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Kaiser, Alexander: Internal visuomotor models for cognitive simulation processes. 2014
Inhalt
Introduction
Theoretical Foundations
Grounded Cognition
Related Concepts
Simulation and Emulation Theories
Experimental Evidence
Learning of Sensorimotor Interactions
Towards a Model Architecture for Simulated Object Interaction
Overview
Visuomotor Associations
Prediction of Object Interactions
Simulation Process
Outline
Visual Prediction by Using RBF Networks
Introduction
Methods
Setup
Image Distortion Model
Image Warping
Radial Basis Functions
Generalized Radial Basis Function Networks
Positive Definite and Conditionally Definite Kernels
Dual Representation
Visual Forward Model
Data Acquisition
Full Mapping Model
Two-Staged Mapping Model
Validator Model
Results
Conclusions & Outlook
A Geometric Model for Visual Prediction and Saccade Control
Introduction
Geometric model
Visual forward model
Transformation
Interpolation
Image Distortion
Results
Saccade Control
Geometric Saccade Controller
Adaptive Controller
Results
Conclusions
Outlook
An Associative Model for Mental Imagery
Introduction
Robotic Agent
Vergence Model
Arm Postures
Kinesthetic Association
Vergence Control
Collection of Training Data
Neural Network and Training
Visual Association
Eigen-Images
Data Collection and Image Processing
Appearance Vectors and Network Training
Results
Conclusions & Outlook
Stereo Matching by Internal Simulation
Introduction
Setup
Robotic Agent
Retinal Images
Visual forward model
Data Acquisition
Implementation
Saccade Controller
Stereo Matching
Predictive Matching
SIFT-Based Matching
Saliency Detection
Pre-Processing
Segmentation and Clustering
Results
Experiment 1
Experiment 2
Conclusions & Outlook
Overall Conclusions & Outlook
Visual Prediction
Visuomotor Associations
Future Research Directions
Alternative Learning Methods
Alternative Approaches of ``Perception through Anticipation''
Down-Dating the Inverse of a Matrix
Reconstruction of Gripper Positions
Simulated Gripper Appearance
Bibliography