Searching for an object in a cluttered area is often complicated by the fact that the clutter hides portions of the area from view. Multiple viewpoints are often required. Previous viewpoint selection algorithms rely ...
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Searching for an object in a cluttered area is often complicated by the fact that the clutter hides portions of the area from view. Multiple viewpoints are often required. Previous viewpoint selection algorithms rely on models that represent the portions already viewed. Unfortunately, these models are often difficult to construct when the sensor position is imprecisely known and when the obtainable depth data is sparse. This paper questions whether scene models are really necessary for selecting viewpoints for search tasks. It investigates two alternative viewpoint selection methods that do not rely on such models. One constructs no representation and simply uses a fitted set of viewpoints, while the other selects viewpoints based on detected occluding edges. On average, both model-free methods compare very favorably to model-based methods, although additional work is necessary to ensure that they abort in a timely manner when the desired object cannot be found.< >
This article presents a methodology for using stereo visual feedback to perform manipulation tasks. The two major innovations in the approach are: 1) the use of feature-based tracking methods that perform in real-time...
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This article presents a methodology for using stereo visual feedback to perform manipulation tasks. The two major innovations in the approach are: 1) the use of feature-based tracking methods that perform in real-time on standard workstations without specialized hardware; and 2) the use of closed-loop feedback control based on projective invariants to make positioning accuracy independent of hand-eye calibration error. Particular attention is given to the feature tracking component of the system. The feature tracker is a programming environment that supports a variety of low-level detection methods (basic features), and features defined in terms of other features (composite features). Basic and composite features are combined into feature networks. Experimental results from two feature networks are presented. One computes corresponding epipolar lines using eight corresponding features in two images. The second computes a visual trajectory for a visual servoing system.< >
We are considering the problem of recovering the three-dimensional geometry of a scene from binocular stereo disparity. Once a dense disparity map has been computed from a stereo pair of images, one often needs to cal...
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We are considering the problem of recovering the three-dimensional geometry of a scene from binocular stereo disparity. Once a dense disparity map has been computed from a stereo pair of images, one often needs to calculate some local differential properties of the corresponding 3-D surface such as orientation or curvatures. The usual approach is to build a 3-D reconstruction of the surface(s) from which all shape properties will then be derived without ever going back to the original images. In this paper, we depart from this paradigm and propose to use the images directly to compute the shape properties. We thus propose a new method extending the classical correlation method to estimate accurately both the disparity and its derivatives directly from the image data. We then relate those derivatives to differential properties of the surface such as orientation and curvatures.< >
The concept of visual looming can be used as a powerful visual cue for autonomous obstacle avoidance. In this paper a method that measures looming quantitatively by fixating a camera at a point on the surface of an ob...
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The concept of visual looming can be used as a powerful visual cue for autonomous obstacle avoidance. In this paper a method that measures looming quantitatively by fixating a camera at a point on the surface of an object is presented. It is based on studying the texture and its temporal change near the fixation point. The surface may be tilted relative to the optical axis. Looming can be calculated from the relative change in texture density and from the local orientation of the surface. The orientation is obtained from a set of one-dimensional directional densities of the texture primitives. This visual cue is used as a feedback signal of a closed loop system to implement obstacle avoidance using a six-degree-of-freedom simulator.< >
This paper considers the problem of modeling and extracting arbitrary deformable contours from noisy images. We propose a global contour model based on a stable and regenerative shape matrix, which is invariant and un...
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This paper considers the problem of modeling and extracting arbitrary deformable contours from noisy images. We propose a global contour model based on a stable and regenerative shape matrix, which is invariant and unique under rigid motions. Combined with Markov random field to model local deformations, this yields prior distribution that exerts influence over a global model while allowing for deformations. We then cast the problem of extraction into posterior estimation and show its equivalence to energy minimization of a generalized active contour model. We discuss pertinent issues in shape training, minimax regularization and initialization by generalized Hough transform. Finally, we present experimental results and compare its performance to rigid template matching.< >
Image deformations due to the relative motion between an observer and an object may be used to infer 3D structure. Up to first order, these deformations can be written in terms of an affine transform. A new framework ...
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Image deformations due to the relative motion between an observer and an object may be used to infer 3D structure. Up to first order, these deformations can be written in terms of an affine transform. A new framework for measuring affine transforms, which correctly handles the problem of corresponding deformed patches, is presented. In this framework, points, lines or image brightnesses may be used to derive the affine transform between image patches. No correspondence is required. The patches are filtered using Gaussians and derivatives of Gaussians, and the filters are deformed according to the affine transform. The problem of finding the affine transform is therefore reduced to that of finding the appropriate deformed filter to use. The method is local and can handle large affine deformations. Experiments demonstrate that this technique can find scale changes and optical flow in situations where other methods fail.< >
This paper presents a new method for extracting the 3-D shape and texture of an object undergoing translational motion from image sequences captured through a monocular extra-wide picture viewing angle. The feature of...
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This paper presents a new method for extracting the 3-D shape and texture of an object undergoing translational motion from image sequences captured through a monocular extra-wide picture viewing angle. The feature of this work is extracting this information from image sequences without requiring rigid environmental conditions. In this method, the relative positions between target and view position are estimated based on spatio-temporal image analysis, and shape is reconstructed from the multiple silhouette information. After reconstructing the 3-D shape, the voxel value of a surface point is determined by statistically analyzing those images that contain the surface point. The proposed method can extract 3-D shape and surface texture at a stroke from outdoor scenes. An experiment using real outdoor scenes confirms the effectiveness of the method.< >
We present a method for registering images of complex 3D surfaces that does not require explicit correspondences between features across the images. Our method relies on the use of a full 3D model of the surface to ad...
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We present a method for registering images of complex 3D surfaces that does not require explicit correspondences between features across the images. Our method relies on the use of a full 3D model of the surface to adjust the position and orientation of the camera by minimizing an objective function based on the projections of the images onto the model. This approach constrains the camera parameters strongly enough so that the models do not need, initially, to be accurate to yield good results. When registration has been achieved, the models can be refined and the fine details recovered. Our method is applicable to the calibration of stereo imagery, the precise registration of new images of a scene and the tracking of deformable objects. It can therefore lead to important applications in fields such as augmented reality in a medical context or data compression for transmission purposes. We demonstrate its applicability by using images of faces and of terrain.< >
This paper describes an efficient shape representation framework for planar shapes using Voronoi skeletons. A new algorithm for the construction of the Voronoi diagram of a polygon with holes is first described. The m...
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This paper describes an efficient shape representation framework for planar shapes using Voronoi skeletons. A new algorithm for the construction of the Voronoi diagram of a polygon with holes is first described. The main features of this algorithm are its robustness in handling the standard degenerate cases (colinearity of more than two points; co-circularity of more than three points), and its ease of implementation. This algorithm is then used to derive accurate and robust skeletons for planar shapes. The shape representation scheme using Voronoi skeletons possesses the important properties of connectivity as well as Euclidean metrics. The resultant representation is stable with respect to being invariant to perturbations along the boundary of the shape.< >
Following Sugihara, we represent the geometric constraints imposed by the line-drawing of a polyhedron as a set of linear equalities and inequalities. Unlike him, we explicitly take into account the uncertainty in ver...
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Following Sugihara, we represent the geometric constraints imposed by the line-drawing of a polyhedron as a set of linear equalities and inequalities. Unlike him, we explicitly take into account the uncertainty in vertex position. This allows us to circumvent the superstrictness of the constraints without deleting any of them. For a given error bound, deciding whether a line-drawing is the correct projection of a polyhedron is reduced to linear programming, and 3D shape recovery is reduced to optimization under linear constraints. Our method can be used for recovering the shape of polyhedral objects whose reflectance can be modelled accurately. We have implemented if for the Lambertian model and the Lambertian model with interreflections. We present results obtained using real images.< >
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