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The Hilbert Problems of Computer Vision

The Hilbert Problems of Computer Vision. Jitendra Malik. Forty years of computer vision 1963-2003. 1960s: Beginnings in artificial intelligence, image processing and pattern recognition 1970s: Foundational work on image formation: Horn, Koenderink, Longuet-Higgins …

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The Hilbert Problems of Computer Vision

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  1. The Hilbert Problems of Computer Vision Jitendra Malik

  2. Forty years of computer vision 1963-2003 • 1960s: Beginnings in artificial intelligence, image processing and pattern recognition • 1970s: Foundational work on image formation: Horn, Koenderink, Longuet-Higgins … • 1980s: Vision as applied mathematics: geometry, multi-scale analysis, control theory, optimization … • 1990s: • Geometric analysis largely completed • Probabilistic/Learning approaches in full swing • Successful applications in graphics, biometrics, HCI …

  3. And now … • Back to basics: the classic problem of understanding the scene from its image/s • Central question: Interplay of bottom-up and top-down information

  4. Early Vision • What can we learn from image statistics that we didn't know already? • How far can bottom-up image segmentation go? • How do we make inferences from shading and texture patterns in natural images?

  5. Static Scene Understanding • What is the interaction between segmentation and recognition? • What is the interaction between scenes, objects, and parts? • What is the role of design vs. learning in recognition systems?

  6. Dynamic Scene Understanding • What is the role of high-level knowledge in long range motion correspondence? • How do we find and track articulated structures? • How do we represent "movemes" and actions?

  7. From Images to Objects "I stand at the window and see a house, trees, sky. Theoretically I might say there were 327 brightnesses and nuances of colour. Do I have "327"? No. I have sky, house, and trees." --Max Wertheimer

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