We present a novel stereo vision modeling framework that generates approximate, yet physically-plausible representations of objects rather than creating accurate models that are c...
Krishnanand N. Kaipa, Josh C. Bongard, Andrew N. M...
This paper presents a Bayesian network based multimodal fusion method for robust and real-time face tracking. The Bayesian network integrates a prior of second order system dynami...
We propose to shift the goal of recognition from naming
to describing. Doing so allows us not only to name familiar
objects, but also: to report unusual aspects of a familiar
ob...
Ali Farhadi, David A. Forsyth, Derek Hoiem, Ian En...
In this paper we describe the first stage of a new learning system for object detection and recognition. For our system we propose Boosting [5] as the underlying learning technique...
Andreas Opelt, Michael Fussenegger, Axel Pinz, Pet...
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...