Motion and depth estimation for autonomous
Transcript
Motion and depth estimation for autonomous
Università degli Studi di Genova Academic year 2015-2016 MASTER EMARO (Second Year) European Master on Advanced Robotics thesis short proposal Title: Motion and depth estimation for autonomous navigation Where: Genova Short summary To navigate in a real environment, e.g. to avoid obstacle and target, is a crucial ability for artificial agents. The motion information about the scene can be effectively computed by inspired models of the human visual system. The aim of this thesis is to develop an integrated neural autonomous navigation. The expected results are software modules (CPU or GPU-based) and depth estimation, and their assessment in real conditions. to reach a and depth using biomodel for for motion To better understand: 1 – 2 bibliographic references (please documents accessible from internet) F Solari, M Chessa, NVK Medathati, P Kornprobst. What can we expect from a V1-MT feedforward architecture for optical flow estimation? Signal Processing: Image Communication, 2015. Name and references of the hosting laboratory and/or the external institution (University, Research Centre, Private Company etc.): University of Genoa, DIBRIS Contacts (name, phone, email, skype..): Manuela Chessa, +39 010 353 2289, [email protected] Fabio Solari, +39 010 353 2059, [email protected]
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