image deformations due to relative motion between an observer and an object maybe used to infer 3-D structure. Up to first order these deformations can be written in terms of an affine ***, a novel approach is adopted...
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ISBN:
(纸本)0818638826
image deformations due to relative motion between an observer and an object maybe used to infer 3-D structure. Up to first order these deformations can be written in terms of an affine ***, a novel approach is adopted to measuring affine transforms which correctly handles the problem of corresponding deformed patches. The patches are filtered using gaussians and derivatives of gaussians and the filters 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. In the special case where the affine transform can be written as a scale change and an in-plane rotation, the gaussian and first derivative equations have been solved for the scale. This case arises frequently in robot navigation. The robustness of the method has been demonstrated experimentally.
Attitude is the 3-D rotation between the coordinate system of a known object and that of a sensed portion of its surface. Combinations of the support function of a known object with curvature measurements from a visib...
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ISBN:
(纸本)0818638826
Attitude is the 3-D rotation between the coordinate system of a known object and that of a sensed portion of its surface. Combinations of the support function of a known object with curvature measurements from a visible surface transform attitude determination into optimization problems that can be solved using standard numerical methods. Previous work using the Extended Gaussian image (EGI) defined for convex polyhedra is extended to the domain of smooth, strictly convex objects where the EGI becomes equivalent to the second curvature function. 3-D shape matching using the first curvature function is new. The paper highlights theoretical foundations, algorithm development and experimental proof-of-concept using real objects and surface data obtained from an existing photometric stereo system.
In a manufacturing environment, objects are often presented to inspection systems via conveyor belts. If multiple snapshots of a moving object are taken by a fired camera, the motion of the belt provides the necessary...
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ISBN:
(纸本)0818638826
In a manufacturing environment, objects are often presented to inspection systems via conveyor belts. If multiple snapshots of a moving object are taken by a fired camera, the motion of the belt provides the necessary stereo disparity. This method is called motion stereo. A simple parallel algorithm for calculating depths from motion stereo was implemented which makes the assumption that the incremental disparity is less than the minimum distance between edges. To relax this constraint, a more general multi-scale pyramidal algorithm is developed. The two algorithms have been tested on the SFU pyramidal vision machine which was recently completed for real-time computer vision applications. the total processing.time was 50 msec per image for the simple algorithm and approximately 0.5 seconds per image for the multi-scale algorithm.
A distance transformation is to convert a digital binary image that consists of object (foreground) and nonobject (background) pixels into a gray-scale image in which each object pixel has a value corresponding to the...
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ISBN:
(纸本)0818638826
A distance transformation is to convert a digital binary image that consists of object (foreground) and nonobject (background) pixels into a gray-scale image in which each object pixel has a value corresponding to the minimum distance from the background by a distance function. Since the Euclidean distance measurement has metric accuracy as in the continuous case and possesses rotation invariance, it is very useful in image analysis and object inspection. Unfortunately, due to its nonlinearity, the global operation of Euclidean distance transformation (EDT) is difficult to decompose into small neighborhood operations. This paper presents two novel efficient algorithms on EDT using integers of squared Euclidean distances in which the global computations can be equivalent to local 3 × 3 neighborhood operations. The first algorithm requires only a limited number of iterations on the chain propagation;however, the second algorithm can avoid iterations and simply requires two scans of the image. The complexity of both algorithms is achieved to be only linearly proportional to image size.
We address the problem of adaptive segmentation of images of objects with smooth surfaces. The images are composed of regions of slowly varying intensities that may be corrupted by additive noise. The underlying field...
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ISBN:
(纸本)0818638826
We address the problem of adaptive segmentation of images of objects with smooth surfaces. The images are composed of regions of slowly varying intensities that may be corrupted by additive noise. The underlying field is modelled by a Markov random field that consists of both a label process which contains the classification of each pixel in the image and intensity functions which contain the possible grey levels that each pixel may take. The algorithm iteratively repeats two steps;(a) the parameter estimation step, in which the ML estimates of the associated parameters are obtained, and (b) the restoration step, in which the underlying field is estimated through the MAP method. The major contribution of this paper is the idea of allowing the pixel grey values to vary across the image regions. These values are estimated by using windows on the observed data and, as the algorithm progresses, the window size is decreased so that the algorithm adapts to the characteristics of each region.
This work is concerned with the problem of recovering the 3-dimensional motion of a non-rigid object from a sequence of stereo images. The object undergoes uniform expansion and 3-dimensional shearing about an unknown...
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ISBN:
(纸本)0818638826
This work is concerned with the problem of recovering the 3-dimensional motion of a non-rigid object from a sequence of stereo images. The object undergoes uniform expansion and 3-dimensional shearing about an unknown point in space, in addition to being subjected to rigid motion. We assume feature correspondence over multiple frames. We reduce the problem of recovering the 3-dimensional motion uniquely to the (unique) solution of a set of homogeneous polynomial equations using algebraic geometry, the commutative algebra software package MACAULAY and the Fortran polynomial continuation program POLSYS. We show that, with four points correspondence, only two (stereo) snapshots are needed to determine the motion uniquely.
A new method for acquiring time-sequential range images is proposed. Stereo pairs of thermal and intensity images are synchronously acquired and are mutually registered. Stereo thermal images are segmented into isotem...
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ISBN:
(纸本)0818638826
A new method for acquiring time-sequential range images is proposed. Stereo pairs of thermal and intensity images are synchronously acquired and are mutually registered. Stereo thermal images are segmented into isotemperature regions. Then, contour based matching is done for the isotemperature regions, To supplement matching, dynamic programming matching is performed for either intensity profile or edges in the stereo intensity images. By corresponding pixel pairs obtained from the matching processes, the 3D coordinates of the points can be calculated. Experiments with real scenes having moving human beings show promising results.
This paper presents a method to obtain the optimal motion description from two consecutive images including multiple moving parts. It copes with segmentation and motion estimation problems which resemble the well know...
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ISBN:
(纸本)0818638826
This paper presents a method to obtain the optimal motion description from two consecutive images including multiple moving parts. It copes with segmentation and motion estimation problems which resemble the well known `chicken and egg' relation. `Segmentation' is necessary for `motion estimation' of each part, and vice versa. Unlike previous approaches based on the motion similarity between two pixels, we propose to use an information measure approach, based on comparisons between an individual (or pixel) and a class (or set of pixels). First, the motion of an edge segment is optimally modeled. Next, merging and splitting processes are iterated until the minimum description is obtained for the whole image. As a result, the image is segmented into several regions, each of which is represented by an edge segment list, and at the same time, the maximum likelihood motion estimation is obtained for each region. Experiments performed on real images are shown.
This paper describes a qualitative approach to quantitative recovery of shape and pose of a straight homogeneous generalized cylinder (hereafter SHGC) based on a `weak Lambertian assumption' which relaxes the stri...
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ISBN:
(纸本)0818638826
This paper describes a qualitative approach to quantitative recovery of shape and pose of a straight homogeneous generalized cylinder (hereafter SHGC) based on a `weak Lambertian assumption' which relaxes the strict cosine law of Lambertian reflection model. The method does not need to know the lighting condition or surface albedos. First, the image of the projection of the axis of an SHGC is extracted. Next, we estimate the slant angle of the SHGC using the weak Lambertian assumption along an external cross-section curve. Finally, we obtain the location of the SHGC's 3D axis on other parallels. As a result,, we recover the pose (slant and tilt) and the shape (the shape of the cross-section the location of the axis, and the sweeping function) of an SHGC. The experimental results for both synthesized and real images are shown.
Estimating 3-D motion parameters from the three-dimensional point correspondences is considered in this paper. A minimum errors-in-variable formulation of the motion estimation problem is developed to obtain stable an...
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ISBN:
(纸本)0818638826
Estimating 3-D motion parameters from the three-dimensional point correspondences is considered in this paper. A minimum errors-in-variable formulation of the motion estimation problem is developed to obtain stable and accurate solutions and connected with the ordinary least squares formulation of the problem. When covariance matrices of 3-D points are known, a closed form matrix-weighted solution is derived for estimating the motion parameters in the presence of i.i.d. Gaussian noise. In a general case, a closed form approximate solution is also presented. The solutions extend two solutions proposed by Horn et al. and by Arun et al., respectively. The experimental results demonstrate that our solutions are accurate and reliable in presence of noise with different deviation.
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