Distributed Smart Cameras for Aging in Place

Abstract

This paper describes the design and preliminary implementation of two distributed smart camera applications: a fall detector and an object finder. These functions are part of a novel suite of applications being developed to address aging in place health care technologies. Our approach to these applications is unique in that they are based heavily on video data, whereas other solutions may require devices that must be worn or attached to objects. The fall detector relies on features extracted from video by the camera nodes, which are sent to a central processing node where one of several machine learning techniques are applied to detect a fall. If a fall is detected, alerts are triggered both in the home and to a third party. The object finder similarly uses a boosted cascade of classifiers to visually recognize objects either by request of the user or automatically when an object is moved.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2006
Accession Number
ADA459913

Entities

People

  • Adam Williams
  • Allen Hanson
  • Dan Xie
  • Edward M. Riseman
  • Roderic Grupen
  • Shichao Ou

Organizations

  • University of Massachusetts Amherst

Tags

Communities of Interest

  • Biomedical
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Artificial Intelligence Software
  • Automata Theory
  • Change Detection
  • Computational Science
  • Computer Vision
  • Computers
  • Detection
  • Detectors
  • Energy Management
  • Hidden Markov Models
  • Machine Learning
  • Mobile Phones
  • Object Recognition
  • Recognition
  • Sensor Networks
  • Supervised Machine Learning
  • Wireless Sensor Networks

Fields of Study

  • Computer science

Readers

  • Image Processing and Computer Vision.
  • Sensor Fusion and Tracking Systems.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy