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Cognitive Systems Foresight 3D Vision. Cognitive Systems Foresight 3D Vision What are the potential implications of computer vision research for the study.

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Presentation on theme: "Cognitive Systems Foresight 3D Vision. Cognitive Systems Foresight 3D Vision What are the potential implications of computer vision research for the study."— Presentation transcript:

1 Cognitive Systems Foresight 3D Vision

2 Cognitive Systems Foresight 3D Vision What are the potential implications of computer vision research for the study of biological vision, in areas other than 3D perception? Is it viewpoint recognition or object recognition? Pose the question the other way – how cognitive systems can help computer vision, computer systems not robust yet Biological vision has informed computer vision in the area of “salience” (e.g. research by Koch lab) Selecting amongst multiple models (c.f. data fusion) Importance of context in object recognition, connections with model selection in computer systems, attention switching in biological systems

3 Cognitive Systems Foresight 3D Vision More generally, what are the potential influences from the study of computational cognitive systems on the study of biological ones? Experimental challenges, multi-modal perception (dolphins use both sight and echo location). Need to work on both biological systems and engineering systems in parallel Desire to work on both simple focused problems and multi-tasking situations Dave Cliff - no general purpose vision systems in nature – are animal specific, function dictated by requirements in nature (maybe no general principles underlying different animal vision systems). Gabriel Horn – there are some general principles underlying animal systems Neuroscientists need to look towards computer scientists working on problems which are not well understood in biology (e.g. speech & language processing)

4 Cognitive Systems Foresight 3D Vision What are the potential applications for society of the study of biological or computational vision systems? The integration of vision with robotic control remains a significant target Homeland security and surveillance – tracking large numbers of people moving around say an airport or a system (implications for public policy of large-scale surveillance) Work on space-time trajectories of people walking through a car-park, criminals have statistically different trajectories compared to honest citizens Higher level interpretation of scenes – still a lot of work to do in this area (applications in CCTV etc) Study of biological vision will aid autonomous robotics. Many cases animals ensure robustness by using multiple systems operating in parallel (trade-off time against accuracy).


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