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07 history of cv vision paradigms - system - algorithms - applications - evaluation

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zukun

This document outlines the history of computer vision from the 1960s to present day through a graph-based structure. It covers early paradigms in areas like pattern recognition and image processing in the 1970s. Artificial intelligence approaches emerged in the 1970s including systems like SHRDLU. Vision research in the 1980s focused on areas like image understanding, expert systems, and reasoning. Robotics became an important application area from the 1990s onward, with a focus on learning and interaction. Current computer vision systems, libraries and toolboxes build upon these historical paradigms, systems and algorithms.

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Institute of Electrical Measurement and Measurement Signal Processing VISION: • Paradigms • Systems Axel Pinz • Algorithms • Applications • Evaluation A Graph-based structure ! History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 1
Institute of Electrical Measurement and Measurement Signal Processing The Graph of Vision History Systems Image Understanding 1978 1980s Artificial Intelligence 1971 Pattern Recognition Image Proc. 1970s Cognitive Psychology 1985 ? Neurophysiology 1963 Algorithms 1962 Marr Robotics 1978 1994 ? Recognition R iti 1970s Reconstruction R+R 1980 ? 1990 History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 2
Institute of Electrical Measurement and Measurement Signal Processing Artificial Intelligence • SHRDLU [Winograd 1971] • Blocks world original screen di l (MIT AI Lab) i i l display L b) later l l t color rendering (U i Ut h) d i (Univ. Utah) History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 3
Institute of Electrical Measurement and Measurement Signal Processing Blocks World – 1970s • Natural language understanding • Spatio-temporal reasoning • LISP • Visual input would be nice • Vi i as an “ Vision “enabling sensory module” i AI bli d l ” in – Patrick Henry Winston “The Psychology of Computer Vision” 1975 – M i Mi k “A framework for representing k Marvin Minsky f kf ti knowledge” 1975 l d ” • Frames • Frame Representation Language FRL g g History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 4
Institute of Electrical Measurement and Measurement Signal Processing Blocks World – Today • Still an issue of ongoing research research… • EU FP 6 project MACS • 2004 2008 2004-2008 Learning ! “Affordances” … Affordances History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 5
Institute of Electrical Measurement and Measurement Signal Processing AI Methods for Vision – 1980s • “Image Understanding” • Expert systems – SIGMA Aerial Image Understanding – Matsuyama Hwang … Matsuyama, Hwang, • Reasoning, Blackboard system – VISIONS, Draper, OHM, … • Schema learning g – SLS, Draper,… History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 6
Institute of Electrical Measurement and Measurement Signal Processing SIGMA [Matsuyama] History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 7
Institute of Electrical Measurement and Measurement Signal Processing VISIONS [Hanson+Riseman], SLS [Draper] A Massachusetts “road”-scene History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 8
Institute of Electrical Measurement and Measurement Signal Processing “Image Understanding” – 1980s • Integrating bottom-up and top-down p processes combinatorial explosion p • “knowledge engineers”, hand-crafted knowledge-base knowledge base learning is a must History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 9
Institute of Electrical Measurement and Measurement Signal Processing Systems 1990 – 200+ • “Computer Vision Systems” – [Hanson+Riseman 1978] • UMass VISIONS KBVision – AAI Amerinex Artificial intelligence – AAI Amerinex Applied Imaging • Gi Grimson Cognex C – PatMax • Matlab • OpenCV • IUE • toolboxes, libraries – TargetJr Joe Mundy g y History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 10
Institute of Electrical Measurement and Measurement Signal Processing Robotics • B k “building b i f b di ” Brooks: “b ildi brains for bodies” – Autonomous Robots 1:7-25, 1994 • Learning! • Interaction! • Reward by survival…! • Active, purposive, qualitative – Bajcsy 1988 – Aloimonos 1989 History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 11
Institute of Electrical Measurement and Measurement Signal Processing Babybot – Lira Lab [Sandini] learning to p g push learnt Babybot’s view History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 12
Institute of Electrical Measurement and Measurement Signal Processing Neurophysiology • Retina visual cortex • Layered representation in visual cortex • Receptive fields • Hubel+Wiesel – Gradients – Oriented “edgels” – At various scales – Bottom-up grouping recognition – Visual pathway p y stereo, reconstruction , History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 13
Institute of Electrical Measurement and Measurement Signal Processing Visual Pathway [Hubel+Wiesel] History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 14
Institute of Electrical Measurement and Measurement Signal Processing Receptive Fields [Hubel+Wiesel] on off on-off simple complex History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 15
Institute of Electrical Measurement and Measurement Signal Processing Pattern Recognition + Image Processing – PRIP • Structural [Pavlidis 1972, Fu 1982] • Statistical [Fukunaga 1990] • R Representation ( t ti (regular, i l irregular, scale,…) l l ) pyramids, scale space, graphs,… • Feature sets, feature selection, classifiers, learning,… • 2D (discrete) signal processing History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 16
Institute of Electrical Measurement and Measurement Signal Processing Maximum Likelihood Classification History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 17
Institute of Electrical Measurement and Measurement Signal Processing Scale Space [Lindeberg] Space + time [Laptev + Lindeberg] History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 18
Institute of Electrical Measurement and Measurement Signal Processing Cognitive Psychology • Perceptual grouping – Lowe 1985 – Sarkar 1994 – LLVE Matsuyama • Qualitative volumetric models (Geons) – Biederman 1985 Bergevin+Levine 1988 1985, – Dickinson 1992: Aspect Hierarchy • A renaissance i t d ’ shape models f i in today’s h d l for category detection… History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 19
Institute of Electrical Measurement and Measurement Signal Processing My Favorite Example [Lowe] Very hard !!! History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 20
Institute of Electrical Measurement and Measurement Signal Processing My Favorite Example [Lowe] Very easy !!! History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 21
Institute of Electrical Measurement and Measurement Signal Processing Geons [Biederman], Aspect Hierarchy [Dickinson] History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 22
Institute of Electrical Measurement and Measurement Signal Processing Geons [Biederman], Aspect Hierarchy [Dickinson] History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 23
Institute of Electrical Measurement and Measurement Signal Processing The Marr Paradigm – 1978-? • Systems approach to vision computational model – Algorithm, data, hardware implementation g , , p – Low level modules • Representational levels – P i l sketch Primal k t h saliency li – 2-1/2 D reconstruction ! – 3D object model is it really required? • “reconstruction school” • “visual modules”, “shape from X” • Zerroug 1994 • Structure + Motion 200x History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 24
Institute of Electrical Measurement and Measurement Signal Processing Marr (~1978) – “primal sketch” “saliency” ! “Harris” corners Harris History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 25
Institute of Electrical Measurement and Measurement Signal Processing Marr (~1978) – “2-1/2-D sketch”, “generalized cone 2 1/2 D sketch , generalized cone” History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 26
Institute of Electrical Measurement and Measurement Signal Processing Marr (~1978) – 3D hierarchical models History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 27
Institute of Electrical Measurement and Measurement Signal Processing Marr ~1978, Aloimonos ~1988 “robustness” History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 28
Institute of Electrical Measurement and Measurement Signal Processing Zerroug 1994 History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 29
Institute of Electrical Measurement and Measurement Signal Processing Algorithms • Convolution kernels • Mathematical morphology structuring elements Serra • Fourier transform spectrum, phase, descriptors, Gabor filter bank • Hough t H h transform f voting space ti • PCA • Pyramids (regular, irregular) graphs • Scale space theory in CV Lindeberg • Algebraic projective geometry Hartley, Zisserman • Color (good chapters in Forsyth+Ponce, Burger+Burge) (g p y , g g ) • Texture invariant moments (Hu … Haralick … VanGool) • Interest point detection (Schmid, …) affine covariance • Pattern Classification Duda+Hart Duda Hart • Machine Learning Hastie et al. History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 30
Institute of Electrical Measurement and Measurement Signal Processing Reconstruction • Projective P j ti geometry t • Photogrammetry g y • Essential, fundamental, multiview, … • Calibrated, uncalibrated, autocalibration, Calibrated uncalibrated autocalibration calibration-free,… • St t Structure and Motion d M ti History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 31
Institute of Electrical Measurement and Measurement Signal Processing Structure and motion [Schweighofer 2008] [ g ] History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 32
Institute of Electrical Measurement and Measurement Signal Processing Recognition • S Specific objects ifi bj t – PCA [Murase+Nayar 95], Eigenfaces [Pentland 93] • Categories – Generative [Fergus 2003], discriminative [Opelt 2004] • Recognition vs localization vs. • Features (descriptors), grouping – Shape texture, color proximity similarity Shape, texture color, proximity, similarity,… • Saliency (detectors) • Active – Motion, space+time … History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 33
Institute of Electrical Measurement and Measurement Signal Processing Shape-Based Category Detection [Opelt 2006] History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 34
Institute of Electrical Measurement and Measurement Signal Processing “R + R”: Confluence of R R : Recognition and Reconstruction • “ “recognition and reconstruction schools will merge” iti d t ti h l ill ” [Aloimonos+Shulman 1989] • “Marr paradigm – use of 2-1/2D complicates the problem” Marr 2 1/2D problem [Medioni et al. 2000] tensor voting • Spatio-temporal reasoning and representation History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 35
Institute of Electrical Measurement and Measurement Signal Processing The Graph of Vision History Systems Image Understanding 1990s 1980s Artificial Intelligence 1971 Pattern Recognition Image Proc. 1970s Cognitive Psychology 1985 ? Neurophysiology 1963 Algorithms 1962 Marr Robotics 1978 1994 ? Recognition R iti 1970s Reconstruction R+R 1980 ? 1990 History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 36

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07 history of cv vision paradigms - system - algorithms - applications - evaluation

  • 1. Institute of Electrical Measurement and Measurement Signal Processing VISION: • Paradigms • Systems Axel Pinz • Algorithms • Applications • Evaluation A Graph-based structure ! History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 1
  • 2. Institute of Electrical Measurement and Measurement Signal Processing The Graph of Vision History Systems Image Understanding 1978 1980s Artificial Intelligence 1971 Pattern Recognition Image Proc. 1970s Cognitive Psychology 1985 ? Neurophysiology 1963 Algorithms 1962 Marr Robotics 1978 1994 ? Recognition R iti 1970s Reconstruction R+R 1980 ? 1990 History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 2
  • 3. Institute of Electrical Measurement and Measurement Signal Processing Artificial Intelligence • SHRDLU [Winograd 1971] • Blocks world original screen di l (MIT AI Lab) i i l display L b) later l l t color rendering (U i Ut h) d i (Univ. Utah) History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 3
  • 4. Institute of Electrical Measurement and Measurement Signal Processing Blocks World – 1970s • Natural language understanding • Spatio-temporal reasoning • LISP • Visual input would be nice • Vi i as an “ Vision “enabling sensory module” i AI bli d l ” in – Patrick Henry Winston “The Psychology of Computer Vision” 1975 – M i Mi k “A framework for representing k Marvin Minsky f kf ti knowledge” 1975 l d ” • Frames • Frame Representation Language FRL g g History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 4
  • 5. Institute of Electrical Measurement and Measurement Signal Processing Blocks World – Today • Still an issue of ongoing research research… • EU FP 6 project MACS • 2004 2008 2004-2008 Learning ! “Affordances” … Affordances History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 5
  • 6. Institute of Electrical Measurement and Measurement Signal Processing AI Methods for Vision – 1980s • “Image Understanding” • Expert systems – SIGMA Aerial Image Understanding – Matsuyama Hwang … Matsuyama, Hwang, • Reasoning, Blackboard system – VISIONS, Draper, OHM, … • Schema learning g – SLS, Draper,… History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 6
  • 7. Institute of Electrical Measurement and Measurement Signal Processing SIGMA [Matsuyama] History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 7
  • 8. Institute of Electrical Measurement and Measurement Signal Processing VISIONS [Hanson+Riseman], SLS [Draper] A Massachusetts “road”-scene History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 8
  • 9. Institute of Electrical Measurement and Measurement Signal Processing “Image Understanding” – 1980s • Integrating bottom-up and top-down p processes combinatorial explosion p • “knowledge engineers”, hand-crafted knowledge-base knowledge base learning is a must History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 9
  • 10. Institute of Electrical Measurement and Measurement Signal Processing Systems 1990 – 200+ • “Computer Vision Systems” – [Hanson+Riseman 1978] • UMass VISIONS KBVision – AAI Amerinex Artificial intelligence – AAI Amerinex Applied Imaging • Gi Grimson Cognex C – PatMax • Matlab • OpenCV • IUE • toolboxes, libraries – TargetJr Joe Mundy g y History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 10
  • 11. Institute of Electrical Measurement and Measurement Signal Processing Robotics • B k “building b i f b di ” Brooks: “b ildi brains for bodies” – Autonomous Robots 1:7-25, 1994 • Learning! • Interaction! • Reward by survival…! • Active, purposive, qualitative – Bajcsy 1988 – Aloimonos 1989 History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 11
  • 12. Institute of Electrical Measurement and Measurement Signal Processing Babybot – Lira Lab [Sandini] learning to p g push learnt Babybot’s view History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 12
  • 13. Institute of Electrical Measurement and Measurement Signal Processing Neurophysiology • Retina visual cortex • Layered representation in visual cortex • Receptive fields • Hubel+Wiesel – Gradients – Oriented “edgels” – At various scales – Bottom-up grouping recognition – Visual pathway p y stereo, reconstruction , History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 13
  • 14. Institute of Electrical Measurement and Measurement Signal Processing Visual Pathway [Hubel+Wiesel] History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 14
  • 15. Institute of Electrical Measurement and Measurement Signal Processing Receptive Fields [Hubel+Wiesel] on off on-off simple complex History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 15
  • 16. Institute of Electrical Measurement and Measurement Signal Processing Pattern Recognition + Image Processing – PRIP • Structural [Pavlidis 1972, Fu 1982] • Statistical [Fukunaga 1990] • R Representation ( t ti (regular, i l irregular, scale,…) l l ) pyramids, scale space, graphs,… • Feature sets, feature selection, classifiers, learning,… • 2D (discrete) signal processing History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 16
  • 17. Institute of Electrical Measurement and Measurement Signal Processing Maximum Likelihood Classification History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 17
  • 18. Institute of Electrical Measurement and Measurement Signal Processing Scale Space [Lindeberg] Space + time [Laptev + Lindeberg] History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 18
  • 19. Institute of Electrical Measurement and Measurement Signal Processing Cognitive Psychology • Perceptual grouping – Lowe 1985 – Sarkar 1994 – LLVE Matsuyama • Qualitative volumetric models (Geons) – Biederman 1985 Bergevin+Levine 1988 1985, – Dickinson 1992: Aspect Hierarchy • A renaissance i t d ’ shape models f i in today’s h d l for category detection… History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 19
  • 20. Institute of Electrical Measurement and Measurement Signal Processing My Favorite Example [Lowe] Very hard !!! History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 20
  • 21. Institute of Electrical Measurement and Measurement Signal Processing My Favorite Example [Lowe] Very easy !!! History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 21
  • 22. Institute of Electrical Measurement and Measurement Signal Processing Geons [Biederman], Aspect Hierarchy [Dickinson] History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 22
  • 23. Institute of Electrical Measurement and Measurement Signal Processing Geons [Biederman], Aspect Hierarchy [Dickinson] History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 23
  • 24. Institute of Electrical Measurement and Measurement Signal Processing The Marr Paradigm – 1978-? • Systems approach to vision computational model – Algorithm, data, hardware implementation g , , p – Low level modules • Representational levels – P i l sketch Primal k t h saliency li – 2-1/2 D reconstruction ! – 3D object model is it really required? • “reconstruction school” • “visual modules”, “shape from X” • Zerroug 1994 • Structure + Motion 200x History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 24
  • 25. Institute of Electrical Measurement and Measurement Signal Processing Marr (~1978) – “primal sketch” “saliency” ! “Harris” corners Harris History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 25
  • 26. Institute of Electrical Measurement and Measurement Signal Processing Marr (~1978) – “2-1/2-D sketch”, “generalized cone 2 1/2 D sketch , generalized cone” History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 26
  • 27. Institute of Electrical Measurement and Measurement Signal Processing Marr (~1978) – 3D hierarchical models History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 27
  • 28. Institute of Electrical Measurement and Measurement Signal Processing Marr ~1978, Aloimonos ~1988 “robustness” History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 28
  • 29. Institute of Electrical Measurement and Measurement Signal Processing Zerroug 1994 History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 29
  • 30. Institute of Electrical Measurement and Measurement Signal Processing Algorithms • Convolution kernels • Mathematical morphology structuring elements Serra • Fourier transform spectrum, phase, descriptors, Gabor filter bank • Hough t H h transform f voting space ti • PCA • Pyramids (regular, irregular) graphs • Scale space theory in CV Lindeberg • Algebraic projective geometry Hartley, Zisserman • Color (good chapters in Forsyth+Ponce, Burger+Burge) (g p y , g g ) • Texture invariant moments (Hu … Haralick … VanGool) • Interest point detection (Schmid, …) affine covariance • Pattern Classification Duda+Hart Duda Hart • Machine Learning Hastie et al. History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 30
  • 31. Institute of Electrical Measurement and Measurement Signal Processing Reconstruction • Projective P j ti geometry t • Photogrammetry g y • Essential, fundamental, multiview, … • Calibrated, uncalibrated, autocalibration, Calibrated uncalibrated autocalibration calibration-free,… • St t Structure and Motion d M ti History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 31
  • 32. Institute of Electrical Measurement and Measurement Signal Processing Structure and motion [Schweighofer 2008] [ g ] History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 32
  • 33. Institute of Electrical Measurement and Measurement Signal Processing Recognition • S Specific objects ifi bj t – PCA [Murase+Nayar 95], Eigenfaces [Pentland 93] • Categories – Generative [Fergus 2003], discriminative [Opelt 2004] • Recognition vs localization vs. • Features (descriptors), grouping – Shape texture, color proximity similarity Shape, texture color, proximity, similarity,… • Saliency (detectors) • Active – Motion, space+time … History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 33
  • 34. Institute of Electrical Measurement and Measurement Signal Processing Shape-Based Category Detection [Opelt 2006] History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 34
  • 35. Institute of Electrical Measurement and Measurement Signal Processing “R + R”: Confluence of R R : Recognition and Reconstruction • “ “recognition and reconstruction schools will merge” iti d t ti h l ill ” [Aloimonos+Shulman 1989] • “Marr paradigm – use of 2-1/2D complicates the problem” Marr 2 1/2D problem [Medioni et al. 2000] tensor voting • Spatio-temporal reasoning and representation History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 35
  • 36. Institute of Electrical Measurement and Measurement Signal Processing The Graph of Vision History Systems Image Understanding 1990s 1980s Artificial Intelligence 1971 Pattern Recognition Image Proc. 1970s Cognitive Psychology 1985 ? Neurophysiology 1963 Algorithms 1962 Marr Robotics 1978 1994 ? Recognition R iti 1970s Reconstruction R+R 1980 ? 1990 History of Computer Vision Paradigms-Systems-Algorithms-Applications-Evaluation Professor Horst Cerjak, 19.12.2005 Axel Pinz 9.5.2008 36