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Approaches to moving object detection and parameter estimation in a video sequence for the transport analysis system
- Source :
- Компьютерная оптика, Vol 44, Iss 5, Pp 746-756 (2020)
- Publication Year :
- 2020
- Publisher :
- Samara National Research University, 2020.
-
Abstract
- The paper discusses different approaches to image and video processing aiming to solve the problems of detecting, tracking and estimating the parameters of moving objects. The developed algorithms for solving these problems are described in relation to the field of transport analytics. When developing the algorithms, attention was given to solving the problems on an embedded platform of video surveillance cameras, which imposes restrictions on the computational complexity. The first (basic) algorithm for moving object detection and parameter estimation is based on processing two associated areas of an image. This algorithm includes a computationally efficient adaptive procedure for evaluating and updating the background component of an image. The procedure is based on the physics of the process of movement of the object of interest through a processing zone. The second algorithm performs object tracking based on an optical flow method initialized by feature points. The third algorithm is based on object segment tracking and is computationally efficient for the implementation on an embedded platform of intelligent cameras. Results of experimental studies of the proposed algorithms are presented, as well as a comparison with some well-known algorithms. It is shown that tracking algorithms can improve the accuracy of moving object parameter estimation. Tracking also reduces the number of classification errors compared to the basic approach to object detection and parameter estimation.
- Subjects :
- Computer science
02 engineering and technology
01 natural sciences
010309 optics
0103 physical sciences
0202 electrical engineering, electronic engineering, information engineering
lcsh:Information theory
lcsh:QC350-467
Computer vision
transport analytics
Electrical and Electronic Engineering
video sequence analysis
business.industry
Estimation theory
Video sequence
object detection
tracking
lcsh:Q350-390
Atomic and Molecular Physics, and Optics
Object detection
Computer Science Applications
image processing
020201 artificial intelligence & image processing
Artificial intelligence
business
parameter estimation
lcsh:Optics. Light
Subjects
Details
- Language :
- English
- ISSN :
- 24126179 and 01342452
- Volume :
- 44
- Issue :
- 5
- Database :
- OpenAIRE
- Journal :
- Компьютерная оптика
- Accession number :
- edsair.doi.dedup.....cb40d5aebc96a3f878675decbf2142c1