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Disparity energy model using a trained neuronal population
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Orientador(es)
Resumo(s)
Depth information using the biological Disparity Energy Model can be obtained by using a population of complex
cells. This model explicitly involves cell parameters like their
spatial frequency, orientation, binocular phase and position
difference. However, this is a mathematical model. Our brain
does not have access to such parameters, it can only exploit
responses. Therefore, we use a new model for encoding disparity
information implicitly by employing a trained binocular neuronal
population. This model allows to decode disparity information in
a way similar to how our visual system could have developed this
ability, during evolution, in order to accurately estimate disparity
of entire scenes
Descrição
Palavras-chave
Visão humana Córtex Disparity Biological model Learning Population coding
Contexto Educativo
Citação
Martins, Jaime A.; Rodrigues, J.M.F.; du Buf, J.M.H. Disparity energy model using a trained neuronal population, Trabalho apresentado em 2011 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), In 2011 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Bilbao, Spain, 2011.
Editora
IEEE