Application of Improved Bhattacharyya Coefficient Based Multi-Object Detection and Tracking Integrated Strategy

Zeng, Mingbin; Wei, Zheng; Hu, Hongchang; Yang, Xu

doi:10.1109/icnidc.2018.8525809

Cited by 3 publications

(2 citation statements)

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“…The authors of the paper [3] proposed a new object detection and tracking where both detection and tracking are integrated to get better performance. This algorithm is suitable for multi-object detection and tracking by reducing the total searching area.…”

Section: Related Workmentioning

confidence: 99%

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Efficient Moving Vehicle Detection Algorithm for Various Traffic Conditions

N*¹,

Meenakshi²

2019

IJRTE

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Many computer vision applications needs to detect moving object from an input video sequences. The main applications of this are traffic monitoring, visual surveillance, people tracking and security etc. Among these, traffic monitoring is one of the most difficult tasks in real time video processing. Many algorithms are introduced to monitor traffic accurately. But most of the cases, the detection accuracy is very less and the detection time is higher which makes the algorithms are not suitable for real time applications. In this paper, a new technique to detect moving vehicle efficiently using Modified Gaussian Mixture Model and Modified Blob Detection techniques is proposed. The modified Gaussian Mixture model generates the background from overall probability of the complete data set and by calculating the required step size from the frame differences. The modified Blob Analysis is then used to classify proper moving objects. The simulation results shows that the method accurately detect the target

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Section: Related Workmentioning

confidence: 99%

“…To get accurate σ k value, non-linear color space is considered. In such cases the density of the parameter set is defined as (3) The equation (2) is for a particular "k" and the total set of parameters becomes (4) Where, ω k =Priori probability of the surface 'k'.…”

Section: Modified Gaussian Mixture Modelmentioning

confidence: 99%