MULTI-TARGET TRACKING IN NON-OVERLAPPING SURVEILLANCE CAMERAS USING PREDEFINED REFERENCE SET

Authors

  • POOJA MAGDUM Department of E &TC, Shivaji University, Bharati Vidyapeeth’s College of Engineering, Kolhapur,
  • SACHINB. JADHAV Department of E &TC, Shivaji University, Bharati Vidyapeeth’s College of Engineering, Kolhapur,

Keywords:

AdaBoost, GentleBoost, HOG, LBP

Abstract

In this paper, we consider multi-object target tracking using video reference datasets. Our objective is detection of the target using a novel adaboost and Gentle Boost method in order to track the subjects from reference data sets. Multi-target tracking is still challenging topic which is used to find the same object across different camera views and also used to find the location and sizes of different object at different places. Furthermore extensive performance analysis of the three main partsdemonstrates usefulness of multiobject tracking. We carried out experiment to analyze discriminative power of nine features (HSV, LBP, HOG extracted on body, torso and legs) used in the appearance model for multicam dataset. For each features the RMSE and PSNR obtained.

Downloads

Published

2021-03-27

Issue

Vol. 4 No. 5 (2017): IJIERT

Section

Articles

License

Creative Commons License

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

Under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0 DEED).

You are free to:

  1. Share — copy and redistribute the material in any medium or format
  2. The licensor cannot revoke these freedoms as long as you follow the license terms.

Under the following terms:

  1. Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
  2. NonCommercial — You may not use the material for commercial purposes .
  3. NoDerivatives — If you remix, transform, or build upon the material, you may not distribute the modified material.
  4. No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Notices:

You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .

No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.

 

Rights of Authors

Authors retain the following rights:
1. Copyright and other proprietary rights relating to the article, such as patent rights,
2. the right to use the substance of the article in future works, including lectures and books,
3. the right to reproduce the article for own purposes, provided the copies are not offered for sale,
4. the right to self-archive the article.