Review of algorithms for Tag Detection in video sequences

被引：0

作者：

Klempous, Ryszard ^{[1
]}

Kluwak, Konrad ^{[1
]}

Nikodem, Jan ^{[1
]}

Kulbacki, Marek ^{[2
,3
]}

Segen, Jakub ^{[2
,3
]}

Kniec, Wojciech ^{[2
,3
]}

Serester, Andrea ^{[4
]}

机构：

[1] Wroclaw Univ Sci & Technol, Fac Elect, Wroclaw, Poland

[2] Polish Japanese Acad Informat Technol, R&D Ctr, Warsaw, Poland

[3] DIVE IN AI, Wroclaw, Poland

[4] Obuda Univ, Antal Bejczy Ctr Intelligent Robot, Budapest, Hungary

来源：

2018 IEEE 22ND INTERNATIONAL CONFERENCE ON INTELLIGENT ENGINEERING SYSTEMS (INES 2018) | 2018年

关键词：

EMOTION RECOGNITION; PICTORIAL STRUCTURES; SURVEILLANCE; CONSTRAINTS; MOVEMENT;

D O I：

暂无

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：

Detecting moving objects in video sequences may be particularly challenging because of the characteristics of the objects, such as their size, colour, contrast, velocity and trajectory. Industrial video tagging systems should generate tags based on information inferred from video frames and learn relations between given concepts. In opposite to traditional methods such systems should effectively segment semantic objects in tagged videos, even when the image-based object detectors provide inaccurate proposals. Such systems usually base on the knowledge which is constantly updated to acquire the dynamics of the indexed concepts. In this paper we present a short review of the most importants algorithms for detection of markers in video sequences and problems related with practical applications.

引用

页码：359 / 363

页数：5

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