Visual object tracking is a standard function of computer vision that has been the source of
numerous propositions. This diversity of approaches leads to the idea of trying to fuse them …

The main objective of this work is to evaluate a simple fusion system which improves the
performance of several object trackers, within a methodological and rigorous evaluation …

Visual object tracking is a fundamental function of computer vision that has been the object
of numerous studies. The diversity of the proposed approaches leads to the idea of trying to …

Existing tracking methods vary strongly in their approach and therefore have different
strengths and weaknesses. For example, a single tracking algorithm may be good at …

We propose a decision-level approach to fuse the output of multiple trackers based on their
estimated individual performance. The proposed approach is composed of three main steps …

Visual object tracking is a challenging task in computer vision, especially if there are no
constraints to the scenario and the objects are arbitrary. The number of tracking algorithms is …

In this paper, we propose a novel method for visual object tracking called HMMTxD. The
method fuses observations from complementary out-of-the box trackers and a detector by …

Visual object tracking is a challenging task in computer vision, especially if there are no
constraints to the scenario and the objects are arbitrary. The number of tracking algorithms is …

We propose in this paper a tracking algorithm which is able to adapt itself to different scene
contexts. A feature pool is used to compute the matching score between two detected …

In this paper, we tackle the tracking problem from a fusion angle and propose a
disagreement-based approach. While most existing fusion-based tracking algorithms work …