Martins, JaimeRodrigues, J. M. F.du Buf, J. M. H.2013-01-152013-01-152011Martins, 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, 2011.978-1-4673-0753-6AUT: JRO00913; DUB00865;http://hdl.handle.net/10400.1/2078Depth 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 scenesengVisão humanaCórtexDisparityBiological modelLearningPopulation codingconference object2012-12-27