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Robert C. Bolles

Other affiliations: Artificial Intelligence Center
Bio: Robert C. Bolles is an academic researcher from SRI International. The author has contributed to research in topics: Feature (computer vision) & Epipolar geometry. The author has an hindex of 24, co-authored 64 publications receiving 25498 citations. Previous affiliations of Robert C. Bolles include Artificial Intelligence Center.


Papers
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Proceedings ArticleDOI
23 Jun 1998
TL;DR: A method of statistical background modeling for stereo sequences that improves the reliability and sensitivity of segmentation in the presence of object clutter is presented, and the dynamic version of the method, called gated background adaptation, can reliably learn background statistics in the absence of corrupting foreground motion.
Abstract: Stereo sequences promise to be a powerful method for segmenting images for applications such as tracking human figures. We present a method of statistical background modeling for stereo sequences that improves the reliability and sensitivity of segmentation in the presence of object clutter. The dynamic version of the method, called gated background adaptation, can reliably learn background statistics in the presence of corrupting foreground motion. The method has been used with a simple head discriminator to detect and track people using a stereo head mounted on a pan/tilt platform. It runs at video rates using standard PC hardware.

155 citations

Patent
29 Jun 2001
TL;DR: In this article, the authors transform the image of the text to a normalized coordinate system before performing OCR, and combine OCR results from multiple frames, in a manner that takes the best recognition results from each frame and forms a single result that can be more accurate than the results from any of the individual frames.
Abstract: An apparatus and a concomitant method for detecting and recognizing text information in a captured imagery. The present method transforms the image of the text to a normalized coordinate system before performing OCR, thereby yielding more robust recognition performance. The present invention also combines OCR results from multiple frames, in a manner that takes the best recognition results from each frame and forms a single result that can be more accurate than the results from any of the individual frames.

149 citations

Journal IssueDOI
TL;DR: The main components that comprise the system, including stereo processing, obstacle and free space interpretation, long-range perception, online terrain traversability learning, visual odometry, map registration, planning, and control are described.
Abstract: The challenge in the DARPA Learning Applied to Ground Robots (LAGR) project is to autonomously navigate a small robot using stereo vision as the main sensor. During this project, we demonstrated a complete autonomous system for off-road navigation in unstructured environments, using stereo vision as the main sensor. The system is very robust—we can typically give it a goal position several hundred meters away and expect it to get there. In this paper we describe the main components that comprise the system, including stereo processing, obstacle and free space interpretation, long-range perception, online terrain traversability learning, visual odometry, map registration, planning, and control. At the end of 3 years, the system we developed outperformed all nine other teams in final blind tests over previously unseen terrain. © 2008 Wiley Periodicals, Inc.

103 citations

Patent
28 Aug 1981
TL;DR: In this paper, an apparatus for controlling positioning of an implement relative to a workpiece, such as a welding head with respect to members to be welded, projects light patterns including an array of light elements each having a known shape and spacing relative to one another on the workpiece.
Abstract: An apparatus for controlling positioning of an implement relative to a workpiece, such as a welding head with respect to members to be welded, projects light patterns including an array of light elements each having a known shape and spacing relative to one another on the workpiece. The light elements as reflected from the workpiece are detected and output signals produced in response to the detected light elements. The output signals are classified into groups based on at least one common characteristic resulting from workpiece geometry. The workpiece geometry is defined from at least one relationship between different ones of the groups of the first output signals. Second output signals are produced indicative of the so-determined workpiece geometry. The second output signals are used to control positioning of the implement relative to the workpiece. This apparatus and process allows workpiece geometry to be defined and the implement to be positioned relative to the workpiece on a real-time basis.

90 citations

Journal ArticleDOI
TL;DR: The main components that comprise the system, including stereo processing, obstacle and free space interpretation, long‐range perception, online terrain traversability learning, visual odometry, map registration, planning, and control are described.
Abstract: The challenge in the DARPA Learning Applied to Ground Robots (L AGR) project is to autonomously navigate a small robot using stereo visio n as the main sensor. During this project, we demonstrated a complete autonomous system for off-road navigation in unstructured environments, using stereo vis ion as the main sensor. The system is very robust – we can typically give it a goal posi ti n several hundred meters away, and expect it to get there. In this paper we d escribe the main components that comprise the system, including stereo proc essing, obstacle and freespace interpretation, long-range perception, online terrain traversability learning, visual odometry, map registration, planning, and cont rol. At the end of three years, the system we developed outperformed all 9 other team s in final blind tests over previously-unseen terrain.

83 citations


Cited by
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Journal ArticleDOI
TL;DR: A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original.
Abstract: The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSIBLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.

70,111 citations

Journal ArticleDOI
Paul J. Besl1, H.D. McKay1
TL;DR: In this paper, the authors describe a general-purpose representation-independent method for the accurate and computationally efficient registration of 3D shapes including free-form curves and surfaces, based on the iterative closest point (ICP) algorithm, which requires only a procedure to find the closest point on a geometric entity to a given point.
Abstract: The authors describe a general-purpose, representation-independent method for the accurate and computationally efficient registration of 3-D shapes including free-form curves and surfaces. The method handles the full six degrees of freedom and is based on the iterative closest point (ICP) algorithm, which requires only a procedure to find the closest point on a geometric entity to a given point. The ICP algorithm always converges monotonically to the nearest local minimum of a mean-square distance metric, and the rate of convergence is rapid during the first few iterations. Therefore, given an adequate set of initial rotations and translations for a particular class of objects with a certain level of 'shape complexity', one can globally minimize the mean-square distance metric over all six degrees of freedom by testing each initial registration. One important application of this method is to register sensed data from unfixtured rigid objects with an ideal geometric model, prior to shape inspection. Experimental results show the capabilities of the registration algorithm on point sets, curves, and surfaces. >

17,598 citations

01 Jan 2001
TL;DR: This book is referred to read because it is an inspiring book to give you more chance to get experiences and also thoughts and it will show the best book collections and completed collections.
Abstract: Downloading the book in this website lists can give you more advantages. It will show you the best book collections and completed collections. So many books can be found in this website. So, this is not only this multiple view geometry in computer vision. However, this book is referred to read because it is an inspiring book to give you more chance to get experiences and also thoughts. This is simple, read the soft file of the book and you get it.

14,282 citations

Journal ArticleDOI
TL;DR: This paper has designed a stand-alone, flexible C++ implementation that enables the evaluation of individual components and that can easily be extended to include new algorithms.
Abstract: Stereo matching is one of the most active research areas in computer vision. While a large number of algorithms for stereo correspondence have been developed, relatively little work has been done on characterizing their performance. In this paper, we present a taxonomy of dense, two-frame stereo methods designed to assess the different components and design decisions made in individual stereo algorithms. Using this taxonomy, we compare existing stereo methods and present experiments evaluating the performance of many different variants. In order to establish a common software platform and a collection of data sets for easy evaluation, we have designed a stand-alone, flexible C++ implementation that enables the evaluation of individual components and that can be easily extended to include new algorithms. We have also produced several new multiframe stereo data sets with ground truth, and are making both the code and data sets available on the Web.

7,458 citations

Journal ArticleDOI
TL;DR: A review of recent as well as classic image registration methods to provide a comprehensive reference source for the researchers involved in image registration, regardless of particular application areas.

6,842 citations