TENTACLE: Multi-Camera Immersive Surveillance System

Abstract

This final technical report describes the results of collaborative efforts by Primordial, intuVision, and All Hazards Management in conducting a phase I Small Business Innovation Research (SBIR) effort, titled AF103-032: Multicamera real-time Feature Recognition, Extraction &Tagging Automation (McFRETA), and authored by the U.S. Air Force Research Laboratory (AFRL). The goal of the effort was to design, develop, and demonstrate a scalable framework and software application to enable tracking and feature extraction of uncooperative entities capture in multiple streaming sources and enabling near real-time forensic analysis of the extracted data. During the effort, Primordial worked with intuVision to identify key features to extract from live video feeds to include geographic location, entity type, and dominate colors of the entity. Primordial then built a graphical user interface to display avatars representing real world entities in a three dimensional virtual reality using the WorldWind SDK. To prove feasibility of the system, Primordial conducted 13 internal demonstrations to validate the results of the system.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2011
Accession Number
ADA556217

Entities

People

  • Benjamin L. Post
  • Justin W. Benjamin
  • Kyle K. Estes
  • Randy L. Milbert

Tags

Communities of Interest

  • Autonomy
  • C4I
  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Application Software
  • Computer Programming
  • Computer Programs
  • Computer Vision
  • Computers
  • Control Systems
  • Feature Extraction
  • Graphical User Interface
  • Image Processing
  • Information Exchange
  • Network Protocols
  • Pattern Recognition
  • Three Dimensional
  • Unmanned Aerial Vehicles
  • User Interface

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computer Vision.
  • Software Engineering

Technology Areas

  • AI & ML
  • AI & ML - Information Retrieval