We propose a novel approach to designing algorithms for
object tracking based on fusing multiple observation models.
As the space of possible observation models is too large
for...
Model learning and tracking are two important topics in computer vision. While there are many applications where one of them is used to support the other, there are currently only...
Abstract. We propose an online learning algorithm to tackle the problem of learning under limited computational resources in a teacher-student scenario, over multiple visual cues. ...
We derive a probabilistic framework for robust, real-time, visual tracking of previously unseen objects from a moving camera. The tracking problem is handled using a bag-of-pixels ...
We propose a method that rates the suitability of given templates for template-based tracking in real-time. This is important for applications with online template selection, such...