithms suitable for the approximate optimization of a very wide class of MRFs ...