Research Interests

Computer Vision: My long-term goal is to design an image-understanding system, which mimics human image-categorization and image-search performance. The overall approach is motivated by a number of perceptual and cognitive studies, which is summarized in a monograph I have written a few years ago. So far I have developed a contour partitioning, description and grouping process, which was already successfully applied in image classification, image retrieval, shape classification and video genre classification. To improve the system, we now elaborate the grouping and learning process. We are eager to apply the methodology to other tasks, in which contour information is beneficial (object recognition, video surveillance, medical imaging, face analysis, etc.)

            image classification I                       my early work

image classification II                      reaching some benchmarks with contour groupings

image classification [site]                shows results from image classification (categorization), searches and sorting.

image retrieval                                  our results at ImageCLEF 2010.

video retrieval                                   how the methodology improves video indexing.

shape retrieval                                  a quick and efficient way to describe shapes.

COREL category labels                  contains info about the labeling of the COREL image classes.

[link to visual search]                      discusses search aspects (e.g., regions of interest).

 

(Some) Former Research

Applied Visual Perception: Human-computer interaction at visual interfaces, such as the PC monitor, is still relatively awkward. The interaction could be easily improved if human gaze position were tracked and guided toward task-relevant locations (Barth et al 2006). To realize that in practice, it requires a good concept of how to read the user’s attention and how to generate the appropriate process of gaze guidance. I have assembled a list of aspects, which allows me to systematically approach this issue, and I have carried out basic eye-movement research to investigate some of these aspects in detail. Some of my applied ideas were implemented in collaboration with Michael Dorr at the University of Lübeck. To gain a more detailed understanding of saccadic target selection, I analyzed fixation locations made in real scenes, a project done in collaboration with Ben Tatler at the University of Dundee.

 

[link to gaze guidance]                    surveys my part of the research collaboration.

[link to applied project]                    a gaze-recapturing editor cursor (GREC) to improve text-editing on a PC monitor.

[link to saccadic target selection]    an analysis of saccadic target selection.

[link to project website]                    5 different European labs were involved.

 

 


Christoph Rasche