Motion detection based on the combining of the background subtraction and spatial color information

Motion Detection of Webcam Using Frame Differencing Method

Research Journal of Engineering and Technology ◽

10.52711/2321-581x.2021.00006 ◽

2021 ◽

pp. 32-38

Author(s):

Pooja Nagpal ◽

Shalini Bhaskar Bajaj ◽

Aman Jatain ◽

Sarika Chaudhary

Keyword(s):

Machine Learning ◽

Motion Detection ◽

Background Subtraction ◽

Surveillance System ◽

Detection Algorithm ◽

Alert Message ◽

Object Level

It is the capability of humans and as well as vehicles to automatically detect object level motion that results into collision less navigation and also provides sense of situation. This paper presents a technique for secure object level motion detection which yields more accurate results. To achieve this, python code has been used along with various machine learning libraries. The detection algorithm uses the advantage of background subtraction and fed in data to detect even the slightest movement this system makes use of a webcam to scan a premise and detect movement of any sort; on the recognition of any activity it immediately sends an alert message to the owner of the system via mail. Any person requiring a surveillance system can use it.

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A Light Weight Background Subtraction Algorithm for Motion Detection in Fog Computing

Letters of the IEEE Computer Society ◽

10.1109/locs.2020.2974703 ◽

2020 ◽

Vol 3 (1) ◽

pp. 17-20

Author(s):

R. Siddharth ◽

G. Aghila

Keyword(s):

Motion Detection ◽

Background Subtraction ◽

Fog Computing ◽

Light Weight

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Abnormal Motion Detection for Intelligent Video Surveillance

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.58-60.2290 ◽

2011 ◽

Vol 58-60 ◽

pp. 2290-2295 ◽

Cited By ~ 1

Author(s):

Ruo Hong Huan ◽

Xiao Mei Tang ◽

Zhe Hu Wang ◽

Qing Zhang Chen

Keyword(s):

Kalman Filter ◽

Object Tracking ◽

Video Surveillance ◽

Motion Detection ◽

Background Subtraction ◽

Moving Objects ◽

Video Streams ◽

Intelligent Video Surveillance ◽

Tracking Process ◽

Object Parameters

A method of abnormal motion detection for intelligent video surveillance is presented, which includes object intrusion detection, object overlong stay detection and object overpopulation detection. Background subtraction algorithm is used to detect moving objects in video streams. Kalman filter is applied for object tracking. By the construction of relation matrix, the tracking process is divided into five statuses for prediction and estimation, which are object disappearing, object separating, new object appearing, object sheltering and object matching. The object parameters and predictive information in the next frame which is used to track moving objects is established by Kalman filter. Then, three types of abnormal motion detection are implemented. The relative position of alarm area or guard line with the rectangle boxes of the moving objects is used to detect whether the object is invading. The existing time of the moving objects in monitor area is counted to detect whether the object is staying too long. Moving objects in the monitor area are classified and counted to detect whether the objects are too much. Alarm will be triggered when abnormal motion detection as defined is detected in the monitor area.

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Review of Human Motion Detection based on Background Subtraction Techniques

International Journal of Computer Applications ◽

10.5120/21757-4988 ◽

2015 ◽

Vol 122 (13) ◽

pp. 1-5 ◽

Cited By ~ 5

Author(s):

Arwa DarwishAlzughaibi ◽

Hanadi Ahmed Hakami ◽

Zenon Chaczko

Keyword(s):

Motion Detection ◽

Background Subtraction ◽

Human Motion ◽

Human Motion Detection

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Space Monitoring System Using the Background Subtraction Method with Whatsapp Notifications

Jurnal Jartel Jurnal Jaringan Telekomunikasi ◽

10.33795/jartel.v5i2.199 ◽

2017 ◽

Vol 5 (2) ◽

pp. 15-20

Author(s):

Reza Aulia

Keyword(s):

Quality Of Service ◽

Light Intensity ◽

Motion Detection ◽

Background Subtraction ◽

Mobile Network ◽

Fire Detection ◽

Subtraction Method ◽

Service Testing ◽

Detection Program

This research was carried out by monitoring space using the background subtraction method with WhatsApp notifications, with features that make a system that can work and can help security and safety. The testing of this research is the effect of light intensity, the diversity of objects with different distances on motion detection and fire detection, WhatsApp notification delay testing and Quality of Service streaming networks on the website. From the results of the system testing carried out, the test results show that the light intensity used in the motion detection program must be more than 0 lux and objects that are too small are not defined as motion, fire detection can work at lux 8.33 and 25, delay in sending notifications is the same - equally good, when using a mobile network or FTTH, for delay in QOS (Quality of Service) testing it is in the very bad category, namely 0.99 Second, the resulting throughtput is 1048.53 Bytes / second on average and Packet loss is categorized as good in ITU -T with a value of 0%.

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