Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/29352
Title: | Classifying variable objects using a flexible shape model | Authors: | Lanitis, Andreas Taylor, Chris J. Ahmed, T. Cootes, Timothy F. |
Major Field of Science: | Engineering and Technology;Agricultural Sciences | Field Category: | Computer and Information Sciences;Design | Keywords: | Image classification;Face recognition;Image representations;Statistics | Issue Date: | 4-Jul-1995 | Source: | Fifth International Conference on Image Processing and its Applications, 1995, Edinburgh, pp.70-74 | Start page: | 70 | End page: | 74 | Conference: | Fifth International Conference on Image Processing and its Applications | Abstract: | Point Distribution Models (PDMs) are statistical models which represent objects whose shape can vary. A useful feature of PDMs is their ability to capture the shape of variable objects within a training set with a small number of shape parameters. This compact and accurate parametrization can be used for the design of efficient classification systems. In this paper we describe a classification system which uses shape parameters. We have tested the system on classifying hand outlines, face outlines and hand gestures; experimental results are presented. | URI: | https://hdl.handle.net/20.500.14279/29352 | DOI: | 10.1049/cp:19950622 | Type: | Conference Papers | Affiliation : | Wolfson Image Analysis Unit |
Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
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