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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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Book ChapterDOI
01 Jan 1987
TL;DR: In this paper, a technique for unifying spatial and temporal analysis of an image sequence taken by a camera moving in a straight line is presented, based on a "dense" sequence of images-images taken close enough together to form a solid block of data.
Abstract: A technique for unifying spatial and temporal analysis of an image sequence taken by a camera moving in a straight line is presented. The technique is based on a “dense” sequence of images-images taken close enough together to form a solid block of data. Slices of this solid directly encode changes due to motion of the camera. These slices, which have one spatial dimension and one temporal dimension, are more structured than conventional images. This additional structure makes them easier to analyze. We present the theory behind this technique, describe an initial implementation, and discuss our preliminary results.

80 citations

Proceedings ArticleDOI
21 Feb 2007
TL;DR: This paper shows how it is possible to build a consistent, globally correct map in real time, using efficient precise stereo algorithms for map making and visual odometry for localization.
Abstract: We consider the problem of autonomous navigation in unstructured outdoor terrains using vision sensors. The goal is for a robot to come into a new environment, map it and move to a given goal at modest speeds (1 m/sec). The biggest challenges are in building good maps and keeping the robot well localized as it advances towards the goal. In this paper, we concentrate on showing how it is possible to build a consistent, globally correct map in real time, using efficient precise stereo algorithms for map making and visual odometry for localization. While we have made advances in both localization and mapping using stereo vision, it is the integration of the techniques that is the biggest contribution of the research. The validity of our approach is tested in blind experiments, where we submit our code to an independent testing group that runs and validates it on an outdoor robot

70 citations

Proceedings ArticleDOI
10 Oct 1979
TL;DR: A technique that uses the relative positions and orientations of the features to determine the correspondence between features of an object model and features observed in a picture and is a robust, general-purpose way to match structures.
Abstract: A crucial step in the recognition or location of an object in an image is the proper identification of object features. If the features are not uniquely characterized by their local appearances, as is often the case in programmable assembly, the matching technique must base its decisions on the relative structure of the features. In this paper we describe a technique that uses the relative positions and orientations of the features to determine the correspondence between features of an object model and features observed in a picture. A graph is constructed in which maximal cliques (i.e., completely connected subgraphs) represent mutually consistent assignments of model features to observed features. The technique is a robust, general-purpose way to match structures. However, in practical applications its use is restricted to moderately sized graphs because the algorithm that locates maximal cliques is apparently exponential. For tasks that require the analysis of large graphs a few techniques are presented to reformulate them so that smaller graphs are sufficient.© (1979) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

70 citations

Proceedings ArticleDOI
13 Mar 1984
TL;DR: A strategy for recognizing and locating three-dimensional objects in range data is presented and a detailed example of this approach being used to recognize moderately complex castings in a jumble is presented.
Abstract: A strategy for recognizing and locating three-dimensional objects in range data is presented. The strategy combines information derived from models of the objects and edges and surfaces detected in the data to efficiently match objects. Given a set of objects to be found, the set of object features are partitioned into subsets having similar intrinsic properties. An ordered tree of features to be considered is set up for each subset. These search trees are designed to maximize the use of the information as it is obtained and minimize the time required to recognize objects. A detailed example of this approach being used to recognize moderately complex castings in a jumble is presented.

69 citations

Journal ArticleDOI
TL;DR: This work proposes an approach that reliably rectifies and subsequently recognizes individual lines of text in real-world text that has been rigorously tested on still imagery as well as on MPEG-2 video clips in real time.
Abstract: Real-world text on street signs, nameplates, etc. often lies in an oblique plane and hence cannot be recognized by traditional OCR systems due to perspective distortion. Furthermore, such text often comprises only one or two lines, preventing the use of existing perspective rectification methods that were primarily designed for images of document pages. We propose an approach that reliably rectifies and subsequently recognizes individual lines of text. Our system, which includes novel algorithms for extraction of text from real-world scenery, perspective rectification, and binarization, has been rigorously tested on still imagery as well as on MPEG-2 video clips in real time.

68 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