Most thermal infrared (TIR) tracking methods are discriminative, treating the tracking
problem as a classification task. However, the objective of the classifier (label prediction) is …

The performance of the tracking task directly depends on target object appearance features.
Therefore, a robust method for constructing appearance features is crucial for avoiding …

In the most tracking approaches, a score function is utilized to determine which candidate is
the optimal one by measuring the similarity between the candidate and the template …

In this paper, a new robust mean shift tracker is proposed by utilizing the joint color and
texture histogram. The contribution of our work is to take local phase quantization (LPQ) …

Occlusion is one of the most challenging problems in visual object tracking. Recently, a lot of
discriminative methods have been proposed to deal with this problem. For the discriminative …

Discriminative methods have been widely applied to construct the appearance model for
visual tracking. Most existing methods incorporate online updating strategy to adapt to the …

Visual object tracking is a challenging task in the field of computer vision, due to many
constraints like scene variation, occlusion, cluttered background and higher data size. The …

We consider a control proximal gradient algorithm (CPGA) for solving the minimization of a
nonsmooth convex function. In particular, the convex function is an ℓ _1 ℓ 1 regularized least …

In this paper, we propose a novel thermal infrared (TIR) tracker via a deep Siamese
convolutional neural network (CNN), named Siamesetir. Different from the most existing …

Although recently developed trackers have shown excellent performance even when
tracking fast moving and shape changing objects with variable scale and orientation, the …