A performance evaluation of gradient field HOG descriptor for sketch based image retrieval
A performance evaluation of gradient field HOG descriptor for sketch based image retrieval
复制标题
DOI：
10.1016/j.cviu.2013.02.005
复制
发表时间：
2013-07-01
影响因子：
4.5
通讯作者：
Collomosse, John
中科院分区：
文献类型：
--
作者：
Hu, Rui;Collomosse, John
我们提出了一个图像检索系统的交互式搜索的照片集，使用手绘草图描绘形状。我们描述梯度场HOG（GF-HOG），一个适应形式的HOG描述符适合于基于草图的图像检索（SBIR）。我们将GF-HOG到一袋视觉词（BoVW）检索框架，并演示了如何利用这种组合既强大的SBIR，并在图像中定位素描对象。我们评估了一个大型的Flickr来源的数据集，包括33个形状类别，使用10个非专家素描查询。我们将GF-HOG与最先进的描述符进行比较，这些描述符具有常见的距离度量和用于图像检索的语言模型，并探索草图的仿射变形如何影响搜索性能。GF-HOG被证明始终优于检索SIFT，多分辨率HOG，自相似性，形状上下文和结构张量。此外，我们将语义关键字到我们的GF-HOG系统，使图像搜索的注释草图的使用。提出了一种新的基于图的语义相似性度量方法，并探讨了两个应用：基于语义草图的图像检索和语义照片蒙太奇。(C)2013 Elsevier Inc. All rights reserved.
We present an image retrieval system for the interactive search of photo collections using free-hand sketches depicting shape. We describe Gradient Field HOG (GF-HOG); an adapted form of the HOG descriptor suitable for Sketch Based Image Retrieval (SBIR). We incorporate GF-HOG into a Bag of Visual Words (BoVW) retrieval framework, and demonstrate how this combination may be harnessed both for robust SBIR, and for localizing sketched objects within an image. We evaluate over a large Flickr sourced dataset comprising 33 shape categories, using queries from 10 non-expert sketchers. We compare GF-HOG against state-of-the-art descriptors with common distance measures and language models for image retrieval, and explore how affine deformation of the sketch impacts search performance. GF-HOG is shown to consistently outperform retrieval versus SIFT, multi-resolution HOG, Self Similarity, Shape Context and Structure Tensor. Further, we incorporate semantic keywords into our GF-HOG system to enable the use of annotated sketches for image search. A novel graph-based measure of semantic similarity is proposed and two applications explored: semantic sketch based image retrieval and a semantic photo montage. (C) 2013 Elsevier Inc. All rights reserved.