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Iterative point matching for registration of freeform curves and surfaces
, 1994
"... A heuristic method has been developed for registering two sets of 3D curves obtained by using an edgebased stereo system, or two dense 3D maps obtained by using a correlationbased stereo system. Geometric matching in general is a difficult unsolved problem in computer vision. Fortunately, in ma ..."
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Cited by 479 (6 self)
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A heuristic method has been developed for registering two sets of 3D curves obtained by using an edgebased stereo system, or two dense 3D maps obtained by using a correlationbased stereo system. Geometric matching in general is a difficult unsolved problem in computer vision. Fortunately, in many practical applications, some a priori knowledge exists which considerably simplifies the problem. In visual navigation, for example, the motion between successive positions is usually approximately known. From this initial estimate, our algorithm computes observer motion with very good precision, which is required for environment modeling (e.g., building a Digital Elevation Map). Objects are represented by a set of 3D points, which are considered as the samples of a surface. No constraint is imposed on the form of the objects. The proposed algorithm is based on iteratively matching points in one set to the closest points in the other. A statistical method based on the distance distribution is used to deal with outliers, occlusion, appearance and disappearance, which allows us to do subsetsubset matching. A leastsquares technique is used to estimate 3D motion from the point correspondences, which reduces the average distance between points in the two sets. Both synthetic and real data have been used to test the algorithm, and the results show that it is efficient and robust, and yields an accurate motion estimate.
Visual odometry for ground vehicle applications
 Journal of Field Robotics
, 2006
"... We present a system that estimates the motion of a stereo head or a single moving camera based on video input. The system operates in realtime with low delay and the motion estimates are used for navigational purposes. The front end of the system is a feature tracker. Point features are matched bet ..."
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Cited by 90 (5 self)
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We present a system that estimates the motion of a stereo head or a single moving camera based on video input. The system operates in realtime with low delay and the motion estimates are used for navigational purposes. The front end of the system is a feature tracker. Point features are matched between pairs of frames and linked into image trajectories at video rate. Robust estimates of the camera motion are then produced from the feature tracks using a geometric hypothesizeandtest architecture. This generates motion estimates from visual input alone. No prior knowledge of the scene nor the motion is necessary. The visual estimates can also be used in conjunction with information from other sources such as GPS, inertia sensors, wheel encoders, etc. The pose estimation method has been applied successfully to video from aerial, automotive and handheld platforms. We focus on results obtained with a stereohead mounted on an autonomous ground vehicle. We give examples of camera trajectories estimated in realtime purely from images over previously unseen distances (600 meters) and periods of time. 1.
Token Tracking in a Cluttered Scene
 Image and Vision Computing
, 1993
"... The statistical data association technique is an important approach to analyze long sequences of images in Computer Vision. Although it has extensively been studied in other domains such as in radar imagery, it was introduced only recently in Computer Vision, and is already recognized as an efficien ..."
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Cited by 21 (0 self)
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The statistical data association technique is an important approach to analyze long sequences of images in Computer Vision. Although it has extensively been studied in other domains such as in radar imagery, it was introduced only recently in Computer Vision, and is already recognized as an efficient approach to solving correspondence and motion problems. This paper has two purposes. The first is to present a general formulation of token tracking. The parameterization of tokens is not addressed. This might be useful to those who are not familiar with statistical tracking techniques. The second is to introduce some strategies for tracking with emphasis on practical importance. They include beam search for resolving multiple matches, support of existence for discarding false matches, and locking on reliable tokens and maximizing local rigidity for handling combinatorial explosion. We have implemented those strategies in a 3D line segment tracking algorithm and found them very useful.
Motion and Surface Recovery Using Curvature and Motion Consistency
 In PROC. Second European Conference on Computer Vision
, 1993
"... this paper is a set of algorithms for reconstructing surfaces obtained from overlapping range images in a common frame of reference. Surfaces are assumed to be piecewisesmooth but not necessarily rigid. Motion parameters, rotations and translations that describe correspondence between views, are re ..."
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Cited by 9 (3 self)
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this paper is a set of algorithms for reconstructing surfaces obtained from overlapping range images in a common frame of reference. Surfaces are assumed to be piecewisesmooth but not necessarily rigid. Motion parameters, rotations and translations that describe correspondence between views, are recovered locally under the assumption that the curvature structure at a point on a surface varies slowly under transformation. The recovery problem can thus be posed as finding the set of motion parameters that preserves curvature across two views. We show that an appropriate similarity functional can be devised that is convex in the vicinity of the true motion parameters. This leads to an efficient local algorithm that recovers motion parameters in gradient descent fashion. Fusion of information from different viewpoints is accomplished by applying local motion estimates to map data points between frames. However, because these estimates are determined locally, they are subject to the usual effects of noise and quantization error. To increase the robustness of this reconstruction procedure the additional constraint of motion consistency is introduced, that variations in the velocities of adjacent regions are also piecewisesmooth. This is cast as a second local minimization problem which seeks to find the set of motion parameters that minimizes differences in the relative positions and orientations at adjacent points. The resulting algorithm serves to smooth out local perturbations and blend adjacent surface patches. In contrast to global rigid body motion approaches, our procedure for reconstructing surfaces from different viewpoints is tolerant of local errors in correspondence and can accommodate objects that are articulated.
Relaxed parametric design with probabilistic constraints
 In Solid Modelling93
, 1994
"... Abstract: Parametric design is an important modeling paradigm in computer aided design. Relationships (constraints) between the degrees of freedom (DOFs) of the model, instead of the DOFs themselves, are specified, resulting in efficient design modifications and variations. Current parametric modele ..."
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Cited by 9 (4 self)
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Abstract: Parametric design is an important modeling paradigm in computer aided design. Relationships (constraints) between the degrees of freedom (DOFs) of the model, instead of the DOFs themselves, are specified, resulting in efficient design modifications and variations. Current parametric modelers require an exact specification of all the constraints involved, which causes overwork on the part of the designer during design iterations. We describe the relaxed parametric design modeling paradigm, in which decisions which needlessly limit the freedom of design in later stages are avoided. The designer uses soft constraints and specifies the exactness by which they are to be met. As a specific scheme for implementing relaxed parametric design, we present probabilistic constraints, where a parametric model is viewed as a stochastic process. Softness of a constraint is represented as the covariance of a suitably distributed random variable. We describe a novel method for expressing the DOFs and the model as a system of probabilistic equations, which is then solved using the Kalman filter, a powerful estimation tool for stochastic systems. An a priori covariance matrix associated with a DOF can be used as a guideline to the solver to select a particular solution among multiple solutions.
A Stereovision System for a Planetary Rover: Calibration, Correlation, Registration, and Fusion
, 1996
"... This paper describes a complete stereovision system, which was originally developed for planetary applications, but can be used for other applications such as object modeling. A new effective onsite calibration technique has been developed, which can make use of the information from the surrounding ..."
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Cited by 6 (0 self)
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This paper describes a complete stereovision system, which was originally developed for planetary applications, but can be used for other applications such as object modeling. A new effective onsite calibration technique has been developed, which can make use of the information from the surrounding environment as well as the information from the calibration apparatus. A correlationbased stereo algorithm is used, which can produce sufficient dense range maps with an algorithmic structure for fast implementations. A technique based on iterative closestpoint matching has been developed for registration of successive depth maps and computation of the displacements between successive positions. A statistical method based on the distance distribution is integrated into this registration technique, which allows us to deal with the important problems such as outliers, occlusion, appearance and disappearance. Finally, the registered maps are expressed in the same coordinate system and are fu...
A StereovisionBased Navigation System for a Mobile Robot
, 1993
"... This report describes the work at INRIA on obstacle avoidance and trajectory planning for a mobile robot using stereovision. Our mobile robot is equipped with a trinocular vision system that has been put into hardware and is be capable of delivering 3D maps of the environment at rates between 1 ..."
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Cited by 4 (0 self)
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This report describes the work at INRIA on obstacle avoidance and trajectory planning for a mobile robot using stereovision. Our mobile robot is equipped with a trinocular vision system that has been put into hardware and is be capable of delivering 3D maps of the environment at rates between 1 and 5 Hz. Those 3D maps contain line segments extracted from the images and reconstructed in three dimensions. They are used for a variety of tasks including obstacle avoidance and trajectory planning. For those two tasks, we project on the ground floor the 3D line segments to obtain a twodimensional map, we simplify the map according to some simple geometric criteria, and use the remaining 2D segments to construct a tessellation, more precisely a triangulation, of the ground floor. This tessellation has several advantages: ffl It is adapted to the structure of the environment since all stereo segments are edges of triangles in the tessellation, ffl It can be efficiently computed ...