Person Tracking and Counting System Using Motion Vector Analysis for Crowd Steering

被引:0
|
作者
Sujatha, K. [1 ]
Raju, S. V. S. V. P. Rama [1 ]
Rao, P. V. Nageswara [2 ]
Rao, A. Arjuna [3 ]
Shyamanth, K. [4 ]
机构
[1] Dadi Inst Engn & Technol, CSE Dept, Visakhapatnam, Andhra Pradesh, India
[2] GITAM Univ, CSE Dept, Visakhapatnam, Andhra Pradesh, India
[3] Miracle Educ Soc Grp Inst, Visakhapatnam, Andhra Pradesh, India
[4] Andhra Univ, Visakhapatnam, Andhra Pradesh, India
来源
PROCEEDINGS OF INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND DATA ENGINEERING (ICCIDE 2018) | 2019年 / 28卷
关键词
Video surveillance; Sensitive areas; Motion vector analysis; Moving person detection and tracking; Background subtraction; Person counting;
D O I
10.1007/978-981-13-6459-4_25
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Video surveillance has been in use since a protracted time as an assistance to beat security and other problems. Historically, the video outputs area unit monitored by human operators and area unit sometimes saved to tapes for later use. Sensitive areas like shopping malls, banks, huddled public places want a strict police investigation and may require management of the flow of individuals mechanically. To do such automation, a wise video closed-circuit television is required for today's world equipped with machine learning algorithms. In this project, a sensible visual closed-circuit television with person detection and following capabilities is bestowed. This can be used to regulate the flow of persons into the sensitive areas, which is often achieved by count the persons who are getting into and going through these areas, so knowing the overall capability a sensitive space is holing at any specific purpose of your time. Motion vector analysis is that the main construct that is used here to realize the following of the persons. This has a tendency to count the persons who are getting into and going out stationary cameras fixed points, the capability is obtained as distinction between the count of the persons entered and count of the persons who left the sensitive space. Any sensitive space would have a restricted house to accommodate. So it is necessary to prohibit the persons from getting into sensitive space, once the capability is reached to threshold price.
引用
收藏
页码:249 / 256
页数:8
相关论文
共 8 条
  • [1] Abnormal Crowd Tracking and Motion Analysis
    Santhiya, G.
    Sankaragomathi, K.
    Selvarani, S.
    Kumar, A. Niranjil
    2014 INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES (ICACCCT), 2014, : 1300 - 1304
  • [2] CROWD ANALYSIS IN NON-STATIC CAMERAS USING FEATURE TRACKING AND MULTI-PERSON DENSITY
    Senst, Tobias
    Eiselein, Volker
    Keller, Ivo
    Sikora, Thomas
    2014 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2014, : 6041 - 6045
  • [3] PERSON COUNTING SYSTEM USING EFV SEGMENTATION AND FUZZY LOGIC
    Sivabalakrishnan, M.
    Shanthi, K.
    BIG DATA, CLOUD AND COMPUTING CHALLENGES, 2015, 50 : 572 - 578
  • [4] Multiple-person tracking system for content analysis
    Hsieh, JW
    Huang, YS
    INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2002, 16 (04) : 447 - 462
  • [5] Subjective analysis of social distance monitoring using YOLO v3 architecture and crowd tracking system
    Ozbek, Muhammed Murat
    Syed, Mustafa
    Oksuz, Ilkay
    TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, 2021, 29 (02) : 1157 - 1170
  • [6] Real-time detection of passing objects using virtual gate and motion vector analysis
    Lin, Daw-Tung
    Liu, Li-Wei
    UBIQUITOUS INTELLIGENCE AND COMPUTING, PROCEEDINGS, 2008, 5061 : 710 - 719
  • [7] Motion detection and tracking using belief indicators for an automatic visual-surveillance system
    Motamed, Cina
    IMAGE AND VISION COMPUTING, 2006, 24 (11) : 1192 - 1201
  • [8] ADAPTIVE ERROR CONCEALMENT FOR MULTIPLE DESCRIPTION VIDEO CODING USING MOTION VECTOR ANALYSIS
    Gadgil, Neeraj
    Yang, Meilin
    Comer, Mary L.
    Delp, Edward J.
    2012 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP 2012), 2012, : 1637 - 1640