Prof. Dr. Didier Stricker
Dr. Alain Pagani
Dr. Gerd Reis
Eric Thil
Keonna Cunningham
Dr. Oliver Wasenmüller
Dr. Gabriele Bleser
Dr. Bruno Mirbach
Dr. Jason Raphael Rambach
Dr. Bertram Taetz
Dr. Muhammad Zeshan Afzal
Sk Aziz Ali
Mhd Rashed Al Koutayni
Murad Almadani
Alaa Alshubbak
Yuriy Anisimov
Jilliam Maria Diaz Barros
Ramy Battrawy
Hammad Butt
Mahdi Chamseddine
Steve Dias da Cruz
Fangwen Shu
Torben Fetzer
Ahmet Firintepe
Sophie Folawiyo
David Michael Fürst
Kamalveerkaur Garewal
Christiano Couto Gava
Leif Eric Goebel
Tewodros Amberbir Habtegebrial
Simon Häring
Khurram Hashmi
Jigyasa Singh Katrolia
Andreas Kölsch
Onorina Kovalenko
Stephan Krauß
Paul Lesur
Muhammad Jameel Nawaz Malik
Michael Lorenz
Markus Miezal
Mina Ameli
Nareg Minaskan Karabid
Mohammad Minouei
Pramod Murthy
Mathias Musahl
Peter Neigel
Manthan Pancholi
Qinzhuan Qian
Engr. Kumail Raza
Dr. Nadia Robertini
María Alejandra Sánchez Marín
Dr. Kripasindhu Sarkar
Alexander Schäfer
Pascal Schneider
René Schuster
Mohamed Selim
Lukas Stefan Staecker
Dennis Stumpf
Yongzhi Su
Xiaoying Tan
Yaxu Xie
Dr. Vladislav Golyanik
Dr. Aditya Tewari
André Luiz Brandão
Tracker Fusion on VOT Challenge: How Does It Perform and What Can We Learn About Single Trackers?
Tracker Fusion on VOT Challenge: How Does It Perform and What Can We Learn About Single Trackers?
International Conference on Computer Vision (ICCV-2015), December 11-18, Santiago, Chile
- Abstract:
- Tracker fusion i.e. the fusion of the outputs of different tracking methods is an interesting new concept. Thus it should also be considered in the VOT challenges. In this paper we evaluate the performance of tracker fusion on the VOT2013 and VOT2014 datasets. Furthermore, we utilize the fusion concept to create novel fusion based measures for evaluating trackers. Fusion based evaluation is interesting as it does not evaluate trackers independently but in the context of all other trackers. It allows us for example to identify trackers that could despite poor average performance be interesting for research in object tracking. We found e.g. that all state-of-the-art trackers lack some strengths of a simple NCC tracker. Tracker fusion can exploit this and profit from an additional NCC tracker. We raise the question: Can this also be exploited in a more direct way i.e. can we e.g. combine NCC concepts with a state-of-the-art tracker?