Abstract. We develop an object detection method combining top-down recognition with bottom-up image segmentation. There are two main steps in this method: a hypothesis generation s...
In this paper we address the problem of tracking an object in a video given its location in the first frame and no other information. Recently, a class of tracking techniques cal...
We describe a transition fault model, which is easy to simulate under test sequences that are applied at-speed, and provides a target for the generation of at-speed test sequences...
Many approaches to object recognition are founded on probability theory, and can be broadly characterized as either generative or discriminative according to whether or not the di...
Combining different and complementary object models promises to increase the robustness and generality of today’s computer vision algorithms. This paper introduces a new method ...