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Asymmetric Totally-Corrective Boosting for Real-Time Object Detection

Wang, Peng; Shen, Chunhua; Barnes, Nick; Zheng, Hong; Ren, Zhang


Real-time object detection is one of the core problems in computer vision. The cascade boosting framework proposed by Viola and Jones has become the standard for this problem. In this framework, the learning goal for each node is asymmetric, which is required to achieve a high detection rate and a moderate false positive rate. We develop new boosting algorithms to address this asymmetric learning problem. We show that our methods explicitly optimize asymmetric loss objectives in a totally...[Show more]

CollectionsANU Research Publications
Date published: 2010
Type: Conference paper
Source: Proceedings of ACCV 2010
DOI: 10.1007/978-3-642-19315-6_14


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