computer vision laboratory december 20, 2015the cospal project1 michael felsberg computer vision...
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April 21, 2023 The COSPAL Project 1
Computer Vision Laboratory
The COSPAL Project
Michael FelsbergComputer Vision Laboratory
Linköping UniversitySWEDEN
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Computer Vision Laboratory
Fact Sheet
• COSPAL acronym:COgnitiveSystems using Perception-Action Learning
• STREP IST-2003-004176
• Project Start:1. July 2004
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Computer Vision Laboratory
ConsortiumLinköping University, SwedenComputer Vision Laboratory (coordinator)Gösta GranlundChristian-Albrechts-University of Kiel, GermanyCognitive SystemsGerald SommerUniversity of Surrey, UKCentre for Vision, Speech, & Signal ProcessingVaclav HlavacCzech Technical University in Prague, Czech RepublicCenter for Machine PerceptionJosef Kittler
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Consortium
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Objectives
• Architectures for autonomous robots with cognitive capabilities
• Vision based systems
• Stationary manipulator
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Feature input Output
Scenedescription
Actiongeneration
Approach
• Action precedes perception • Incremental learning and exploration• Bidirectional interface to reasoning unit
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Early Demonstrator
• Parallel progress in WPs
• Concentrate on architectural aspect
• Fully automatic learning and evaluation
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Final Demonstrator I
• Embedding into ‘real’ world
• Scalability of the architecture
• Stability and robustness
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QuickTime™ and aYUV420 codec decompressor
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Final Demonstrator II
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Just a toy example?
Fact: this scenario can ‘easily’ be solvedby a traditional system design.
• Is it robust?
• Can it generalize?
• Is it scalable?
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Robustness/Generalization
?
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Challenge of COSPAL
… is NOT to solve the puzzle problem
… is NOT to do model registration and fitting
… but to develop a system architecture whichis able to semi-autonomously,step-by-step build up knowledgeand solution strategies
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Architecture
• Homogeneous network structures• Localized representations (channels)• Associations between channels to be learned
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Hardware
• PCs• Firewire cameras• RX90• 3D turntable
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Software & Interfaces
• Heterogeneous code modules:– C++– Matlab– Python
• Loosely coupled processes– Controlling process– XML files– Exception: servoing (PVM)
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Summary
• Autonomous cognitive system– Action-precedes-perception learning– Bidirectional interface to symbolic unit– Incremental learning at all levels
• Demonstrator as proof of architecture
• Architectural building blocks for systems in more serious applications