Deterministic and stochastic methods for gaze tracking in real-time
Psychological evidence demonstrates how eye gaze analysis is requested for human computer interaction endowed with emotion recognition capabilities. The existing proposals analyse eyelid and iris motion by using colour information and edge detectors, but eye movements are quite fast and difficult fo...
| Autores: | , , |
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| Tipo de documento: | capítulo de livro |
| Data de publicação: | 2007 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositório: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglês |
| OAI Identifier: | oai:upcommons.upc.edu:2117/2667 |
| Acesso em linha: | https://hdl.handle.net/2117/2667 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Computer vision Visió per ordinador Classificació INSPEC::Pattern recognition::Computer vision Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo |
| Resumo: | Psychological evidence demonstrates how eye gaze analysis is requested for human computer interaction endowed with emotion recognition capabilities. The existing proposals analyse eyelid and iris motion by using colour information and edge detectors, but eye movements are quite fast and difficult for precise and robust tracking. Instead, we propose to reduce the dimensionality of the image-data by using multi-Gaussian modelling and transition estimations by applying partial differences. The tracking system can handle illumination changes, low-image resolution and occlusions while estimating eyelid and iris movements as continuous variables. Therefore, this is an accurate and robust tracking system for eyelids and irises in 3D for standard image quality. |
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