Visual tracking extensions for accurate target recovery in low frame rate videos

Yoav Liberman, Adi Perry

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


Visual tracking in low frame rate videos has many inherent difficulties for achieving accurate target recovery, such as occlusions, abrupt motions and rapid pose changes. Thus, conventional tracking methods cannot be applied reliably. In this paper, we offer a new scheme for tracking objects in low frame rate videos. We present a method of integrating multiple metrics for template matching, as an extension for the particle filter. By inspecting a large data set of videos for tracking, we show that our method not only outperforms other related benchmarks in the field, but it also achieves better results both visually and quantitatively, once compared to actual ground truth data.

Original languageEnglish
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 pages12
ISBN (Electronic)9783319142487
StatePublished - 2014
Externally publishedYes
Event10th International Symposium on Visual Computing, ISVC 2014 - Las Vegas, United States
Duration: 8 Dec 201410 Dec 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

Bibliographical note

Publisher Copyright:
© Springer International Publishing Switzerland 2014.


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