We present a probabilistic framework for component-based automatic detection and tracking of objects in video. We represent objects as spatio-temporal two-layer graphical models, w...
Leonid Sigal, Ying Zhu, Dorin Comaniciu, Michael J...
In this study, an effective foreground/background segmentation approach for bootstrapping video sequences is proposed. First, a modified block representation approach is used to c...
This paper proposes a new evolutionary region merging method to improve segmentation quality result on oversegmented images. The initial segmented image is described by a modified ...
We present an efficient and accurate object tracking algorithm based on the concept of graph cut segmentation. The ability to track visible objects in real-time provides an inval...
We present a method to segment a collection of unlabeled images while exploiting automatically discovered appearance patterns shared between them. Given an unlabeled pool of multi...