Conference proceeding
Active appearance motion model segmentation
Proceedings Second International Workshop on Digital and Computational Video, pp.64-68
2001
DOI: 10.1109/DCV.2001.929943
Abstract
An adaptive method for temporal sequence segmentation was developed and its performance assessed in the segmentation of cardiac motion image sequences. The primary contribution of this paper is the development of a novel, 2D+time active appearance motion model (AAMM) that represents the dynamics of the cardiac cycle in combination with the shape and image appearance of the heart. Cootes' 2D active appearance model (AAM) framework was extended by considering a complete image sequence as a single shape/intensity sample. This way, the proven strength of AAMs, like robustness and ability to capture observer preference, are augmented with temporal consistency over an image sequence.
Details
- Title: Subtitle
- Active appearance motion model segmentation
- Creators
- Milan Sonka - University of IowaBoudewijn P F LelieveldtSteven C MitchellJohan G BoschRob J van der GeestJohan H C Reiber
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings Second International Workshop on Digital and Computational Video, pp.64-68
- DOI
- 10.1109/DCV.2001.929943
- Publisher
- IEEE
- Language
- English
- Date published
- 2001
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Radiation Oncology; Fraternal Order of Eagles Diabetes Research Center; Injury Prevention Research Center; Ophthalmology and Visual Sciences
- Record Identifier
- 9984186706202771
Metrics
23 Record Views