Abstract
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.
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Terzić, K. et al. (2013). Biological Models for Active Vision: Towards a Unified Architecture. In: Chen, M., Leibe, B., Neumann, B. (eds) Computer Vision Systems. ICVS 2013. Lecture Notes in Computer Science, vol 7963. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39402-7_12
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DOI: https://doi.org/10.1007/978-3-642-39402-7_12
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