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Generic Object Detection based on Boosting embedded with Bag-of-words

机译:基于升放堆积的通用对象检测

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摘要

This paper studies generic object detection. In the view of complexity and diversity of generic object, it proposes Boosting generic object detection method with bag-of-words. Boosting method has good detection efficiency, but it has some fault detections due to the diversity and complexity of the object. While Bag-of-words method has some advantages, such as local patch features, simplicity and robustness, and it has good classification performance of complex object. The proposed method applies Bag-of-words to remove the fault detection and to improve the tracking results of Boosting, and thus it achieves high generic object detection accuracy.
机译:本文研究了通用物体检测。鉴于通用对象的复杂性和多样性,提出用单词袋装促进通用物体检测方法。升压方法具有良好的检测效率,但由于对象的多样性和复杂性,它具有一些故障检测。虽然单词袋式方法具有一些优点,如本地补丁功能,简单性和鲁棒性,它具有良好的复杂对象的分类性能。所提出的方法适用于单词袋来消除故障检测并提高升压的跟踪结果,从而实现高通用物体检测精度。

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