Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/29314
Title: | Unified approach to coding and interpreting face images | Authors: | Lanitis, Andreas Taylor, Chris J. Cootes, Timothy F. |
Major Field of Science: | Engineering and Technology | Field Category: | Computer and Information Sciences;Arts;Design | Keywords: | Image coding;Face recognition;Image recognition;Shape;Facial features;Pattern recognition | Issue Date: | 20-Jun-1995 | Source: | Proceedings of IEEE International Conference on Computer Vision, 1995, USA, pp.368-373 | Start page: | 368 | End page: | 373 | Conference: | IEEE International Conference on Computer Vision | Abstract: | Face images are difficult to interpret because they are highly variable. Sources of variability include individual appearance, 3D pose, facial expression and lighting. We describe a compact parametrised model of facial appearance which takes into account all these sources of variability. The model represents both shape and grey-level appearance and is created by performing a statistical analysis over a training set of face images. A robust multi-resolution search algorithm is used to fit the model to faces in new images. This allows the main facial features to be located and a set of shape and grey-level appearance parameters to be recovered. A good approximation to a given face can be reconstructed using less than 100 of these parameters. This representation can be used for tasks such as image coding, person identification, pose recovery, gender recognition and expression recognition. The system performs well on all the tasks listed above. | URI: | https://hdl.handle.net/20.500.14279/29314 | DOI: | 10.1109/ICCV.1995.466919 | Rights: | © Copyright IEEE | Type: | Conference Papers | Affiliation : | The University of Manchester | Publication Type: | Peer Reviewed |
Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
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