This paper presents an Italic/Roman word type recognition system without a priori knowledge on the characters' font. This method aims at analyzing old documents in which char...
A novel framework for background music identification is proposed in this paper. Given a piece of audio signals that mixes background music with speech/noise, we identify the musi...
Model-based methods for sequential organization in cochannel speech require pretrained speaker models and often prior knowledge of participating speakers. We propose an unsupervis...
In this paper, we propose an approach to accurately localize detected objects. The goal is to predict which features pertain to the object and define the object extent with segme...
This paper treats tracking as a foreground/background classification problem and proposes an online semisupervised learning framework. Initialized with a small number of labeled ...