Carlos Arturo Hernández-Gracidas

Learn More
Content-based image retrieval (CBIR) is currently limited because of the lack of representational power of the low-level image features, which fail to properly represent the actual contents of an image, and consequently poor results are achieved with the use of this sole information. Spatial relations represent a class of high-level image features which can(More)
We describe the object retrieval task of ImageCLEF 2007, give an overview of the methods of the participating groups, and present and discuss the results. The task was based on the widely used PASCAL object recognition data to train object recognition methods and on the IAPR TC-12 benchmark dataset from which images of objects of the ten different classes(More)
In this paper we proposed the use of spatial relations as a way of improving annotation-based image retrieval. We analyzed different types of spatial relations and selected the most adequate ones for image retrieval. We developed an image comparison and retrieval method based on conceptual graphs, which incorporates spatial relations. Additionally, we(More)
Content-based image retrieval is one attractive research field in computer vision, but also one facing critical problems. Approaches using the image as a whole and those focused on identifying relevant objects in the image, usually fail with several topics, for which they cannot provide a rich enough representation. Recent methods try to solve this problem(More)
Using as experimental platform an image retrieval method based on a spatio-conceptual representation of images, in this paper we investigate two main concerns on annotationbased image retrieval: label weighting and data fusion. On the one hand, we analyze the influence of different weighting schemes on the quality of the retrieval performance, and, on the(More)
  • 1