Segment Cluster Tracking is a new approach of motion analysis in the class of mapping methods/algorithms. It solves the correspondence problem by matching image regions, resp. features of image regions. The image regions are created by combining color segments the result of a color segmentationto segment clusters. The tracking task is to find best correspondences between clusters of segments in...

Object tracking is a issue in the domain of computer visual, most of current state-of-art approaches for visual tracking adapt tracking-by-detection, using detection to address tracking problem. While suitable for cases when the object is always in the sense and these algorithms always results in failures and can’t track back after failure. This paper we propose a tracking method based on failu...

SUMMARY In order to investigate reading processes of Japanese language learners, we have conducted an experiment to record eye movements during Japanese text reading using an eye-tracking system. We showed that Japanese native speakers use " forward and backward jumping eye movements " frequently [13], [14]. In this paper, we analyzed further the same eye tracking data. Our goal is to examine w...

Title of dissertation Robust Methods for Visual Tracking and Model Alignment Hao Wu, Doctor of Philosophy, 2009 Directed by Professor Rama Chellappa Department of Electrical and Computer Engineering The ubiquitous presence of cameras and camera networks needs the development of robust visual analytics algorithms. As the building block of many video surveillance tasks, a robust visual tracking a...

The paper describes a simple but effective method for incorporating automatically learned tempo models into realtime music tracking systems. In particular, instead of training our system with ‘rehearsal data’ by a particular performer, we provide it with many different interpretations of a given piece, possibly by many different performers. During the tracking process the system continuously re...

The problem of belief tracking in the presence of stochastic actions and observations is pervasive and yet computationally intractable. In this work we show however that probabilistic beliefs can be maintained in factored form exactly and efficiently across a number of causally closed beams, when the state variables that appear in more than one beam obey a form of backward determinism. Since co...

This paper presents a first attempt to bridge the gap between logical and cognitive treatments of strategic reasoning in games. The focus of the paper is backward induction, a principle which is purported to follow from common knowledge of rationality by Zermelo’s theorem. There have been extensive formal debates about the merits of principle of backward induction among game theorists and logic...

In this paper, we present improved wordlevel confidence measures based on posterior probabilities for children’s oral reading continuous speech recognition. Initially we compute posterior probability based confidence measures on word graphs using a forward-backward algorithm. We study how an increase of the word graph density affects the quality of these confidence measures. For this purpose we...