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Applications
of AI, Machine Vision and Robotics
Boyer, K.L. (Ohio State University, USA),
Stark, L. (University of the Pacific, California, USA),
This text discusses research efforts in artificial intelligence,
machine vision and robotics. Specific topics covered include:
sensor confidence; low level feature extraction schemes;
non-parametric multi-scale curve smoothing; and design criteria
for a four degree-of-freedom robot head.
Description
This text features a broad array of research efforts in
computer vision including low level processing, perceptual
organization, object recognition and active vision. The
volume's nine papers specifically report on topics such
as sensor confidence, low level feature extraction schemes,
non-parametric multi-scale curve smoothing, integration
of geometric and non-geometric attributes for object recognition,
design criteria for a four degree-of-freedom robot head,
a real-time vision system based on control of visual attention
and a behaviour-based active eye vision system. The scope
of the book provides a sample of current concepts, examples
and applications from multiple areas of computer vision.
Table of Contents
Range estimation from camera blur by regularized adaptive
identification, L.-F. Holeva
modelling sensor confidence for sensor integration task,
K. Hughes and N. Ranganathan
from 3-D scattered data to geometric signal description
- invariant stable recovery of straight line segments, P.
Hebert et al
feature extraction and matching as signal detection, X.-P.
Hu and N. Ahuja
non-parametric multi-scale curve smoothing, P.L. Rosin
integration of geometric and non-geometric attributes for
fast object recognition, L. Grewe and A. Kak
a four degree-of-freedom robot head for active vision, F.-L.
Du and M. Brady
control of eye and arm movements using active, attentional
vision, P.A. Sandon
behaviour-based active vision, C.S. Pinhanez.
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Learning-Based
Robot Vision: Principles and Applications
Pauli, Josef.
Pauli, Josef
Synopsis
This text provides the background and introduces a practical
methodology for developing autonomous camera-equipped robot
systems which solve deliberate tasks in open environments,
based on their competences acquired from training, interaction,
and learning in the real task-relevant world; visual demonstration
and neural learning for the backbone for acquiring the situated
competences. The author verifies the practicability of the
proposed methodology by presenting a structured case study
including high-level sub-tasks such as localizing, approaching,
grasping, and carrying objects
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Modelling
and Planning for Sensor Based Intelligent Robot Systems
Edition N
Bunke, H. (University of Bern, Switzerland), Kanade, T. (Carnegie
Mellon University, USA), Noltemeie
Presents an overview of and covers developments in the areas
of modelling and planning for sensor based robots. Topics
addressed include active vision, sensor fusion, environment
modelling, motion planning, robot navigation, distributed
control architectures, and reactive behaviour.
Description
This edited and reviewed volume consists of papers that were
originally presented at a workshop in the Scientific Center
at Schloss Dagstuhl, Germany. It gives an overview of the
field and presents the latest developments in the areas of
modelling and planning for sensor based robots. The particular
topics addressed include active vision, sensor fusion, environment
modelling, motion planning, robot navigation, distributed
control architectures, reactive behaviour, and others.
Key contributors to this volume are: S. Arimoto, R. Bolles,
H. Bunke, H. Christensen, R. Dillmann, T. Henderson, R. Jarvis,
H. Noltemeier, U. Rembold, Y. Shirai, C. Torras.
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Three-dimensional
Computer Vision
Faugeras, Olivier
Provides an exposition of an area in computer vision: the
problems and techniques related to three-dimensional (stereo)
vision and motion. The emphasis is on using geometry to
solve problems in stereo and motion, with examples from
navigation and object recognition.
Description
This monograph provides a thorough, mathematically rigorous
exposition of a broad and vital area in computer vision:
the problems and techniques related to three-dimensional
(stereo) vision and motion. The emphasis is on using geometry
to solve problems in stereo and motion, with examples from
navigation and object recognition.
Faugeras takes up such problems in computer vision as projective
geometry, camera calibration, edge detection, stereo vision
(with many examples on real images), different kinds of
representations and transformations (especially 3-D rotations),
uncertainty and methods of addressing it, and object representation
and recognition. His theoretical account is illustrated
with the results of actual working programmes.
"Three-Dimensional
Computer Vision" proposes solutions to problems arising
from a specific robotics scenario in which a system must
perceive and act. Moving about an unknown environment, the
system has to avoid static and mobile obstacles, build models
of objects and places in order to be able to recognize and
locate them, and characterize its own motion and that of
moving objects, by providing descriptions of the corresponding
three-dimensional motions. The ideas generated, however,
can be used in different settings, resulting in a general
book on computer vision that reveals the relationship of
three-dimensional geometry and the imaging process.
Table of Contents
Projective geometry
modelling and calibrating cameras
edge detection
representing geometric primitives and their uncertainty
stereo vision
determining discrete motion from points and lines
tracking tokens over time
motion fields of curves
interpolating and approximating three-dimensional data
recognizing and locating objects and places
answers to problems. Appendices: constrained optimization
some results from algebraic geometry
differential geometry.
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