TRACKING OF LOW-SIZED TARGETS FROM NON-STATIONARY CAMERA BASED ON COVARIANCE FEATURES AND PREDICTOR

A fast selective-covariance tracking method of low-sized targets from non-stationary camera is proposed. It is based on selective predictor and representation of spatial and statistical target properties by covariance matrix. The comparison of proposed selective-covariance and known covariance metho...

Full description

Saved in:
Bibliographic Details
Main Authors: I. A. Baryskievic, V. Yu. Tsviatkou
Format: Article
Language:Russian
Published: Educational institution «Belarusian State University of Informatics and Radioelectronics» 2019-06-01
Series:Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki
Subjects:
Online Access:https://doklady.bsuir.by/jour/article/view/303
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849398492918710272
author I. A. Baryskievic
V. Yu. Tsviatkou
author_facet I. A. Baryskievic
V. Yu. Tsviatkou
author_sort I. A. Baryskievic
collection DOAJ
description A fast selective-covariance tracking method of low-sized targets from non-stationary camera is proposed. It is based on selective predictor and representation of spatial and statistical target properties by covariance matrix. The comparison of proposed selective-covariance and known covariance methods is provided.
format Article
id doaj-art-93f8078b2a2a4a2eba1936e986bd46e4
institution Kabale University
issn 1729-7648
language Russian
publishDate 2019-06-01
publisher Educational institution «Belarusian State University of Informatics and Radioelectronics»
record_format Article
series Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki
spelling doaj-art-93f8078b2a2a4a2eba1936e986bd46e42025-08-20T03:38:35ZrusEducational institution «Belarusian State University of Informatics and Radioelectronics»Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki1729-76482019-06-01033339302TRACKING OF LOW-SIZED TARGETS FROM NON-STATIONARY CAMERA BASED ON COVARIANCE FEATURES AND PREDICTORI. A. Baryskievic0V. Yu. Tsviatkou1Белорусский государственный университет информатики и радиоэлектроникиБелорусский государственный университет информатики и радиоэлектроникиA fast selective-covariance tracking method of low-sized targets from non-stationary camera is proposed. It is based on selective predictor and representation of spatial and statistical target properties by covariance matrix. The comparison of proposed selective-covariance and known covariance methods is provided.https://doklady.bsuir.by/jour/article/view/303сопровождение малоразмерных целейнестационарная видеокамераковариационная матрицапредсказание
spellingShingle I. A. Baryskievic
V. Yu. Tsviatkou
TRACKING OF LOW-SIZED TARGETS FROM NON-STATIONARY CAMERA BASED ON COVARIANCE FEATURES AND PREDICTOR
Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki
сопровождение малоразмерных целей
нестационарная видеокамера
ковариационная матрица
предсказание
title TRACKING OF LOW-SIZED TARGETS FROM NON-STATIONARY CAMERA BASED ON COVARIANCE FEATURES AND PREDICTOR
title_full TRACKING OF LOW-SIZED TARGETS FROM NON-STATIONARY CAMERA BASED ON COVARIANCE FEATURES AND PREDICTOR
title_fullStr TRACKING OF LOW-SIZED TARGETS FROM NON-STATIONARY CAMERA BASED ON COVARIANCE FEATURES AND PREDICTOR
title_full_unstemmed TRACKING OF LOW-SIZED TARGETS FROM NON-STATIONARY CAMERA BASED ON COVARIANCE FEATURES AND PREDICTOR
title_short TRACKING OF LOW-SIZED TARGETS FROM NON-STATIONARY CAMERA BASED ON COVARIANCE FEATURES AND PREDICTOR
title_sort tracking of low sized targets from non stationary camera based on covariance features and predictor
topic сопровождение малоразмерных целей
нестационарная видеокамера
ковариационная матрица
предсказание
url https://doklady.bsuir.by/jour/article/view/303
work_keys_str_mv AT iabaryskievic trackingoflowsizedtargetsfromnonstationarycamerabasedoncovariancefeaturesandpredictor
AT vyutsviatkou trackingoflowsizedtargetsfromnonstationarycamerabasedoncovariancefeaturesandpredictor