Smart Accident Detection and Prevention System (SADPS)

The two objectives of the smart accident detection and prevention system (SADPS) are 1) accident prevention and 2) accident detection. Based on the survey, 1.3 million people die every year due to roadway accidents. The main reason for this type of accident is speeding. So, the proposed SADPS focused on finding the speed parameters of each vehicle and giving notification to speeding vehicles through SMS that can be used to prevent accidents. The second objective is accident detection. For this task, each vehicle accelerometer values will be taken by the SADPS system. When an accident occurs, the location as well as the related details are sent to the SADPS system. This proposed system takes the immediate remedy by alerting the nearby police station and hospitals. Proposed SADPS also acts as a video surveillance and monitoring system. Automatic background subtraction and object tracking is done with the help of novel approaches.

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Moving Object Tracking Algorithm for Complex Shape and Occlusion Handling

International Journal of Engineering and Advanced Technology - Regular Issue ◽

10.35940/ijeat.a1528.109119 ◽

2019 ◽

Vol 9 (1) ◽

pp. 6299-6304

Keyword(s):

Object Tracking ◽

Video Surveillance ◽

Background Subtraction ◽

Traffic Monitoring ◽

Block Matching ◽

Moving Object ◽

Subtraction Method ◽

Matching Algorithm ◽

Block Matching Algorithm ◽

Moving Object Tracking

An object tracking increases loads of enthusiasm for dynamic research in applications such as video surveillance, vehicle navigation, highways, crowded public places, borders, forest and traffic monitoring areas. The system we develop aims to measure and analyze the application of background subtraction method and block matching algorithm to trace object movements through video-based. The making of video surveillance systems “smart” requires fast, reliable and robust algorithms for moving object detection and tracking. This research applies background subtraction method to detect moving object, assisted with block matching algorithm which aims to get good results on objects that have been detected. Performance evaluation is carried out to determine the various parameters. In this paper author design and develop a novel algorithm for moving object tracking in video surveillance also compares and analyse existing algorithms for moving object tracking. Author main aim to design and develop an algorithm for moving object tracking to handle occlusion and complex object shapes.

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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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Development of a Novel Algorithm for Moving Object Tracking in Video Surveillance

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.l2578.1081219 ◽

2019 ◽

Vol 8 (12) ◽

pp. 3394-3401

Keyword(s):

Object Tracking ◽

Video Surveillance ◽

Background Subtraction ◽

Block Matching ◽

Moving Object ◽

Subtraction Method ◽

Matching Algorithm ◽

Block Matching Algorithm ◽

Detection And Tracking ◽

Moving Object Tracking

Video surveillance is a process of analyzing video sequences. It involves analysis, interpretation of object behaviors, as well as object detection and tracking. Video processing plays an important role in the industry and computer vision such as online monitoring of assembly processes, video surveillance security system, medical treatment, robot navigation and military, etc. Detection and tracking of human objects is one of the important studies in improving the ability of the surveillance system. The aim of this research work is to measure and analyze the application of background subtraction method and block matching algorithm to trace object movements through video-based. This research applies background subtraction method to detect moving object, assisted with block matching algorithm which aims to get good results on objects that have been detected. Performance evaluation is carried out to determine the various parameters. In this paper author design and develop a novel algorithm for moving object tracking in video surveillance also compares and analyse existing algorithms for moving object tracking. Author main aim to design and develop an algorithm for moving object tracking to handle occlusion and complex object shapes.

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