Scale-adaptive object tracking with diverse ensembles

Sara Elkerdawy*, Abdelrahman Eldesokey, Ahmed Salaheldin, Mohamed ElHelw

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Tracking by detection techniques have recently been gaining increased attention in visual object tracking due to their promising results in applications such as robotics, surveillance, traffic monitoring, to name a few. These techniques often employ semi-supervised appearance model where a set of samples are continuously extracted around the object to train a discriminant classifier between the object and the background whereas real-time performance is attained by using reduced object representations as in the case of the compressive tracking algorithm. However, because they rely on self updating, visual tracking algorithms are prone to visual drift especially when the object undergoes significant scale changes. In this paper, we present a real-time visual tracker that is adaptive to appearance and scale variations. The algorithm is divided into two phases: (1) object localization using a diverse ensemble of multiple random projections, and (2) scale estimation between an updated object template and the localized object position computed in the first phase. Experimental results obtained with publicly-available visual tracking datasets demonstrate that the proposed tracker provides robust tracking in case of significant scale variations with more accurate overlap and less visual drift.

Original languageEnglish (US)
Title of host publicationAdvances in Visual Computing - 10th International Symposium, ISVC 2014, Proceedings
EditorsGeorge Bebis, Richard Boyle, Bahram Parvin, Darko Koracin, Ryan McMahan, Jason Jerald, Hui Zhang, Steven M. Drucker, Kambhamettu Chandra, El Choubassi Maha, Zhigang Deng, Mark Carlson
PublisherSpringer Verlag
Number of pages8
ISBN (Electronic)9783319142487
StatePublished - 2014
Event10th International Symposium on Visual Computing, ISVC 2014 - Las Vegas, United States
Duration: Dec 8 2014Dec 10 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference10th International Symposium on Visual Computing, ISVC 2014
Country/TerritoryUnited States
CityLas Vegas


  • Diverse Ensembles
  • Random Projections
  • Visual Tracking

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


Dive into the research topics of 'Scale-adaptive object tracking with diverse ensembles'. Together they form a unique fingerprint.

Cite this