A model-based technique is presented for recognizing 3-D objects using a novel object representation and a novel generic matching engine. Each object to be recognized is defined by an appearance model (AM) describing ...
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ISBN:
(纸本)0818620579
A model-based technique is presented for recognizing 3-D objects using a novel object representation and a novel generic matching engine. Each object to be recognized is defined by an appearance model (AM) describing the expected appearances of the object over a range of aspects in a specific type of imagery. The AMs for all the objects to be recognized are organized in an AM hierarchy (AMH) defining object classes. This AMH, together with an image event extracted from the input imagery and primitives obtained by decomposing the event, constitute the input to the matching engine. This engine determines which object in the AMH most likely corresponds to the event and its primitives. The approach described is at the heart of an automatic target recognition system built by the authors.
A model-based vision system is proposed in which a commercial CAD system has been used for object modeling. Assuming that the model is known, the corresponding object in the scene is located. Given the CAD model of an...
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ISBN:
(纸本)0818620617
A model-based vision system is proposed in which a commercial CAD system has been used for object modeling. Assuming that the model is known, the corresponding object in the scene is located. Given the CAD model of an object, certain features of the model are extracted, while others are precalculated and stored. The given dense 3-D range image is segmented into a set of homogeneous surface patches using a recently developed segmentation procedure. Properties such as curvature, surface normal, and surface area are approximated for each surface patch. For each extracted surface patch, three filters are applied to the previously obtained model features to find the best match. Then, a global consistency filter is applied to remove ambiguities and to find the best matched model.
Human subjects easily perceive and extensively use shape regularities such as symmetry or periodicity when they are confronted with the task of object description and recognition. A computer vision algorithm is presen...
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ISBN:
(纸本)0818620579
Human subjects easily perceive and extensively use shape regularities such as symmetry or periodicity when they are confronted with the task of object description and recognition. A computer vision algorithm is presented that emulates such behavior in that it similarly makes use of shape redundancies for the concise description and meaningful segmentation of planar object contours. The contours are analyzed in so-called arc length space. This parameter space facilitates the detection of regularities under a broad range of viewing conditions. Several of the irregularities which have traditionally been treated in isolation, are given a unified substrate for their detection and use in building compact models. Regularity consistency checks are made and, if necessary, altered versions are inferred.
Discontinuities have been important in visual reconstruction to avoid oversmoothing. This work raises the question as to whether location of discontinuities is necessary in this process. The author proposes a class of...
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ISBN:
(纸本)0818620579
Discontinuities have been important in visual reconstruction to avoid oversmoothing. This work raises the question as to whether location of discontinuities is necessary in this process. The author proposes a class of adaptive regularizers (ARs) for reconstruction in the framework of regularization, in an attempt to solve the conflict between 'oversmoothing across discontinuities' and 'finding discontinuities'. The proposal differs from existing methods in the way it controls continuity, in which true discontinuities are considered in the mathematical sense only. A simple analog neuron-like circuit for hardware implementation is suggested. Experimental results are presented.
The problem of finding a path for a mobile robot in two dimensions among stationary obstacles using a free-space graph representation of the robot's workspace is examined. One problem with solutions of this type h...
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ISBN:
(纸本)0818620617
The problem of finding a path for a mobile robot in two dimensions among stationary obstacles using a free-space graph representation of the robot's workspace is examined. One problem with solutions of this type has been the time it takes to construct a graph from the image of the workspace. Two solutions are presented which seek to resolve this situation by constructing the graph representation 'on the fly' in a scanline fashion by processing the image one line at a time from top to bottom. Each method consists of three processes: one which breaks the obstacles in the image into pseudo-obstacles, another which analyzes the pseudo-obstacles and locates regions in the free space which represent nodes in the graph, and a third which completes the graph by locating similarities of the free space regions and uses them as edges. The modularity lends itself toward pipelined processing to reach the solution. Discussions are presented and results given of the graph construction process and the paths found on sample images as well as comparative times.
The issues of integration in a vision and imageprocessing system (VIPS) which has found an increasing number of applications in manufacturing are analyzed. It is pointed out that, to achieve fully integrated systems ...
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ISBN:
(纸本)0818690275
The issues of integration in a vision and imageprocessing system (VIPS) which has found an increasing number of applications in manufacturing are analyzed. It is pointed out that, to achieve fully integrated systems which are seamless and have a uniform occurrence of data and ways to process the data, it is essential that the semantics of components be identified and captured in advance. The semantics of a VIPS are identified in terms of data, processes, and knowledge. The system should have the features of handling large and heterogeneous knowledge bases, the ability to integrate knowledge and data, and a generic knowledge representation scheme. The basic system architecture to meet these features is discussed.
A method is described for segmenting edge data into a combination of straight lines and elliptic arcs. The two-stage process first segments the data into straight line segments. Ellipses are then fitted to the line da...
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ISBN:
(纸本)0818620579
A method is described for segmenting edge data into a combination of straight lines and elliptic arcs. The two-stage process first segments the data into straight line segments. Ellipses are then fitted to the line data. This is much faster than curve fitting directly to pixel data since the lines provide a great reduction in data. Segmentation is performed in the paradigm suggested by D. G. Lowe (1987). A measure of significance is defined that produces a scale-invariant description and allows the replacement of sequences of line segments by ellipses without requiring any thresholds. A method for fitting ellipses to arbitrary curves, essential for this algorithm, has been developed, based on an iterative Kalman filter. This is guaranteed to produce an elliptical fit even though the best conic fit may be a hyperbola or parabola.
The authors propose a hierarchical approach to solving the surface and the vertex correspondence problems in multiple-view-based 3-D object recognition systems. The proposed scheme is a coarse-to-fine search process, ...
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The authors propose a hierarchical approach to solving the surface and the vertex correspondence problems in multiple-view-based 3-D object recognition systems. The proposed scheme is a coarse-to-fine search process, and a Hopfield network is employed at each stage. Compared with the conventional object matching schemes, the proposed technique provides a more general and compact formulation of the problem and a solution more suitable for parallel implementation. At the coarse search stage, the surface matching rates between the input image and each object model in the database are computed through a Hopfield network and used to select the candidates for further consideration. At the fine search stage, the object models selected from the previous stage are fed into another Hopfield network for vertex matching. The object model that has the best surface and vertex correspondences with the input image is finally singled out as the best matched model. Results of experiments using both line drawings and real range images to corroborate the proposed theory are also reported.
A technique is introduced for 3-D surface reconstruction and graphic animation using elastic, deformable models. The basic structure used is an imaginary elastic grid, which is made of membranous, thin-plate type mate...
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ISBN:
(纸本)0818620579
A technique is introduced for 3-D surface reconstruction and graphic animation using elastic, deformable models. The basic structure used is an imaginary elastic grid, which is made of membranous, thin-plate type material. This elastic grid is bent, twisted, compressed, and stretched into any desirable 3-D shape, or from one flexible state to another. The desired shape can be specified by the shape constraints derived automatically from images of a real 3-D object, or by an analytic surface function. Shape reconstruction is guided by a set of imaginary springs that enforce the consistency in the position, orientation, and/or curvature measurements of the elastic grid and the desired shape. The dynamics of a reconstruction process is regulated by Hamilton's principle or the principle of the least action. Implementation results using simple analytic shapes and images of real free-form objects are presented. The authors believe that their model is widely applicable in many surface reconstruction and graphic animation processes.
A range scanner which calculates ranges by triangulation between the incident angles of laser stripes and the positions of their images on a camera sensor was developed for robotic applications. Its originality reside...
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ISBN:
(纸本)0818620617
A range scanner which calculates ranges by triangulation between the incident angles of laser stripes and the positions of their images on a camera sensor was developed for robotic applications. Its originality resides in the use of a solid-state image sensor called Optic RAM instead of a CCD sensor. This sensor chip has three desirable characteristics for the position detection of laser stripes in images: it thresholds the image, detecting only the brighter stripes in binary form;it is an image memory;and pixel values can be addressed randomly in the image. Thus, the design does not require an A/D (analog/digital) converter or a frame buffer and is consequently inexpensive. For improved performance, only the image region next to the previous stripe location is searched, and a 64-KB lookup table stored in RAM is indexed by incident laser angles and stripe addresses to output range data. A 128 × 256 range image is produced in about 20 s. This is reasonably fast considering that this process requires analyzing 256 images. The speed bottleneck is the low sensitivity of the optic RAM chip, which requires a long exposure time per frame (60 ms), corresponding to half the standard video frame rate. Simple calibration methods using planar patterns of parallel lines are presented for calibrating the focal length, the lens distortion, and the mirror position with respect to the camera.
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