Building a general-purpose, real-time active vision system completely based on biological models is a great challenge. We apply a number of biologically plausible algorithms which address different aspects of vision, such as edge and keypoint detection, feature extraction, optical flow and disparity, shape detection, object recognition and scene modelling into a complete system. We present some of the experiments from our ongoing work, where our system leverages a combination of algorithms to solve complex tasks. © 2013 Springer-Verlag.
CITATION STYLE
Terzić, K., Lobato, D., Saleiro, M., Martins, J., Farrajota, M., Rodrigues, J. M. F., & Du Buf, J. M. H. (2013). Biological models for active vision: Towards a unified architecture. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7963 LNCS, pp. 113–122). https://doi.org/10.1007/978-3-642-39402-7_12
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