The compositional nature of visual objects significantly limits their representation complexity and renders learning of structured object models tractable. Adopting this modeling ...
Belief propagation over pairwise connected Markov Random Fields has become a widely used approach, and has been successfully applied to several important computer vision problems....
Automatically discovering common visual patterns from a collection of images is an interesting but yet challenging task, in part because it is computationally prohibiting. Althoug...
We present an object recognition algorithm that uses model and image line features to locate complex objects in high clutter environments. Finding correspondences between model an...
Discriminative learning is challenging when examples are sets of features, and the sets vary in cardinality and lack any sort of meaningful ordering. Kernel-based classification m...