This paper presents an unsupervised segmentation method for feature sequences based on competitivelearning hidden Markov models. Models associated with the nodes of the Self-Organ...
This paper presents a method for incrementally segmenting images over time using both intensity and motion information. This is done by formulating a model of physically signi cant...
We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hid...
John D. Lafferty, Andrew McCallum, Fernando C. N. ...
Stereo sequences promise to be a powerful method for segmenting images for applications such as tracking human figures. We present a method of statistical background modeling for ...
Christopher K. Eveland, Kurt Konolige, Robert C. B...
In this paper we explore the problem of accurately segmenting a person from a video given only approximate location of that person. Unlike previous work which assumes that the app...