The study of transportability aims to identify conditions under which causal information learned from experiments can be reused in a different environment where only passive obser...
In this paper, we present a multi-label sparse coding
framework for feature extraction and classification within
the context of automatic image annotation. First, each image
is ...
Changhu Wang (University of Science and Technology...
This paper deals with the problem of tracking multiple targets in a distributed network of self-configuring pan-tilt-zoom cameras. We focus on applications where events unfold over...
Higher order spatial features, such as doublets or
triplets have been used to incorporate spatial information
into the bag-of-local-features model. Due to computational
limits, ...
Mean shift clustering is a powerful unsupervised data
analysis technique which does not require prior knowledge
of the number of clusters, and does not constrain the shape
of th...