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...
This paper addresses real-time automatic visual tracking,
labeling and classification of a variable number of
objects such as pedestrians or/and vehicles, under timevarying
illu...
Spatiotemporal data is associated with vast amounts of raw samples. Given the limited computational resources typically available, an initial organization of this data supporting
...
Common objects such as people and cars comprise many visual parts and attributes, yet image-based tracking algorithms are often keyed to only one of a target's identifying ch...
In this paper, we propose a novel learning-based method for image hallucination, with image super-resolution being a specific application that we focus on here. Given a low-resolu...