A Scalable Video Rate Camera Interface

Abstract

We survey the state of the art in high-speed interfaces for video input to high performance computers and note the difficulty of providing video at rates appropriate to modern parallel computers. Most interfaces that have been developed to date are not scalable, required extensive hardware development, and impose a full frame time delay between the moment the camera captures video and the moment it is available for processing. We propose a solution, based on a simple interface we have developed, which has been integrated into the iWarp parallel computer developed by Carnegie Mellon University and Intel Corporation. The interface takes advantage of iWarp's systolic capabilities, does not impose any frame buffer delay time, was simple to design, and is readily scalable to provide up to 32 camera ports, from all of which data can be captured at full video rate, on a system that fits in a 19' 6U rack. We have applied the system to multibaseline stereo vision, and provide performance figures. C.1.2 Multiple-instruction-stream, Multiple-data stream processors, Parallel processors, C.3 Real-time systems, 1.2.10 Vision and scene understanding, 1.2.9 Robotics, 1.3.1 Input devices, 1.4.1 Digitization, 1.4.2 Compression.

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Document Details

Document Type
Technical Report
Publication Date
Sep 26, 1994
Accession Number
ADA286144

Entities

People

  • Jon A. Webb
  • Sing B. Kang
  • Thomas Warfel

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Acquisition
  • Bandwidth
  • Cameras
  • Clocks
  • Computer Science
  • Computer Stereo Vision
  • Computer Vision
  • Computers
  • Control
  • High Resolution
  • Host Computers
  • Images
  • Load Monitoring
  • Operating Systems
  • Television Cameras
  • Video
  • Video Signals

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Parallel and Distributed Computing.
  • Software Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Autonomy