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The design and construction of three-dimensional [3-D] object recognition systems has long occupied the attention of many computer vision researchers. The variety of systems that have been developed for this task is evidence both of its strong appeal to researchers and its applicability to modern manufacturing, industrial, military, and consumer environments. 3-D object recognition is of interest to scientists and engineers in several different disciplines due to both a desire to endow computers with robust visual capabilities, and the wide applications which would benefit from mature and robust vision systems. However, 3-D object recognition is a very complex problem, and few systems have been developed for actual production use; most existing systems have been developed for experimental use by researchers only. This edited collection of papers summarizes the state of the art in 3-D object recognition using examples of existing 3-D systems developed by leading researchers in the field. While most chapters describe a complete object recognition system, chapters on biological vision, sensing, and early processing are also included. The volume will serve as a valuable reference source for readers who are involved in implementing model-based object recognition systems, stimulating the cross-fertilisation of ideas in the various domains.

The variety of topics on Image Communication is so broad that no one can be a specialist in all the topics, and the whole area is beyond the scope of a single volume, while the requirement of up to date information is ever increasing. This new closed-end book series is intended both as a comprehensive reference for those already active in the area of Image Communication, as well as providing newcomers with a foothold for commencing research. Each volume will comprise a state of the art work on the editor's/author's area of expertise, containing information until now scattered in many journals and proceedings.

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CONTENTS
Preface = ⅴ
Table of Contents = ⅸ
Contributors = ⅹ
3D Object Recognition : Inspirations and Lessons from Biological Vision = 1
Range Sensing for Computer Vision = 17
Feature Extraction for 3D Model Building and Object Recognition = 57
Three-Dimensional Surface Reconstruction : Theory and Implementation = 89
CAD-Based Object Recognition in Range Images Using Pre-Compiled Strategy Trees = 115
Active 3D Object Models = 135
Image Prediction for Computer Vision = 159
Tools for 3D Object Location from Geometrical Features by Monocular Vision = 181
Part-Based Modeling and Qualitative Recognition = 201
Appearance-Based Vision and The Automatic Generation on Object Recognition Programs = 229
Recognizing 3D Objects Using Constrained Search = 259
Recognition of Superquadric Models in Dense Range Data = 285
Recognition by Alignment = 311
Representations and Algorithms for 3D Curved Object Recognition = 327
Structural Indexing : Efficient Three Dimensional Object Recognition = 353
Building a 3D World Model for Outdoor Scenes from Multiple Sensory Data = 375
Understanding Object Configurations = 397
Modal Descriptions for Modeling, Recognition, and Tracking = 423
Function-Based Generic Recognition for Multiple Object Categories = 447