Codebook-free exemplar models for object detection

Jan Hendrik Becker, T. Tuytelaars, L. Gool
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引用次数: 1

Abstract

Traditional bag-of-features approaches often vector-quantise the features into a visual codebook. This process inevitably causes loss of information. Recently codebook-free methods that avoid the vector-quantisation step have become more popular. Used in conjunction with nearest-neighbour approaches these methods have shown remarkable classification performance. In this paper we show how to exploit the concept of nearest neighbour based classification for object detection. Our codebook-free exemplar model combines the classification power of nearest neighbour methods with a detection concept based on exemplar models. We demonstrate the performance of our proposed system on a real-world dataset of images of motorbikes.
用于对象检测的无代码本范例模型
传统的特征袋方法通常将特征矢量量化为视觉码本。这个过程不可避免地会造成信息的丢失。最近,避免矢量量化步骤的无码本方法变得越来越流行。与最近邻方法结合使用,这些方法显示出显著的分类性能。在本文中,我们展示了如何利用基于最近邻的分类概念进行目标检测。我们的无码本范例模型结合了最近邻方法的分类能力和基于范例模型的检测概念。我们在摩托车图像的真实数据集上演示了我们提出的系统的性能。
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