Path following for an unmanned vehicle using computer generated and live video images

1995 ◽  
Author(s):  
R.C. Seals
Keyword(s):  
Path Following ◽  
Live Video ◽  
Unmanned Vehicle ◽  
Video Images

Realtime transfer of live video images in parallel with three-dimensional modelling of the surgical field in computer-assisted telesurgery

2002 ◽  
Vol 8 (3) ◽  
pp. 125-130 ◽  
Author(s):  
I Klapan ◽  
Lj Šimičić ◽  
K Pasarić ◽  
A Vlahušić ◽  
R Rišavi ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Computer Assisted ◽  
Live Video ◽  
Video Images ◽  
Surgical Field

An Interactive Digital Fishtank Based on Live Video Images

1999 ◽  
pp. 386-396
Author(s):  
Toshihiro Masaki ◽  
Tetsuya Yamaguchi ◽  
Yoshifumi Kitamura
Keyword(s):  
Live Video ◽  
Video Images

scholarly journals A Print-on-demand System for Producing Instructional and Extension Materials

HortScience ◽  
1995 ◽  
Vol 30 (4) ◽  
pp. 901G-902
Author(s):  
James McConnell ◽  
L. Robert Barber
Keyword(s):  
Digital Images ◽  
Video Camera ◽  
Storage Device ◽  
Mass Storage ◽  
Video Capture ◽  
Final Size ◽  
Live Video ◽  
On Demand ◽  
Video Images ◽  
Print On Demand

A Print-on-Demand (POD) System was developed to expand the availability of printed extension and educational materials. The layouts are developed on a computer using text files and digital images. Images can be edited with graphics programs before insertion into the layouts. The completed materials are stored, in final format, on disk and are printed on an as-needed basis or distributed over computer networks. The system greatly reduces the production time to a finished product and gives great flexibility in revising publications. The basic POD system consists of a computer, a mass storage device, and a printer. Photo CDs and video capture are the most common sources of digital images. Photo CDs produce higher-quality images but require more time to get the digitized images due to commercial processing. For Photo CDs, the images are photographed with a 35-mm camera and sent for processing and digitizing. With live video capture, a video camera is connected directly to a computer and images are digitized in real time. Tape recorded images also can be used, but the image quality is less than live video. Video images are digitized at 72 pixels per inch (ppi), and Photo CD images are available at >3000 ppi. Video images are best digitized at twice their desired size and reduced to final size when increasing the resolution.

scholarly journals Remote Sensing with Internet Based Patient Condition Observing System

2018 ◽  
Vol 9 (3) ◽  
pp. 629
Author(s):  
Pratibhahanmantrao Gaikwad ◽  
Dhiren Pranshankar Dave
Keyword(s):  
Remote Sensing ◽  
Health Professional ◽  
Rural Area ◽  
Diagnostic System ◽  
Medical Data ◽  
Diagnosis And Treatment ◽  
Web Based ◽  
Live Video ◽  
Video Images ◽  
Remote Healthcare

<p>This Paper aims to design and demonstrate an innovative web-based remote healthcare diagnostic system that provides vital medical data and live video images of a patient situated in the rural area accessible to a health professional available elsewhere in urban centres resulting in better diagnosis and treatment of that patient.</p>

Video Digitizing Analysis System

1987 ◽  
Vol 3 (1) ◽  
pp. 80-86 ◽  
Author(s):  
Robert Shapiro ◽  
Chris Blow ◽  
Greg Rash
Keyword(s):  
Video Camera ◽  
Basic Program ◽  
Video Image ◽  
Live Video ◽  
Video Images ◽  
The Mean ◽  
The Cross ◽  
Analysis System ◽  
Set Of Points ◽  
Ibm Pc

The use of video images in biomechanical analyses has become more realistic since the introduction of the shuttered video camera. Although recording rates are still limited to 60 Hz, exposure times can be reduced to prevent blurring in most situations. This paper presents a system for manually digitizing video images, a system that utilizes a video overlay board to place a set of cross hairs directly on a previously recorded or live video image. A cursor is used to move the cross hairs over required points. A BASIC program was written for a IBM PC-AT computer to accomplish this task. Video images of a known set of points were digitized, and calculated distances between points were compared to real distances. The mean of the observed errors was 0.79%. It was concluded that this digitizing system, within the limitations of video resolution, yielded digitizing errors similar in magnitude to those observed in cinematographic analyses.

Computing cell tractions from particle displacements on silicone rubber substrata

1994 ◽  
Vol 52 ◽  
pp. 162-163
Author(s):  
Tim Oliver ◽  
Akira Ishihara ◽  
Ken Jacobsen ◽  
Micah Dembo
Keyword(s):  
Plane Stress ◽  
Linear Elasticity ◽  
Silicone Rubber ◽  
Mathematical Analysis ◽  
Elastic Recovery ◽  
Video Images ◽  
Cell Traction Forces ◽  
Latex Beads ◽  
Cell Traction ◽  
Better Than

In order to better understand the distribution of cell traction forces generated by rapidly locomoting cells, we have applied a mathematical analysis to our modified silicone rubber traction assay, based on the plane stress Green’s function of linear elasticity. To achieve this, we made crosslinked silicone rubber films into which we incorporated many more latex beads than previously possible (Figs. 1 and 6), using a modified airbrush. These films could be deformed by fish keratocytes, were virtually drift-free, and showed better than a 90% elastic recovery to micromanipulation (data not shown). Video images of cells locomoting on these films were recorded. From a pair of images representing the undisturbed and stressed states of the film, we recorded the cell’s outline and the associated displacements of bead centroids using Image-1 (Fig. 1). Next, using our own software, a mesh of quadrilaterals was plotted (Fig. 2) to represent the cell outline and to superimpose on the outline a traction density distribution. The net displacement of each bead in the film was calculated from centroid data and displayed with the mesh outline (Fig. 3).

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