Multi-camera Human Tracking via Clustering.

Accession Number

ADA558220

Publication Date

Nov 2011

Media Count

19p

Personal Author

D. Kamenetsky

Abstract

We describe an efficient method for tracking humans in a multi- camera network. Based on online clustering, the proposed method groups single- camera tracks into mutually exclusive subsets corresponding to individuals. Experiments indicate that the algorithm is capable of achieving strong tracking accuracy on simulated data.

Keywords

Algorithms
Australia
Cameras
Clustering
Efficiency
Foreign reports
Humans
Online systems
Tracking


$33.00-COLOR DOCUMENT

Source Agency

Non Paid ADAS

NTIS Subject Category

72B - Algebra, Analysis, Geometry, & Mathematical Logic
82B - Photographic Techniques & Equipment

Corporate Author

Defence Science and Technology Organisation, Edinburgh, (Australia).

Document Type

Technical report

Title Note

Technical rept.

NTIS Issue Number

1218

Contract Number

N/A

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