5-9 June 1988 school papers

Binary morphology: working in the sampled domain: A description is given of the relationship between morphologically filtering and then sampling vs. sampling, and then morphologically filtering in the sampled domain. The authors also describe the relationship between morphologically filtering vs. sampling, morphologically filtering in the sampled domain, and then reconstructing. Unlike the standar....; Authors:Haralick;R.M.;Zhuang;X.;Lin;C.;Lee;J.Publisher:Computer Vision and Pattern Recognition;1988. Proceedings CVPR '88.;Computer Society Conference onConference Date:5-9 June 1988ISSN:0-8186-0862-5Total Page:xv+975

An operational perception system for cross-country navigation: The authors present an operational perception system for cross-country navigation which has been verified in both simulated and real-world environments. Range data from a laser range scanner is transformed into an alternate representation called the Cartesian elevation map (CEM). A detailed vehicle model operates on the CEM to produce traversabilit....; Authors:Daily;M.J.;Harris;J.G.;Reiser;K.Publisher:Computer Vision and Pattern Recognition;1988. Proceedings CVPR '88.;Computer Society Conference onConference Date:5-9 June 1988ISSN:0-8186-0862-5Total Page:xv+975

A collision-free navigation scheme in the presence of moving obstacles: A collision-free navigation scheme for an autonomous vehicle is presented. An attempt is made toward establishing a more realistic navigational environment by considering moving obstacles with unknown trajectories. A collision-free path between the current location and a desired location of the vehicle is obtained, based on future positions of the ....; Authors:Kehtarnavaz;N.;Li;S.Publisher:Computer Vision and Pattern Recognition;1988. Proceedings CVPR '88.;Computer Society Conference onConference Date:5-9 June 1988ISSN:0-8186-0862-5Total Page:xv+975

Road finding for road-network extraction: Automatic extraction of roads from aerial photos has been demonstrated in a number of systems, but the systems which display the better capabilities usually rely on manual selection of road starting points. This interaction with a human operator is eliminated by integrating a road-finding module into a road network extraction system. The road finde....; Authors:Aviad;Z.;Carnine;P.D.;Jr.Publisher:Computer Vision and Pattern Recognition;1988. Proceedings CVPR '88.;Computer Society Conference onConference Date:5-9 June 1988ISSN:0-8186-0862-5Total Page:xv+975

An expert vision system for autonomous land vehicle road following: A production-system model of problem solving is applied to the design of a vision system by which an autonomous land vehicle (ALV) navigates roads. The ALV vision task consists of hypothesizing objects in a scene model and verifying these hypotheses using the vehicles sensors. Object hypothesis generation is based on the local navigation task, and ....; Authors:Dickinson;S.J.;Davis;L.S.Publisher:Computer Vision and Pattern Recognition;1988. Proceedings CVPR '88.;Computer Society Conference onConference Date:5-9 June 1988ISSN:0-8186-0862-5Total Page:xv+975

Structural pyramids for representing and locating moving obstacles in visual guidance of navigation: The author presents an image pyramidal approach for representing and locating moving obstacles in the visual guidance of navigation for mobile robots or autonomous land vehicles. The algorithm is based on the utilization of a structural representation of the image in pyramids. A thresholding and mapping scheme for generating the structural pyramids....; Authors:Zhu;Q.Publisher:Computer Vision and Pattern Recognition;1988. Proceedings CVPR '88.;Computer Society Conference onConference Date:5-9 June 1988ISSN:0-8186-0862-5Total Page:xv+975

Vertex space analysis and its application to model based object recognition: The author discusses some of the properties of vertex space, including insensitivity to changes in scale, orientation, and partial object occlusion, and how these properties relate to problems in model-based object recognition. He also describes techniques developed for 2-D and 3-D object recognition using vertex space. The vertex-space approach to....; Authors:Whitten;G.Publisher:Computer Vision and Pattern Recognition;1988. Proceedings CVPR '88.;Computer Society Conference onConference Date:5-9 June 1988ISSN:0-8186-0862-5Total Page:xv+975

CAD based planning and execution of inspection: The authors have created an interface between computer vision processes and CAD (computer-aided design) databases as part of the development of an automated visual inspection system. A recognition planning system uses rules to select the important vision features from the given CAD database and generates feature-recognition procedures. An inspectio....; Authors:Park;H.D.;Mitchell;O.R.Publisher:Computer Vision and Pattern Recognition;1988. Proceedings CVPR '88.;Computer Society Conference onConference Date:5-9 June 1988ISSN:0-8186-0862-5Total Page:xv+975

Parallel bit-level pipelined VLSI processing unit for the histogramming operation: Using the odd-even network topology, a parallel bit-level pipelined VLSI processing unit is designed for the histogramming operation. In this approach, histogramming is divided into two stages, the counting and marking process and the filtering process. The filtering process is computationally inexpensive compared to the counting and marking phase.....; Authors:Abdelguerfi;M.;Sood;A.K.;Khalaf;S.Publisher:Computer Vision and Pattern Recognition;1988. Proceedings CVPR '88.;Computer Society Conference onConference Date:5-9 June 1988ISSN:0-8186-0862-5Total Page:xv+975

Connected component labeling on polymorphic torus architecture: A parallel algorithm is presented for labeling the connected components of multicolored digital images. The algorithm takes advantage of the bottom-up divide-and-conquer strategy applied in tree and pyramid architectures but only requires a mesh topology. To support nonlocal communication, where meshes perform poorly, the authors propose the polymo....; Authors:Maresca;M.;Li;H.;Lavin;M.Publisher:Computer Vision and Pattern Recognition;1988. Proceedings CVPR '88.;Computer Society Conference onConference Date:5-9 June 1988ISSN:0-8186-0862-5Total Page:xv+975

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