In this paper, we propose a novel structural correlation filter (SCF) model for robust visual
tracking. The proposed SCF model takes part-based tracking strategies into account in a …

Robust object tracking requires knowledge and understanding of the object being tracked:
its appearance, its motion, and how it changes over time. A tracker must be able to modify its …

This paper proposes a new visual tracking algorithm, which leverages the merits of both
template matching approaches and classification models for long-term object detection and …

Animal pose estimation and tracking (APT) is a fundamental task for detecting and tracking
animal keypoints from a sequence of video frames. Previous animal-related datasets focus …

We formulate tracking as an online decision-making process, where a tracking agent must
follow an object despite ambiguous image frames and a limited computational budget …

The empirical study proposes a model for investigating the effect of entrepreneurial
leadership on job insecurity and employee psychological wellbeing during COVID-19 based …

This paper investigates how to integrate the complementary information from RGB and
thermal (RGB-T) sources for object tracking. We propose a novel Convolutional Neural …

Over these years, Correlation Filter-based Trackers (CFTs) have aroused increasing
interests in the field of visual object tracking, and have achieved extremely compelling …

In this paper, we propose a novel correlation particle filter (CPF) for robust visual tracking.
Instead of a simple combination of a correlation filter and a particle filter, we exploit and …

We propose an online tracking algorithm that adaptively models target appearances based
on an online gradient boosting decision tree. Our algorithm is particularly useful for non-rigid …