Abstract
The Minimum Description Length (MDL) approach to shape modelling seeks a compact description of a set of shapes in terms of the coordinates of marks on the shapes. It has been shown that the mark positions resulting from this optimisation to a large extent solve the so-called point correspondence problem: How to select points on shapes defined as curves so that the points correspond across a data set. However, this MDL approach does not capture important shape characteristics related to the curvature of the curves, and occasionally it places marks in obvious conflict with the human notion of point correspondence. This paper shows how the MDL approach can be fine-tuned by adding a term to the cost function expressing the mismatch of curvature features across the data set. The method is illustrated on silhouettes of adult heads. The MDL method is able to solve the point correspondence problem and a classification of the heads into male and female improves dramatically when using the MDL-generated marks.
Original language | English |
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Title of host publication | British Machine Vision Conference, BMVC |
Publication date | 2003 |
Publication status | Published - 2003 |
Event | British Machine Vision Conference, BMVC - Duration: 1 Jan 2003 → … |
Conference
Conference | British Machine Vision Conference, BMVC |
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Period | 01/01/2003 → … |
Keywords
- face recognition
- shape modelling
- silhouettes
- minimum description length
- point correspondence problem
- curvature