.png){kind=icon}
返回
Sketch-based image retrieval using keyshapes
.png){kind=icon}
PRE
AI
DOI：10.1007/s11042-013-1689-0.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Although sketch based image retrieval (SBIR) is still a young research area, there are many applications capable of exploiting this retrieval paradigm, such as web searching and pattern detection. Moreover, nowadays drawing a simple sketch query turns very simple since touch screen based technology is being expanded. In this work, we propose a novel local approach for SBIR based on detecting simple shapes which are named keyshapes. Our method works as a local strategy, but instead of detecting keypoints, it detects keyshapes over which local descriptors are computed. Our proposal based on keyshapes allow us to represent the structure of the objects in an image which could be used to increase the effectiveness in the retrieval task. Indeed, our results show an improvement in the retrieval effectiveness with respect to the state of the art. Furthermore, we demonstrate that combining our keyshape approach with a Bag of Feature approach allows us to achieve significant improvement with respect to the effectiveness of the retrieval task.
Keyword:
Sketch-based image retrieval
Content-based image retrieval
Local descriptors
Local matching
期刊
IF:
3
论文数:
1.9W
被引数:
3.2W
机构
引用论文
Monitoring nature-based tourism trends in Japan’s national parks: Mixed messages from domestic and inbound visitors.png)
PARKS
OAAI
PARKSIF0
OAAI分享收藏Crystalline‐State Reaction with Allosteric Effect in Spin‐Crossover, Interpenetrated Networks with Magnetic and Optical Bistability具有磁和光学双稳态的自旋交叉，互穿网络中具有变构效应的晶态反应
PREAI
分享收藏分享收藏Analyzing Actors’ Engagement in Sustainable Energy Planning at the Local Level in Ghana: An Empirical StudyEnergiesOAAI
EnergiesIF0
OAAI分享收藏
查看更多内容