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...
Abstract. We describe a flexible object recognition and modelling system (FORMS) which represents and recognizes animate objects from their silhouettes. This consists of a model fo...
In this paper, we introduce the semantic network model (SNM), a generalization of the hidden Markov model (HMM) that uses factorization of state transition probabilities to reduce...
Stjepan Rajko, Gang Qian, Todd Ingalls, Jodi James
We propose a multiple classifier system approach to object recognition in computer vision. The aim of the approach is to use multiple experts successively to prune the list of cand...
A novel method unifying viewer and model centered approaches for representing structurally complex 3-D objects like human faces is presented. The uni ed 3D frequency-domain repres...