Boosting-based Face Detection and Adaptation

Boosting-based Face Detection and Adaptation

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In many applications, a detector trained with generic data sets may not perform optimally in a new environment. We propose detection adaption, which is a promising solution for this problem. We present an adaptation scheme based on the Taylor expansion of the boosting learning objective function, and we propose to store the second order statistics of the generic training data for future adaptation. We show that with a small amount of labeled data in the new environment, the detector's performance can be greatly improved. --In many applications, a detector trained with generic data sets may not perform optimally in a new environment.


Title:Boosting-based Face Detection and Adaptation
Author: Cha Zhang, Zhengyou Zhang
Publisher:Morgan & Claypool Publishers - 2010
ISBN-13:

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