Seeing between the pixels: pictures in interactive systems
Seeing between the pixels: pictures in interactive systems
WordsEye: an automatic text-to-scene conversion system
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Non-photorealistic computer graphics: modeling, rendering, and animation
Non-photorealistic computer graphics: modeling, rendering, and animation
Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
International Journal of Computer Vision
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Glyphs for Software Visualization
WPC '97 Proceedings of the 5th International Workshop on Program Comprehension (WPC '97)
ACM SIGGRAPH 2003 Papers
Mean version space: a new active learning method for content-based image retrieval
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
The Story Picturing Engine---a system for automatic text illustration
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
ACM SIGGRAPH 2006 Papers
Structure-preserving manipulation of photographs
Proceedings of the 5th international symposium on Non-photorealistic animation and rendering
ACM SIGGRAPH 2007 papers
Conjoint Analysis to Measure the Perceived Quality in Volume Rendering
IEEE Transactions on Visualization and Computer Graphics
Image retrieval: Ideas, influences, and trends of the new age
ACM Computing Surveys (CSUR)
Modeling and Recognition of Landmark Image Collections Using Iconic Scene Graphs
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Studying aesthetics in photographic images using a computational approach
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
| Hi-index | 0.00 |
The majority of visual communication today occurs by ways of spatial groupings, plots, graphs, data renderings, photographs and video frames. However, the degree of semantics encoded in these visual representations is still quite limited. The use of icons as a form of information encoding has been explored to a much lesser extent. In this paper we describe a framework that uses a dual domain approach involving natural language text processing and global image databases to help users identify icons suitable to visually encode abstract semantic concepts.