Accession Number:

ADA523100

Title:

Information Assurance in Sensor Networks

Descriptive Note:

Final rept. 30 Aug 2008-30 Sep 2009

Corporate Author:

STEVENS INST OF TECHNOLOGY HOBOKEN NJ DEPT OF ELECTRICAL AND COMPUTER ENGINEERING

Personal Author(s):

Report Date:

2009-09-15

Pagination or Media Count:

95.0

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.

Subject Categories:

  • Computer Systems Management and Standards

Distribution Statement:

APPROVED FOR PUBLIC RELEASE