Tracking of Objects in Video Sequences

被引：4
|
作者：
Andriyanov, Nikita [1 ]
Dementiev, Vitaly [2 ]
Kondratiev, Dmitry [2 ]
机构：
[1] Financial Univ Govt Russian Federat, Leningradsky Pr T 49, Moscow 125167, Russia
[2] Ulyanovsk State Tech Univ, Severny Venets Str 32, Ulyanovsk 432027, Russia
来源：
INTELLIGENT DECISION TECHNOLOGIES, KES-IDT 2021 | 2021年 / 238卷
关键词：
Trajectory tracking; Neural networks; Pseudo-gradient algorithms; Nonlinear filtering; MODELS;
D O I：
10.1007/978-981-16-2765-1_21
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The paper considers the issues of trajectory tracking of a large number of objects on video images in modes close to real time. To implement such support, a combination of algorithms based on the YOLO v3 convolutional neural network (CNN), doubly stochastic filters and pseudo-gradient procedures for aligning image fragments is proposed. The obtained numerical performance characteristics show the consistency of such a combination and the possibility of its application in real video processing systems.
引用
收藏
页码：253 / 262
页数：10
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