Robert C. Bolles

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.

A RANSAC-based approach to model fitting and its application to finding cylinders in range data

Abstract: General principles for fitting models to data containing "gross" errors in addition to "measurement" errors are presented A fitting technique is described and illustrated by its application to the problem of locating cylinders in range data, two key steps in this process arc fitting ellipses to partial data and fitting lines to sets of three-dimensional points The technique is specifically designed to filter out gross errors before applying a smoothing procedure to compute a precise model Such a technique is particularly applicable to computer vision tasks because the data in these tasks arc often produced by local computations that are inherently unreliable.

VERL: an ontology framework for representing and annotating video events

Abstract: The notion of "events" is extremely important in characterizing the contents of video. An event is typically triggered by some kind of change of state captured in the video, such as when an object starts moving. The ability to reason with events is a critical step toward video understanding. This article describes the findings of a recent workshop series that has produced an ontology framework for representing video events-called Video Event Representation Language (VERL) -and a companion annotation framework, called Video Event Markup Language (VEML). One of the key concepts in this work is the modeling of events as composable, whereby complex events are constructed from simpler events by operations such as sequencing, iteration, and alternation. The article presents an extensible event and object ontology expressed in VERL and discusses a detailed example of applying VERL and VEML to the description of a "tailgating" event in surveillance video.

Outdoor Mapping and Navigation Using Stereo Vision

Abstract: We consider the problem of autonomous navigation in an unstructured outdoor environment. The goal is for a small outdoor robot to come into a new area, learn about and map its environment, and move to a given goal at modest speeds (1 m/s). This problem is especially difficult in outdoor, off-road environments, where tall grass, shadows, deadfall, and other obstacles predominate. Not surprisingly, the biggest challenge is acquiring and using a reliable map of the new area. Although work in outdoor navigation has preferentially used laser rangefinders [14,2,6], we use stereo vision as the main sensor. Vision sensors allow us to use more distant objects as landmarks for navigation, and to learn and use color and texture models of the environment, in looking further ahead than is possible with range sensors alone.

Perceptual Organization and Curve Partitioning

Abstract: In this paper we offer a critical evaluation of the partitioning (perceptual organization) problem, noting the extent to which it has distinct formulations and parameterizations. We show that most partitioning techniques can be characterized as variations of four distinct paradigms, and argue that any effective technique must satisfy two general principles. We give concrete substance to our general discussion by introducing new partitioning techniques for planar geometric curves, and present experimental results demonstrating their effectiveness.

Generalizing epipolar-plane image analysis on the spatiotemporal surface

Abstract: The previous implementations of the authors' epipolar-plane image-analysis mapping technique demonstrated the feasibility and benefits of the approach, but were carried out for restricted camera geometries. The question of more general geometries made the technique's utility for autonomous navigation uncertain. The authors have developed a generalization of the analysis that: (1) enables varying view direction, including varying over time; (2) provides three-dimensional connectivity information for building coherent spatial descriptions of observed objects; and (3) operates sequentially, allowing initiation and refinement of scene feature estimates while the sensor is in motion. To implement this generalization it was necessary to develop an explicit description of the evolution of images over time. They achieved this by building a process that creates a set of two-dimensional manifolds defined at the zeros of a three-dimensional spatiotemporal Laplacian. These manifolds represent explicitly both the spatial and temporal structure of the temporally evolving imagery and are termed spatiotemporal surfaces. >

Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

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.

A method for registration of 3-D shapes

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. >

Multiple View Geometry in Computer Vision.

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A taxonomy and evaluation of dense two-frame stereo correspondence 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.