Alignment by maximization of mutual information
Massachusetts Institute of Technology · Intel (United States)
Abstract
A new information-theoretic approach is presented for finding the pose of an object in an image. The technique does not require information about the surface properties of the object, besides its shape, and is robust with respect to variations of illumination. In our derivation, few assumptions are made about the nature of the imaging process. As a result, the algorithms are quite general and can foreseeably be used in a wide variety of imaging situations. Experiments are presented that demonstrate the approach in registering magnetic resonance images, aligning a complex 3D object model to real scenes including clutter and occlusion, tracking a human head in a video sequence and aligning a view-based 2D object…
Citation impact
- FWCI
- 2139.86
- Percentile
- 100%
- References
- 36
Authors
2Topics & keywords
- Clutter
- Mutual information
- Computer science
- Artificial intelligence
- Computer vision
- Object (grammar)
- Maximization
- Feature (linguistics)