Annotating image regions using spatial context

Zhiyong Wang, David D. Feng, Zheru Chi, Tian Xia

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

10 Citations (Scopus)


Image annotation plays an important role in bridging the semantic gap between low level features and high level semantic contents in image access. In this paper, such a task is tackled by annotating regions which are primitives of a visual scene. We propose a probabilistic model to characterize spatial context for region annotation. Such a model provides a unifying framework integrating both feature distribution models and spatial context models. A wide range of advanced modeling techniques can be utilized to further extend this framework. The approach is also potentially scalable to a large number of semantic concepts and a large number of images. Experimental results based on simple parametric models demonstrate promising results of our approach by investigating the impacts of neighbors, segmentation, and visual features.
Original languageEnglish
Title of host publicationISM 2006 - 8th IEEE International Symposium on Multimedia
Number of pages7
Publication statusPublished - 1 Dec 2006
EventISM 2006 - 8th IEEE International Symposium on Multimedia - San Diego, CA, United States
Duration: 11 Dec 200613 Dec 2006


ConferenceISM 2006 - 8th IEEE International Symposium on Multimedia
Country/TerritoryUnited States
CitySan Diego, CA

ASJC Scopus subject areas

  • Computer Networks and Communications


Dive into the research topics of 'Annotating image regions using spatial context'. Together they form a unique fingerprint.

Cite this