Please use this identifier to cite or link to this item:
http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/5569Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.creator | Kumar, Vinay P. | - |
| dc.date | 2004-10-01T14:00:07Z | - |
| dc.date | 2004-10-01T14:00:07Z | - |
| dc.date | 2002-09-01 | - |
| dc.date.accessioned | 2013-10-09T02:40:09Z | - |
| dc.date.available | 2013-10-09T02:40:09Z | - |
| dc.date.issued | 2013-10-09 | - |
| dc.identifier | AITR-2002-008 | - |
| dc.identifier | CBCL-221 | - |
| dc.identifier | http://hdl.handle.net/1721.1/5569 | - |
| dc.identifier.uri | http://koha.mediu.edu.my:8181/xmlui/handle/1721 | - |
| dc.description | This thesis proposes a methodology for the design of man-machine interfaces by combining top-down and bottom-up processes in vision. From a computational perspective, we propose that the scientific-cognitive question of combining top-down and bottom-up knowledge is similar to the engineering question of labeling a training set in a supervised learning problem. We investigate these questions in the realm of facial analysis. We propose the use of a linear morphable model (LMM) for representing top-down structure and use it to model various facial variations such as mouth shapes and expression, the pose of faces and visual speech (visemes). We apply a supervised learning method based on support vector machine (SVM) regression for estimating the parameters of LMMs directly from pixel-based representations of faces. We combine these methods for designing new, more self-contained systems for recognizing facial expressions, estimating facial pose and for recognizing visemes. | - |
| dc.format | 68 p. | - |
| dc.format | 21293042 bytes | - |
| dc.format | 2473001 bytes | - |
| dc.format | application/postscript | - |
| dc.format | application/pdf | - |
| dc.language | en_US | - |
| dc.relation | AITR-2002-008 | - |
| dc.relation | CBCL-221 | - |
| dc.subject | AI | - |
| dc.subject | Facial Expression Recognition | - |
| dc.subject | Pose Estimation | - |
| dc.subject | Viseme Recognition | - |
| dc.subject | SVM | - |
| dc.title | Towards Man-Machine Interfaces: Combining Top-down Constraints with Bottom-up Learning in Facial Analysis | - |
| Appears in Collections: | MIT Items | |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.