Information Assurance in Sensor Networks

Abstract

Detection and tracking of a varying number of people is very essential in surveillance sensor systems. In the real applications, due to various human appearance and confessors, as well as various environment conditions, multiple targets detection and tracking become even more challenging. During this year, our major contributions of multiple targets detection and tracking are as follows: Firstly, we extend the Particle Filter Gaussian Process Dynamical Model (PF-GPDM) to track multiple targets in complex visual environment. With the PF-GPDM, a high-dimensional training target trajectory data set of the observation space is projected to a low-dimensional latent space through Probabilistic Principal Component Analysis (PPCA), which will then be used to classify test object trajectories, predict the next motion state, and provide Gaussian Process dynamical samples for the particle filter.

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Document Details

Document Type
Technical Report
Publication Date
Sep 15, 2009
Accession Number
ADA523100

Entities

People

  • Hong Man
  • Yafeng Yin

Organizations

  • Stevens Institute of Technology

Tags

Communities of Interest

  • Autonomy
  • Cyber
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Artificial Intelligence Software
  • Change Detection
  • Cognitive Science
  • Computer Languages
  • Computer Vision
  • Data Mining
  • Databases
  • Detectors
  • Information Processing
  • Information Retrieval
  • Information Science
  • Information Systems
  • Machine Learning
  • Network Science
  • Supervised Machine Learning
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Neural Network Machine Learning.
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • Space
  • Space - Space Objects