Landmark Based Image Analysis

Landmarks are preferred image features for a variety of computer vision tasks such as image mensuration, registration, camera calibration, motion analysis, 3D scene reconstruction, and object recognition. This is a comprehensive treatment of the extraction of landmarks from multi-modality images and the use of these features for elastic image registration. The emphasis is on model-based approaches, that is, the use of explicitly represented knowledge in computer vision. Both geometric models (describing the shape of objects) and intensity models (directly representing the image intensities) are utilized. The work describes theoretical foundations, computational and algorithmic issues, as well as practical applications, notably in medicine (neurosurgery and radiology), remote sensing, and industrial automation. Connections with computer graphics and artificial intelligence are illustrated.