Multimedia ResearchISSN:2582-547X

Multi-Object Tracking Using Improved Lion-Based Clustering With Reference To LVP Pattern

Abstract

MOT in video surveillance is still a challenging aspect due to various complexities like complex occlusion, different poses, small sizes of objects, and so on. Henceforth more research works are under process that concentrate on solving object tracking problems by considering both spatial and visual information. Under these circumstances, this paper aims to propose a new MOT model that tracks the objects precisely. At first, the visibility model of tracking is proposed based on the second derivative model, which considers the second derivative function to predict the objects. Secondly, a spatial tracking model is developed using a nonlinear function. Meanwhile, the objects are tracked by subjecting a new optimization algorithm namely Female Update enabled Cub Updating in LA (FU-CU-LA) that effectively tracks the objects even if moved to the subsequent frames. Subsequently, spatial tracking and optimization-based tracking are integrated, and finally, the resultant center point is integrated with the visual tracking model. The proposed FU-CU-LA-based tacking system is compared with other models to certain measures and proves the superiority of the proposed work.

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DOI : https://doi.org/10.46253/j.mr.v7i2.a2

Author information

Affiliations

Department of CSE Neil Gogte Institute of Technology, Hyderabad, India aadhimarumalla@gmail.com

Publisher Information

  • Received

    19 October

  • Revised

    8 November

  • Accepted

    13 March

Keywords
Multi-Object Tracking; Video Surveillance; Optimization; LA; Spatial Tracking Model.

Publisher : Resbee Info Technologies Pvt Ltd