Shape Matching
Multimedia Indexing
Music Retrieval
3D Shape Recognition
Medical Imaging
Publications

Although the human visual system is very good at the interpretation of images, the amount of digitally acquired and stored data is so large that we need computerized analysis and retrieval methods to handle it. Many applications exist in industry, company archives, internet, and hospital environments. Two examples are verification of misuse of a company logo among one of the millions of images on the Web, and examination and retrieval of the millions of digital medical scans made every year. Characteristic to our research is that fundamental research is followed by experimental verification. The approach we take is strongly algorithmic, and we put emphasis on the analysis of shape of patterns that are present in images, sound, video, and 3D scenes.

The topics we work on are feature extraction, segmentation, matching of images, and organization of images in index structures for efficient retrieval, with a focus on medical imaging and shape-based multimedia. Our research in medical imaging is concerned with alignment of 3D scans (CT, MRI, etc.). Our research in multimedia is concerned with the algorithmic aspects of shape analysis. Some aspects involved are the representation, decomposition, approximation, and deformation of shape, the transformation of one shape into another, the measuring how similar two shapes are, and the organization of shapes in (index) search structures.

The research focusses on the following topics:

Shape Matching
For shape-based image matching, features are extracted from images, such as edge and corner points, curves, and regions. The set of feature of one image is then translated, rotated, and scaled so as to minimize some similarity function with respect to the features from the other image. We develop similarity functions that are robust against noise, occlusion, blurring, and small deformations, as well as algorithms to compute them efficiently.

Multimedia Indexing
We are primarily interested in multimeda retrieval based on the certain pattterns that are present in the content. For example patterns of shape in images and video, or patterns of themes in music. Recognition and matching of the shape of such patterns is often a computationally expensive task. For large collections this makes it unrealistic to sequentially match all multimedia objects in the database with the query. Therefore we investigate indexing search structures that make it possible to use accurate but complex similarity measures and computationaly expensive matching algorithms, while the search is still efficient.

3D Shape Recognition
In reverse engineering, robot vision, machine part database retrieval and many other applications, one of the primary tasks is to match and classify a given 3D object shape. Laser scanning devices, web repositories, and private industrial database provide a huge amount of 3D shapes in the form of point clouds or polyhedral surfaces. We perform research on the matching two point clouds, a point set with a polyhedral surface, and two polyhedral surfaces. Two research issues are how to do partial matching, and how to achieve a accurate match without an good initial estimate.

Medical Imaging
Our research in the area of medical imaging focuses on image processing and image analysis techniques for the tasks of image segmentation and image registration. Currently, specific projects involve the accurate segmentation of the aortic lumen and aortic thrombus using a model-based approach, and the improvement and extension of current medical image registration techniques based on an information-theoretic approach.