DEKF SYSTEM FRO CROWDING ESTIMATION BY A MULTIPLE-MODEL APPROACH

被引：7

作者：

CRAVINO, F

DELLUCCA, M

TESEI, A

机构：

[1] Department of Biophysical and Electronic Engineering (DIBE), University of Genoa, 16145 Genova, Via all’Opera Pia 11A,I

来源：

ELECTRONICS LETTERS | 1994年 / 30卷 / 05期

关键词：

IMAGE PROCESSING; KALMAN FILTERS;

D O I：

10.1049/el:19940280

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

A distributed extended Kalman filter (DEKF) network devoted to real-time crowding estimation for surveillance in complex scenes is presented. Estimation is carried out by extracting a set of significant features from sequences of images. Feature values are associated by virtual sensors with the estimated number of people using nonlinear models obtained in an off-line training phase. Different models are used, depending on the positions and dimensions of the crowded subareas detected in each image.

引用

页码：390 / 391

页数：2