Showing papers on "3D reconstruction published in 1986"
Book•
01 Jan 1986
TL;DR: This chapter discusses three-Dimensional Shape Representation, Relational Matching, and Machine Learning of Computer Vision Algorithms for 3D Perception of Dynamic Scenes.
Abstract: Principles of Computer Vision. Three-Dimensional Shape Representation. Three-Dimensional Shape Recovery from Line Drawings. Recovery of 3D Shape of Curved Objects. Surface Reflection Mechanism. Extracting Shape from Shading. Range Image Analysis. Stereo Vision. Machine Learning of Computer Vision Algorithms. Image Sequence Analysis for 3D Perception of Dynamic Scenes. Nonrigid Motion Analysis. Analysis and Synthesis of Human Movement. Relational Matching. Three-Dimensional Object Recognition. Fundamental Principles of Robot Vision. Chapter References.
454 citations
40 citations
25 citations
TL;DR: Volume 1, 1984, Image Reconstruction from Incomplete Observations.
Abstract: (1986). Advances in Computer Vision and Image Processing.Volume 1, 1984, Image Reconstruction from Incomplete Observations. Optica Acta: International Journal of Optics: Vol. 33, No. 6, pp. 685-685.
16 citations
TL;DR: The successful three-dimensional reconstruction of capillary modules using digital image processing techniques for capillary feature detection/extraction, for construction of montages of overlapping images of the same section, and for automatic image registration by two independent methods without the use of fiducial marks are reported.
13 citations
07 Apr 1986
TL;DR: This paper introduces a technique called the spherical dual image, derived from Gaussian sphere and dual space concepts, leading to a reconstruction algorithm for convex and concave polyhedra.
Abstract: Three-dimensional object representation significantly impacts computations for manipulation, spatial reasoning and vision. This paper introduces a technique called the spherical dual image, derived from Gaussian sphere and dual space concepts. This representation technique will be defined and a number of its properties will be proven, leading to a reconstruction algorithm for convex and concave polyhedra. Finally, the application of this representation for selecting grasping points to manipulate a polyhedron is discussed.
11 citations
26 Mar 1986
TL;DR: The CARTOS-ACE neuron tracing system developed at Columbia University and the program TRACER-1, which reconstructs the three-dimensional structure of a neuron from a series of two-dimensional cross sectional images is described.
Abstract: Neuron tracing of serial sections is the process of reconstructing the three-dimensional structure of a neuron from a series of two-dimensional cross sectional images. Automatic neuron tracing is a challenging computer vision problem. This paper first describes the CARTOS-ACE neuron tracing system developed at Columbia University. It then describes the program TRACER-1 and presents a detailed example of its execution. It then examines TRACER-1's performance more generally and discusses further improvements, many of which will require encoding more knowledge into the next version of the program.
5 citations
01 Jan 1986
TL;DR: A robust stereo algorithm solving the correspondence problem in an indirect way and providing, for each stereo pair, a disparity map of low resolution allows the extraction of a 3D description of the objects present in the scene.
Abstract: This paper describes a method to obtain a volumeric representation of objects from multiple stereo pairs The procedure is based on a robust stereo algorithm solving the correspondence problem in an indirect way and providing, for each stereo pair, a disparity map of low resolution The integration of the depth information computed from stereo pairs acquired from many positions in space, allows the extraction of a 3D description of the objects present in the scene Such description is a volumetric image whose elements (voxels) represent a 3D portion of space The relevance of such explicit 3D representation with respect to image understanding is also discussed
3 citations
01 Jan 1986
TL;DR: An interesting extension of present pattern recognition and image processing technologies is to apply them to spatio-temporal series of images to support embryogenesis study of nematodes.
Abstract: An interesting extension of present pattern recognition and image processing technologies is to apply them to spatio-temporal series of images. A project is ongoing to develop hardware and software to study three dimensional images in biomedicine. The primary goal is to support embryogenesis study of nematodes. The system has been developed on VAX 11/750 and PDP 11/70. Currently two dimensional optical dissect images are analized interactively, and reconstructed into three dimensional cellular images.
3 citations
01 Apr 1986
TL;DR: A hidden feature elimination algorithm based on ray tracing through an octree is presented and is used in a model-based vision system for a robot which services numerically controlled machine tools in an automated factory.
Abstract: A hidden feature elimination algorithm based on ray tracing through an octree is presented. The algorithm has been used in a model-based vision system for a robot which services numerically controlled machine tools in an automated factory. It determines which features of an object are visible from a given camera location. This prediction is used by the model-based vision system to keep the 3-D world model as close as possible to reality. Finally the effect of the resolution limitations of the octree on the algorithm is discussed.
3 citations
01 Jan 1986
TL;DR: An investigation of the relative speed and effectiveness of two computer vision algorithms has been conducted and the two-level algorithm was found to be up to 90% faster than the one-level one.
Abstract: An investigation of the relative speed and effectiveness of two computer vision algorithms has been conducted. One algorithm incorporates a two-level data hierarchy. The other incorporates a one-level hierarchy and serves as a relatively conventional basis for comparison. The computer vision algorithms, programmed in Fortran, detect and recognize a moving square. Both computer vision algorithms could readily be implemented in existing hardware. The two-level algorithm was found to be up to 90% faster than the one-level
01 Sep 1986
TL;DR: This work has developed a system called LANDSCAN, which is an integrated vision system and the recognition process is knowledge driven, and the knowledge is generated by a query in English.
Abstract: : We have developed a system called LANDSCAN, which is an integrated vision system and the recognition process is knowledge driven. This knowledge is generated by a query in English. The visual information is a stereo pair of images, and the description are being made on 3-dimensional information. Keywords: Computer applications, Image processing, Optical images, Natural language, Computer vision, Knowledge driven recognition, Scene analysis.
01 Jan 1986
TL;DR: A stereo vision model in conjunction with evidences from neurophysiology of the human binocular system is established and a computationally efficient algorithm to implement this model is developed.
Abstract: In computer vision, the idea of using stereo cameras for depth perception has been motivated by the fact that in human vision one perception can arise from two retinal images as a result of a process called 'fusion' Nevertheless, most of the stereo algorithms are generally concerned with finding a solution to obtaining depth and three-dimensional shape irrespective of its relevance to the human system Recent progress in the study of the brain mechanisms of vision has opened new vistas in computer vision research This paper investigates this knowledge base and its applicability to improving the technique of computer stereo vision In this regard, (1) a stereo vision model in conjunction with evidences from neurophysiology of the human binocular system is established herein; (2) a computationally efficient algorithm to implement this model is developed This algorithm has been tested on both computer generated and real scene images The results from all directional sub-images are combined to obtain a complete description of the target surface from disparity measurement