Sketch-based image retrieval using keyshapes
Keywords: Sketch-based image retrieval, Content-based image retrieval, Local descriptors, Local matching
Abstract
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.
Más información
Título según WOS: | Sketch-based image retrieval using keyshapes |
Título según SCOPUS: | Sketch-based image retrieval using keyshapes |
Título de la Revista: | MULTIMEDIA TOOLS AND APPLICATIONS |
Volumen: | 73 |
Número: | 3 |
Editorial: | Springer |
Fecha de publicación: | 2014 |
Página de inicio: | 2033 |
Página final: | 2062 |
Idioma: | English |
DOI: |
10.1007/s11042-013-1689-0 |
Notas: | ISI, SCOPUS |