A novel enhanced algorithm for efficient human tracking

Mehdi Gheisari, Zohreh Safari, Mohammad Almasi, Amir Hossein Pourishaban Najafabadi, Abel Sridharan, Ragesh G K, Yang Liu, Aaqif Afzaal Abbasi

Abstract


Tracking moving objects has been an issue in recent years of computer vision and image processing and human tracking makes it a more significant challenge. This category has various aspects and wide applications, such as autonomous deriving, human-robot interactions, and human movement analysis. One of the issues that have always made tracking algorithms difficult is their interaction with goal recognition methods, the mutable appearance of variable aims, and simultaneous tracking of multiple goals. In this paper, a method with high efficiency and higher accuracy was compared to the previous methods for tracking just objects using imaging with the fixed camera is introduced. The proposed algorithm operates in four steps in such a way as to identify a fixed background and remove noise from that. This background is used to subtract from movable objects. After that, while the image is being filtered, the shadows and noises of the filmed image are removed, and finally, using the bubble routing method, the mobile object will be separated and tracked. Experimental results indicated that the proposed model for detecting and tracking mobile objects works well and can improve the motion and trajectory estimation of objects in terms of speed and accuracy to a desirable level up to in terms of accuracy compared with previous methods.


Keywords


Background subtraction; Bubble routing; Deep learning; Human tracking; Image filter; Movable objects; Object tracking

Full Text:

PDF


DOI: http://doi.org/10.11591/ijict.v11i1.pp1-7

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

View IJICT Stats