Exploratory Vision

I Active Human Vision.- 1 Moveo Ergo Video: Natural Retinal Image Motion and its Effect on Vision.- 1.1 Prologue.- 1.2 Introduction.- 1.3 Relation Between Eye Movement and Visual Acuity Circa 1900.- 1.4 The Marshall-Talbot Dynamic Theory of Visual Acuity.- 1.5 Empirical Tests of the Marshall-Talbot Theory.- 1.6 The Phone Rang.- 1.7 The Phone Rang Again.- 1.8 Retinal Image Slip Following Adaptation of the VOR.- 1.9 An Intramural Phone Call.- 1.10 References.- 2 Cogito Ergo Moveo: Cognitive Control of Eye Movement.- 2.1 Introduction.- 2.2 Example 1: Selection of the Target for Smooth Eye Movements.- 2.2.1 Smooth eye movements in the presence of visual backgrounds.- 2.2.2 The role of selective attention.- 2.3 Example 2: Predicting the Future Position of Targets.- 2.3.1 The effect of expectations on smooth eye movements.- 2.3.2 Past history vs. cognitive expectations of future target motion.- 2.4 Example 3: Planning Sequences of Saccades.- 2.5 Example 4: Saccades to Selected Targets in the Presence of Irrelevant Visual Backgrounds.- 2.6 Summary and Conclusions.- 2.7 References.- II Solving Visual Problems.- 3 Robust Computational Vision.- 3.1 Introduction.- 3.2 Vision Problems.- 3.3 Vision Methods.- 3.4 Robust Methods.- 3.5 Applications.- 3.5.1 Surface reconstruction.- 3.5.2 Image flow.- 3.5.3 Dynamic stereo.- 3.6 Discussion.- 3.6.1 Comparison with other paradigms.- 3.6.2 Improving performance.- 3.6.3 Computational resources.- 3.6.4 Further work.- 3.7 References.- 4 Eye Movements and the Complexity of Visual Processing.- 4.1 Introduction.- 4.2 Visual Task Performance.- 4.2.1 Detection.- 4.2.2 Masking.- 4.2.3 Localization.- 4.2.4 Multidimensional tasks.- 4.2.5 Speed-accuracy tradeoff.- 4.3 Task Complexity.- 4.3.1 Theory of complexity.- 4.3.2 Capacity of constrained parallel machines.- 4.3.3 Sequential machines.- 4.3.4 Theoretical speed-accuracy tradeoff.- 4.4 Translation Invariance.- 4.5 Conclusion.- 4.6 References.- 5 Exploratory Vision: Some Implications for Retinal Sampling and Reconstruction.- 5.1 Introduction.- 5.2 From Scene to Sensor to Code.- 5.3 Linear Reconstruction and the Sampling Theorem.- 5.4 Linear Reconstruction and Aliasing.- 5.5 Nonlinear Constraints on Possible Images.- 5.6 Irregular Sampling Arrays and Aliasing.- 5.7 Linear Reconstruction and Movement.- 5.8 Linear Reconstruction with Multiple Sampling Arrays.- 5.9 Ideal Arrays.- 5.10 Visual Representation and Transformational Constancy.- 5.11 Conclusion.- 5.12 References.- 6 Calibration of a Visual System with Receptor Drop-out.- 6.1 Introduction.- 6.1.1 Retinal degeneration and bisection judgments.- 6.1.2 Cone position calibration models.- 6.2 The Learning Algorithms.- 6.2.1 The visual system model.- 6.2.2 The delta rule.- 6.2.3 The TI rule.- 6.2.4 Inadequate sampling.- 6.2.5 A new rule.- 6.2.6 A final example.- 6.3 Discussion.- 6.3.1 Known translations.- 6.3.2 The interpolated image.- 6.3.3 Two views from two eyes.- 6.3.4 Partial damage.- 6.4 Conclusions.- 6.5 References.- 7 Peripheral Visual Field, Fixation and Direction of Heading.- 7.1 Introduction.- 7.2 Retinal Flow in a Rigid 2-D Universe.- 7.2.1 Calculating retinal flow.- 7.2.2 Level sets of retinal flow.- 7.3 Retinal Flow in a Rigid 3-D Universe.- 7.3.1 Calculating retinal flow.- 7.3.2 Points with zero flow in the 3-D universe.- 7.4 Latitudinal and Longitudinal Flow.- 7.4.1 Calculating latitudinal and longitudinal flow.- 7.4.2 Points with zero longitudinal flow in the 3-D universe.- 7.4.3 Points with zero latitudinal flow in the 3-D universe.- 7.5 A Systematic Pattern at the Periphery.- 7.6 Experiment I: Simulated Image Sequence.- 7.7 Experiment II: Servoing to a Target.- 7.8 Conclusion.- 7.9 References.- 8 Local Qualitative Shape from Active Shading.- 8.1 Introduction.- 8.2 Local Qualitative Shape.- 8.3 Diffuse Shading.- 8.3.1 A model of diffuse shading.- 8.3.2 An example.- 8.3.3 Diffuse shading in concavities.- 8.4 Point Source Shading.- 8.5 Active Shading.- 8.6 Conclusion.- 8.7 References.- III Robots that Explore.- 9 The Synthesis of Vision and Action.- 9.1 Prolegomena.- 9.2 Marr's Theory and Its Drawbacks.- 9.3 The Architecture.- 9.3.1 The modules of the system.- 9.3.2 Outline of the approach.- 9.4 The Competences.- 9.4.1 Computational principles.- 9.4.2 Biological hierarchy.- 9.4.3 A hierarchy of models for navigational competences.- 9.4.4 Motion-based competences.- 9.4.5 A look at the motion pathway.- 9.4.6 Form-based competences.- 9.4.7 Spatial understanding.- 9.5 Conclusions.- 9.6 References.- 10 A Framework for Information Assimilation.- 10.1 Introduction.- 10.2 Information Assimilation: Formal Framework.- 10.2.1 Perceptual cycle.- 10.2.2 Sensor fusion and information assimilation.- 10.2.3 Environment Model.- 10.2.4 Input information tracks.- 10.2.5 Task modeling.- 10.2.6 Information assimilation.- 10.2.7 Knowledge caching for assimilation.- 10.3 Example Application: Autonomous Outdoor Navigation.- 10.3.1 Design.- 10.3.2 System architecture.- 10.3.3 Information assimilation module.- 10.4 Applications of Information Assimilation.- 10.5 Conclusion.- 10.6 References.- 11 Task-Oriented Vision.- 11.1 Introduction.- 11.2 Systems Description.- 11.2.1 Rock sampling system.- 11.2.2 Bin picking system.- 11.3 System Analysis.- 11.3.1 Rock-sampling system.- 11.3.2 Bin-picking system.- 11.4 Task-Oriented Approach.- 11.5 Conclusion.- 11.6 References.- IV Human and Machine: Telepresence and Virtual Reality.- 12 Active Vision and Virtual Reality.- 12.1 Introduction.- 12.1.1 Virtual reality and telepresence.- 12.1.2 Active vision.- 12.1.3 Active telepresence.- 12.2 Generating Views.- 12.2.1 Camera calibration.- 12.2.2 Digitization.- 12.2.3 Active estimation of surface depth.- 12.2.4 Registration.- 12.2.5 Warping.- 12.2.6 Integration of views.- 12.2.7 Distortions.- 12.3 Results.- 12.3.1 Simulations.- 12.3.2 Digitized Image Interpolation.- 12.4 Discussion.- 12.5 References.- 13 A Novel Environment for Situated Vision and Behavior.- 13.1 Introduction.- 13.2 The "Looking at People" Domain.- 13.3 Attention and Intention.- 13.4 Action Selection with Time-Varying Goals.- 13.5 Routines for Looking at People.- 13.5.1 Domain constraints.- 13.5.2 Figure-ground processing.- 13.5.3 Scene projection and calibration.- 13.5.4 Hand tracking.- 13.5.5 Gesture interpretation.- 13.6 An Example Implementation: ALIVE.- 13.7 Conclusion.- 13.8 References.- Author Index.