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Wald’s Sequential Analysis for Time-constrained Vision Problems
(IEEE, 2007-04)
In detection and matching problems in computer vision, both classification errors and time to decision characterize the quality of an algorithmic solution. We show how to formalize such problems in the framework of sequential ...
AdaBoost with Totally Corrective Updates for Fast Face Detection
(IEEE, 2004-05)
An extension of the AdaBoost learning algorithm is proposed and brought to bear on the face detection problem. In each weak classifier selection cycle, the novel totally corrective algorithm reduces aggressively the upper ...
WaldBoost – Learning for Time Constrained Sequential Detection
(IEEE, 2005-06)
In many computer vision classification problems, both the error and time characterizes the quality of a decision. We show that such problems can be formalized in the framework of sequential decision-making. If the false ...
Inter-stage Feature Propagation in Cascade Building with AdaBoost
(IEEE, 2004-08)
A modification of the cascaded detector with the Ada-Boost trained stage classifiers is proposed and brought to bear on the face detection problem. The cascaded detector is a sequential classifier with the ability of early ...