Benchmarking Deep Trackers on Aerial Videos

by   Abu Md Niamul Taufique, et al.

In recent years, deep learning-based visual object trackers have achieved state-of-the-art performance on several visual object tracking benchmarks. However, most tracking benchmarks are focused on ground level videos, whereas aerial tracking presents a new set of challenges. In this paper, we compare ten trackers based on deep learning techniques on four aerial datasets. We choose top performing trackers utilizing different approaches, specifically tracking by detection, discriminative correlation filters, Siamese networks and reinforcement learning. In our experiments, we use a subset of OTB2015 dataset with aerial style videos; the UAV123 dataset without synthetic sequences; the UAV20L dataset, which contains 20 long sequences; and DTB70 dataset as our benchmark datasets. We compare the advantages and disadvantages of different trackers in different tracking situations encountered in aerial data. Our findings indicate that the trackers perform significantly worse in aerial datasets compared to standard ground level videos. We attribute this effect to smaller target size, camera motion, significant camera rotation with respect to the target, out of view movement, and clutter in the form of occlusions or similar looking distractors near tracked object.



page 5

page 8

page 17

page 23

page 24

page 25

page 26

page 27


Siam-ReID: Confuser Aware Siamese Tracker with Re-identification Feature

Siamese deep-network trackers have received significant attention in rec...

4-DoF Tracking for Robot Fine Manipulation Tasks

This paper presents two visual trackers from the different paradigms of ...

Visual Object Tracking with Discriminative Filters and Siamese Networks: A Survey and Outlook

Accurate and robust visual object tracking is one of the most challengin...

Beyond standard benchmarks: Parameterizing performance evaluation in visual object tracking

Object-to-camera motion produces a variety of apparent motion patterns t...

Predictive Visual Tracking: A New Benchmark and Baseline Approach

As a crucial robotic perception capability, visual tracking has been int...

An Analysis of Object Representations in Deep Visual Trackers

Fully convolutional deep correlation networks are integral components of...

Through-Foliage Tracking with Airborne Optical Sectioning

Detecting and tracking moving targets through foliage is difficult, and ...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.