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Series in Machine Perception and Artificial Intelligence - Vol. 17
APPLICATIONS OF AI, MACHINE VISION AND ROBOTICS
edited by K L Boyer (The Ohio State University), L Stark (The University of the Pacific) & H Bunke (University of Bern)
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 behavior-based active eye vision system. The scope of the book provides an excellent sample of current concepts, examples and applications from multiple areas of computer vision.
Contents:
- Range Estimation from Camera Blur by Regularized Adaptive
Identification (L F Holeva)
- Modeling Sensor Confidence for Sensor Integration Tasks (K Hughes & N Ranganathan)
- From 3-D Scattered Data to Geometric Signal Description: Invariant Stable Recovery of Straight Line Segments (P Hébert et al.)
- Feature Extraction and Matching as Signal Detection (X-P Hu & N Ahuja)
- Non-Parametric Multiscale Curve Smoothing (P L Rosin)
- Integration of Geometric and Non-Geometric Attributes for Fast Object Recognition (L Grewe & A Kak)
- A Four Degree-of-Freedom Robot Head for Active Vision (F-L Du & M Brady)
- Control of Eye and Arm Movements Using Active, Attentional Vision (P A Sandon)
- Behavior-Based Active Vision (C S Pinhanez)
Readership: Computer scientists and engineers.
| 268pp |
Pub. date: Feb 1995 |
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