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Robust Vision for Vision-Based Control of Motion

Markus Vincze (Editor), Gregory D. Hager (Editor)
ISBN: 978-0-7803-5378-7
262 pages
February 2000, Wiley-IEEE Press
Robust Vision for Vision-Based Control of Motion (0780353781) cover image
Find the design principles you need to move vision-based control out of the lab and into the real world. In this edited collection of state-of-the-art papers, contributors highly regarded in robust vision bring you the latest applications in the field. Whatever your industry - from space ventures to mobile surveillance - you will discover throughout this comprehensive collection a strong emphasis on robust vision simply unmatched today. You will also gain an in-depth analysis of vision techniques used to control the motion of robots and machines.

Expert contributors offer you key insights into:

  • Current control issues including hardware design, system architecture, sensor data fusion, and visual tracking
  • Modeling methods for vision-based sensing
  • Useful summaries of recent conclusions drawn from robust-vision workshops
  • Future research needs

If you want to learn today's approaches to robust vision-based control of motion, this extensive collection is a must. Learn from the experts and, in the process, speed your project development and broaden your technical expertise for future collaborative efforts in your industry.

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PREFACE.

LIST OF CONTRIBUTORS.

CHAPTER 1 CUE INTEGRATION FOR MANIPULATION (D. Kragic and H. I. Christensen).

1.1 Introduction.

1.2 Cue Integration.

1.3 Cues for Visual Servoing.

1.4 System Outline.

1.5 Evaluation.

1.6 Summary.

1.7 Acknowledgments.

CHAPTER 2 SPATIALLY ADAPTIVE FILTERING IN A MODELBASED MACHINE VISION APPROACH TO ROBUST WORKPIECE TRACKING (H.-H. Nagel, Th. MCiller, V. Gengenbach, and A Gehrke).

2.1 Introduction.

2.2 Specification of Problem and Boundary Conditions.

2.3 Solution Approach to Be Investigated.

2.4 Results.

2.5 Discussion and Outlook.

CHAPTER 3 INCREMENTAL FOCUS OF ATTENTION: A LAYERED APPROACH TO ROBUST VISION AND CONTROL (Kentaro Toyama, Gregory D. Hager, and Zachary Dodds).

3.1 Introduction.

3.2 Robust Tracking.

3.3 Action Prohibition in Robot Control.

3.4 Examples.

3.5 Related Work.

3.6 Discussion.

3.7 Acknowledgments.

CHAPTER 4 INTEGRATED OBJECT MODELS FOR ROBUST VISUAL TRACKING (Kevin Nickels and Seth Hutchinson).

4.1 Introduction.

4.2 Models.

4.3 Observation Function.

4.4 Feature Tracking.

4.5 Extended Kalman Filter.

4.6 Experimental Results.

4.7 Conclusions.

CHAPTER 5 ROBUST VISUAL TRACKING BY INTEGRATING VARIOUS CUES (Yoshiaki Shirai, Ryuzo Okada, and Tsuyoshi Yamane).

5.1 Introduction.

5.2 Optical Flow Extraction.

5.3 Tracking with Optical Flow.

5.4 Tracking Two Persons.

5.5 Tracking with Optical Flow and Depth.

5.6 Tracking with Optical Flow and Uniform Brightness Regions.

5.7 Conclusion.

CHAPTER 6 TWO-DIMENSIONAL MODEL-BASED TRACKING OF COMPLEX SHAPES FOR VISUAL SERVOING TASKS (Nathalie Giordana, Patrick Bouthemy, Frangois Chaumette, and Fabien Spindler).

6.1 Introduction.

6.2 Specification of the Homing Task.

6.3 Semi-Automatic Initialization.

6.4 Two-Dimensional Tracking of Polyhedral Object.

6.5 Experimental Results.

6.6 Conclusions.

6.7 Acknowledgments.

CHAPTER 7 INTERACTION OF PERCEPTION AND CONTROL FOR INDOOR EXPLORATION (D. Burschka, C. Eberst, C. Robl, and G. Farber).

7.1 Introduction.

7.2 Concept.

7.3 Sensor Data Preprocessing.

7.4 Interpretation.

7.5 Sensor and Platform Control.

7.6 Results.

7.7 Conclusion.

7.8 Acknowledgment.

CHAPTER 8 REAL-TIME IMAGE PROCESSING FOR IMAGEBASED VISUAL SERVOING (Patrick Rives and Jean-Jacques Borrelly).

8.1 Introduction.

8.2 Image-Based Visual Servoing Requirements.

8.2.1 Building an Application.

8.3 Application to a Pipe Inspection Task.

8.4 Conclusion.

CHAPTER 9 PROVEN TECHNIQUES FOR ROBUST VISUAL SERVO CONTROL (K. Arbter, G. Hirzinger, J. Langwald, G.-Q. Wei, and R Wunsch).

9.1 Introduction.

9.2 Robust Feature Extraction.

9.3 Model-Based Handling of Occlusion.

9.4 Multisensory Servoing.

9.5 Conclusion.

CHAPTER 10 GLOBAL SIGNATURES FOR ROBOT CONTROL AND RECONSTRUCTION (R. A. Hicks, D. J. Pettey, K. S. Daniilidis, and R. Bajcsy).

10.1 Introduction.

10.2 Applications to Robotics.

10.3 Calculating Signatures.

10.4 Simulation Results.

10.5 Conclusion.

CHAPTER 11 USING FOVEATED VISION FOR ROBUST OBJECT TRACKING: THREE-DIMENSIONAL HOROPTER ANALYSIS (Naoki Oshiro, Atsushi Nishikawa, and Fumio Miyazaki).

11.1 Introduction.

11.2 Preliminaries.

11.3 Horopter Analysis.

11.4 Concluding Remarks.

CHAPTER 12 EVALUATION OF THE ROBUSTNESS OF VISUAL BEHAVIORS THROUGH PERFORMANCE CHARACTERIZATION (Joao P Barreto, Paulo Peixoto, Jorge Batista, and Helder Araujo).

12.1 Introduction.

12.2 Control of the MDOF Binocular Tracking System.

12.3 Reference Trajectories Generation Using Synthetic Images.

12.4 Reference Trajectories Equations.

12.5 System Response to Motion.

12.6 Improvements in the Visual Processing.

12.7 Motor Performance and Global System Behavior.

12.8 Improvements in Global Performance--Experimental Results.

12.9 Summary and Conclusions.

CHAPTER 13 ROBUST IMAGE PROCESSING AND POSITIONBASED VISUAL SERVOING (W. J. Wilson, C. C. Williams Hulls, and F. Janabi-Sharifi).

13.1 Introduction.

13.2 Position-Based Visual Servoing and Image Processing.

13.3 Directed Image Processing and Adaptive Windowing.

13.4 Feature Planning and Selection.

13.5 Information Redundancy and Sensor Integration.

13.6 Conclusions.

CHAPTER 14 VISION-BASED OBJECTIVE SELECTION FOR ROBUST BALLISTIC MANIPULATION (Bradley E. Bishop, and Mark W. Spong).

14.1 Introduction.

14.2 Visual Measurement Scheme.

14.3 State Estimation and Prediction.

14.4 Air Hockey.

14.5 Conclusions and Future Work.

14.6 Acknowledgments.

CHAPTER 15 VISION-BASED AUTONOMOUS HELICOPTER RESEARCH AT CARNEGIE MELLON ROBOTICS INSTITUTE (1991-1998) (Omead Amidi, Takeo Kanade, and Ryan Miller).

15.1 Introduction.

15.2 Goals.

15.3 Capabilities.

15.4 Future Work.

INDEX.

ABOUT THE EDITORS.

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Markus Vincze is head of a research group at the Vienna University of Technology, Austria, and leads European research projects. Project RobVision uses vision to navigate a walking robot through the sections of a large container vessel for welding and inspection tasks. His research interests are in the areas of service robotics, robust and reliable visual sensing, and control.

Gregory D. Hager is a professor of computer science at Johns Hopkins University. He currently serves as cochairman of the Robotics and Automation Society Technical Committee on Computer and Robot Vision. Dr. Hager is the author of Task-Directed Sensor Fusion and Planning (Kluwer Academic Publishers, 1990) and coeditor of The Confluence of Vision and Control (Springer-Verlag, 1998). His research interests include visual tracking, hand-eye coordination, human-computer interaction, sensor data fusion, and sensor planning.

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