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Computer vision researchers have been frustrated in their attempts to automatically derive depth information from conventional two-dimensional intensity images. Research on "shape from texture", "shape from shading", and "shape from focus" is still in a laboratory stage and had not seen much use in commercial machine vision systems. A range image or a depth map contains explicit information about the distance from the sensor to the object surfaces within the field of view in the scene. Information about "surface geometry" which is important for, say, three-dimensional object recognition is more easily extracted from "2 1/2 D" range images than from "2D" intensity images. As a result, both active sensors such as laser range finders and passive techniques such as multi-camera stereo vision are being increasingly utilized by vision researchers to solve a variety of problems. This book contains chapters written by distinguished computer vision researchers covering the following areas: Overview of 3D Vision Range Sensing Geometric Processing Object Recognition Navigation Inspection Multisensor Fusion A workshop report, written by the editors, also appears in the book. It summarizes the state of the art and proposes future research directions in range image sensing, processing, interpretation, and applications. The book also contains an extensive, up-to-date bibliography on the above topics. This book provides a unique perspective on the problem of three-dimensional sensing and processing; it is the only comprehensive collection of papers devoted to range images. Both academic researchers interested in research issues in 3D vision and industrial engineers in search of solutions to particular problems will find this a useful reference book.




Computer vision researchers have been frustrated in their attempts to automatically derive depth information from conventional two-dimensional intensity images. Research on "shape from texture", "shape from shading", and "shape from focus" is still in a laboratory stage and had not seen much use in commercial machine vision systems. A range image or a depth map contains explicit information about the distance from the sensor to the object surfaces within the field of view in the scene. Information about "surface geometry" which is important for, say, three-dimensional object recognition is more easily extracted from "2 1/2 D" range images than from "2D" intensity images. As a result, both active sensors such as laser range finders and passive techniques such as multi-camera stereo vision are being increasingly utilized by vision researchers to solve a variety of problems. This book contains chapters written by distinguished computer vision researchers covering the following areas: Overview of 3D Vision Range Sensing Geometric Processing Object Recognition Navigation Inspection Multisensor Fusion A workshop report, written by the editors, also appears in the book. It summarizes the state of the art and proposes future research directions in range image sensing, processing, interpretation, and applications. The book also contains an extensive, up-to-date bibliography on the above topics. This book provides a unique perspective on the problem of three-dimensional sensing and processing; it is the only comprehensive collection of papers devoted to range images. Both academic researchers interested in research issues in 3D vision and industrial engineers in search of solutions to particular problems will find this a useful reference book.


Computer vision researchers have been frustrated in their attempts to automatically derive depth information from conventional two-dimensional intensity images. Research on "shape from texture", "shape from shading", and "shape from focus" is still in a laboratory stage and had not seen much use in commercial machine vision systems. A range image or a depth map contains explicit information about the distance from the sensor to the object surfaces within the field of view in the scene. Information about "surface geometry" which is important for, say, three-dimensional object recognition is more easily extracted from "2 1/2 D" range images than from "2D" intensity images. As a result, both active sensors such as laser range finders and passive techniques such as multi-camera stereo vision are being increasingly utilized by vision researchers to solve a variety of problems. This book contains chapters written by distinguished computer vision researchers covering the following areas: Overview of 3D Vision Range Sensing Geometric Processing Object Recognition Navigation Inspection Multisensor Fusion A workshop report, written by the editors, also appears in the book. It summarizes the state of the art and proposes future research directions in range image sensing, processing, interpretation, and applications. The book also contains an extensive, up-to-date bibliography on the above topics. This book provides a unique perspective on the problem of three-dimensional sensing and processing; it is the only comprehensive collection of papers devoted to range images. Both academic researchers interested in research issues in 3D vision and industrial engineers in search of solutions to particular problems will find this a useful reference book.
Content:
Front Matter....Pages i-xiii
Report: 1988 NSF Range Image Understanding Workshop....Pages 1-31
A Rule-Based Approach to Binocular Stereopsis....Pages 33-139
Geometric Signal Processing....Pages 141-205
Segmentation versus object representation — are they separable?....Pages 207-223
Object Recognition....Pages 225-253
Applications of Range Image Sensing and Processing....Pages 255-272
3-D Vision Techniques for Autonomous Vehicles....Pages 273-337
Multisensor Fusion for Automatic Scene Interpretation....Pages 339-361
Back Matter....Pages 363-387


Computer vision researchers have been frustrated in their attempts to automatically derive depth information from conventional two-dimensional intensity images. Research on "shape from texture", "shape from shading", and "shape from focus" is still in a laboratory stage and had not seen much use in commercial machine vision systems. A range image or a depth map contains explicit information about the distance from the sensor to the object surfaces within the field of view in the scene. Information about "surface geometry" which is important for, say, three-dimensional object recognition is more easily extracted from "2 1/2 D" range images than from "2D" intensity images. As a result, both active sensors such as laser range finders and passive techniques such as multi-camera stereo vision are being increasingly utilized by vision researchers to solve a variety of problems. This book contains chapters written by distinguished computer vision researchers covering the following areas: Overview of 3D Vision Range Sensing Geometric Processing Object Recognition Navigation Inspection Multisensor Fusion A workshop report, written by the editors, also appears in the book. It summarizes the state of the art and proposes future research directions in range image sensing, processing, interpretation, and applications. The book also contains an extensive, up-to-date bibliography on the above topics. This book provides a unique perspective on the problem of three-dimensional sensing and processing; it is the only comprehensive collection of papers devoted to range images. Both academic researchers interested in research issues in 3D vision and industrial engineers in search of solutions to particular problems will find this a useful reference book.
Content:
Front Matter....Pages i-xiii
Report: 1988 NSF Range Image Understanding Workshop....Pages 1-31
A Rule-Based Approach to Binocular Stereopsis....Pages 33-139
Geometric Signal Processing....Pages 141-205
Segmentation versus object representation — are they separable?....Pages 207-223
Object Recognition....Pages 225-253
Applications of Range Image Sensing and Processing....Pages 255-272
3-D Vision Techniques for Autonomous Vehicles....Pages 273-337
Multisensor Fusion for Automatic Scene Interpretation....Pages 339-361
Back Matter....Pages 363-387
....
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