Author: Pennsylvania State Data CenterPublisher:
ISBN: 9781885925787
Category :
Languages : en
Pages : 301
Book Description
1996 Pennsylvania Abstract
Author: Pennsylvania State Data CenterPublisher:
ISBN: 9781885925787
Category :
Languages : en
Pages : 301
Book Description
1996
Author: Pennsylvania Abstract
Author: 27th Annual Meeting
Author: Alan BoultonAbstracts, 27th Annual Meeting : Philadelphia, Pennsylvania, March 2-6, 1996
Author: American Society for NeurochemistryPublisher:
ISBN:
Category :
Languages : en
Pages : 113
Book Description
Statistical Abstract of the United States
Author: Pennsylvania in Public Memory
Author: Carolyn KitchPublisher: Penn State Press
ISBN: 027106885X
Category : History
Languages : en
Pages : 434
Book Description
What stories do we tell about America’s once-great industries at a time when they are fading from the landscape? Pennsylvania in Public Memory attempts to answer that question, exploring the emergence of a heritage culture of industry and its loss through the lens of its most representative industrial state. Based on news coverage, interviews, and more than two hundred heritage sites, this book traces the narrative themes that shape modern public memory of coal, steel, railroading, lumber, oil, and agriculture, and that collectively tell a story about national as well as local identity in a changing social and economic world.
Scientific Program and Abstracts
Author: Society for Gynecologic InvestigationPublisher:
ISBN:
Category :
Languages : en
Pages : 402
Book Description
Pennsylvania Abstract
Author: Front-End Vision and Multi-Scale Image Analysis
Author: Bart M. Haar RomenyPublisher: Springer Science & Business Media
ISBN: 140208840X
Category : Computers
Languages : en
Pages : 470
Book Description
Many approaches have been proposed to solve the problem of finding the optic flow field of an image sequence. Three major classes of optic flow computation techniques can discriminated (see for a good overview Beauchemin and Barron IBeauchemin19951): gradient based (or differential) methods; phase based (or frequency domain) methods; correlation based (or area) methods; feature point (or sparse data) tracking methods; In this chapter we compute the optic flow as a dense optic flow field with a multi scale differential method. The method, originally proposed by Florack and Nielsen [Florack1998a] is known as the Multiscale Optic Flow Constrain Equation (MOFCE). This is a scale space version of the well known computer vision implementation of the optic flow constraint equation, as originally proposed by Horn and Schunck [Horn1981]. This scale space variation, as usual, consists of the introduction of the aperture of the observation in the process. The application to stereo has been described by Maas et al. [Maas 1995a, Maas 1996a]. Of course, difficulties arise when structure emerges or disappears, such as with occlusion, cloud formation etc. Then knowledge is needed about the processes and objects involved. In this chapter we focus on the scale space approach to the local measurement of optic flow, as we may expect the visual front end to do. 17. 2 Motion detection with pairs of receptive fields As a biologically motivated start, we begin with discussing some neurophysiological findings in the visual system with respect to motion detection.