A principled approach to remove false alarms by modelling the context of a face detector
نویسندگان
چکیده
In this article we present a new method to enhance object detection by removing false alarms in a principled way with few parameters. The method models the output of an object classifier which we consider as the context. A hierarchical model is built using the detection distribution around a target sub-window to discriminate between false alarms and true detections. The specific case of face detection is chosen for this work as it is a mature field of research. We report results that are better than baseline methods on XM2VTS and MIT+CMU face databases. We significantly reduce the number of false acceptances while keeping the detection rate at approximately the same level.
منابع مشابه
On Improving Face Detection Performance by Modelling Contextual Information
In this paper we present a new method to enhance object detection by removing false alarms and merging multiple detections in a principled way with few parameters. The method models the output of an object classifier which we consider as the context. A hierarchical model is built using the detection distribution around a target sub-window to discriminate between false alarms and true detections...
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