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1 Neuromath kickoff meeting 2009-01-23 É. Tlapale 1, G.S. Masson 2, P. Kornprobst 1 1 : Équipe Odyssée (INRIA, ENS, INPC) 2 : Équipe DyVA (INCM/CNRS)

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Presentation on theme: "1 Neuromath kickoff meeting 2009-01-23 É. Tlapale 1, G.S. Masson 2, P. Kornprobst 1 1 : Équipe Odyssée (INRIA, ENS, INPC) 2 : Équipe DyVA (INCM/CNRS)"— Presentation transcript:

1 1 Neuromath kickoff meeting É. Tlapale 1, G.S. Masson 2, P. Kornprobst 1 1 : Équipe Odyssée (INRIA, ENS, INPC) 2 : Équipe DyVA (INCM/CNRS)

2 2 Current work We design a bio-inspired model of motion integration. – Functional model (V1/MT) – Feedbacks (MT => V1) – Form modulation (V2) Why ? – To reproduce motion perception – And its dynamic

3 3 Influence of form Chopstick illusions

4 4 Influence of form Chopstick illusions

5 5 Influence de la forme Jonctions intrinsèques vs extrinsèques

6 6 Multi-layer feedback model Input : grey-level sequence

7 7 Multi-layer feedback model Local motion detectors: correlation or energy models

8 8 Multi-layer feedback model

9 9 Lateral inhibition => winner-take-all

10 10 Un modèle multi-couche rétroactif Feedback (Bayerl & Neumann, 2004)

11 11 Multi-layer feedback model Anisotropic diffusion

12 12 Form-modulated diffusion We only use luminosity for now

13 13 Reproducing the perception Wallach (1935)

14 14 Wallace, Stone et Masson (2005) Reproducing the dynamic Eye-movement like read-out

15 15 Reproducing the neurobiology Huang, Albright et Stoner (2007) Notion of objects

16 16 Future work Reformulate our model in a neural field formalism And using a multi-layer variational formalism Propose our form-motion interaction as a synchronisation mechanism

17 17 Journal clubs Biology: Barthelemy et al. (2008) Models: Cesmely & Wang (2000) Technologies: Python, GPGPU


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