| dc.contributor.author | Han, J.W. | |
| dc.contributor.author | Lane, P.C.R. | |
| dc.contributor.author | Davey, N. | |
| dc.contributor.author | Sun, Yi | |
| dc.date.accessioned | 2010-04-27T11:22:45Z | |
| dc.date.available | 2010-04-27T11:22:45Z | |
| dc.date.issued | 2009 | |
| dc.identifier.citation | In: Procs of the Int Conf on Methods and Models in Computer Science, ICM2CS09, art. no. 5397992 | en |
| dc.identifier.isbn | 978-1-4244-5051-0 | |
| dc.identifier.other | 903955 | |
| dc.identifier.uri | http://hdl.handle.net/2299/4450 | |
| dc.description | “This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder."
“Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.” | en |
| dc.description.abstract | Locating and identifying complex objects in a visual scene is a typical problem within the areas of computer vision and image analysis. One technique to minimise the size of image to be identified is to base the classification on smaller features of the image, which are combined into a more complex structure to identify the complete object. For example, locating two eyes, a nose and a mouth can enable us to identify a face without paying attention to the hair, chin or cheeks. In this paper, we present a system and training technique for learning to recognise an object from its component features. Our system incorporates an attention-based mechanism to predict the location of features. We demonstrate the effectiveness of our system with an experiment in face detection; the attention mechanism is shown to improve the overall classification speed and accuracy of feature location. | en |
| dc.format.extent | 6873230 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | en | en |
| dc.publisher | IEEE | en |
| dc.title | Attention mechanisms and component-based face detection. | en |
| dc.type | Conference paper | en |
| herts.preservation.rarelyaccessed | true | |
