Visual tracking

Intermittent Contextual Learning for Keyfilter-Aware UAV Object Tracking Using Deep Convolutional Feature

Correlation filter-based tracking has been widely applied in unmanned aerial vehicle (UAV) with high efficiency. However, it has two imperfections, i.e., boundary effect and filter corruption. Several methods enlarging the search area can mitigate …

BiCF: Learning Bidirectional Incongruity-Aware Correlation Filter for Efficient UAV Object Tracking

Correlation filters (CFs) have shown excellent performance in unmanned aerial vehicle (UAV) tracking scenarios due to their high computational efficiency. During the UAV tracking process, viewpoint variations are usually accompanied by changes in the …

Training-Set Distillation for Real-Time UAV Object Tracking

Correlation filter (CF) has recently exhibited promising performance in visual object tracking for unmanned aerial vehicle (UAV). Such online learning method heavily depends on the quality of the training-set, yet complicated aerial scenarios like …

Keyfilter-Aware Real-Time UAV Object Tracking

Correlation filter-based tracking has been widely applied in unmanned aerial vehicle (UAV) with high efficiency. However, it has two imperfections, i.e., boundary effect and filter corruption. Several methods enlarging the search area can mitigate …

Robust Multi-Kernelized Correlators for UAV Tracking with Adaptive Context Analysis and Dynamic Weighted Filters

In recent years, the correlation filter (CF)-based method has significantly advanced in the tracking for unmanned aerial vehicles (UAV). As the core component of most trackers, CF is a discriminative classifier to distinguish the object from the …

Part-Based Background-Aware Tracking for UAV with Convolutional Features

In recent years, visual tracking is a challenging task in UAV applications. The standard correlation filter (CF) has been extensively applied for UAV object tracking. However, the CF-based tracker severely suffers from boundary effects and cannot …

Correlation Filter-Based Visual Tracking for UAV with Online Multi-Feature Learning

In this paper, a novel online learning-based tracker is presented for the unmanned aerial vehicle (UAV) in different types of tracking applications.

Visual Tracking With Online Structural Similarity-Based Weighted Multiple Instance Learning

This paper presents an online adaptive tracker, which employs a novel weighted multiple instance learning (WMIL) approach.In the proposed tracker, both positive and negative sample importances are integrated into an online learning mechanism for …