Image search using trained flexible shape models
- 1 January 1994
- journal article
- research article
- Published by Taylor & Francis in Journal of Applied Statistics
- Vol. 21 (1-2) , 111-139
- https://doi.org/10.1080/757582971
Abstract
This paper describes a technique for building compact models of the shape and appearance of flexible objects seen in two-dimensional images. The models are derived from the statistics of sets of images of example objects with ‘landmark’ points labelled on each object. Each model consists of a flexible shape template, describing how the landmark points can vary, and a statistical model of the expected grey levels in regions around each point. Such models have proved useful in a wide variety of applications. We describe how the models can be used in local image search and give examples of their application.Keywords
This publication has 11 references indexed in Scilit:
- Feature extraction from faces using deformable templatesInternational Journal of Computer Vision, 1992
- A geometrical derivation of the shape densityAdvances in Applied Probability, 1991
- Closed-form solutions for physically based shape modeling and recognitionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1991
- General shape distributions in a planeAdvances in Applied Probability, 1991
- Fitting parameterized three-dimensional models to imagesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1991
- Procrustes Methods in the Statistical Analysis of ShapeJournal of the Royal Statistical Society Series B: Statistical Methodology, 1991
- Principal warps: thin-plate splines and the decomposition of deformationsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1989
- The statistical analysis of shape dataBiometrika, 1989
- Model-based recognition in robot visionACM Computing Surveys, 1986
- Generalized Procrustes AnalysisPsychometrika, 1975