Comparison of Object Detection Algorithms Using Video and Thermal Images Collected from a UAS Platform: An Application of Drones in Traffic Management
There is a rapid growth of applications of Unmanned Aerial Vehicles (UAVs) in traffic management, such as traffic surveillance, monitoring, and incident detection. However, the existing literature lacks solutions to real-time incident detection while addressing privacy issues in practice. This study explored real-time vehicle detection algorithms on both visual and infrared cameras and conducted experiments comparing their performance. Red Green Blue (RGB) videos and thermal images were collected from a UAS platform along highways in the Tampa, Florida, area. Experiments were designed to quantify the performance of a real-time background subtraction-based method in vehicle detection from a stationary camera on hovering UAVs under free-flow conditions. Several parameters were set in the experiments based on the geometry of the drone and sensor relative to the roadway. The results show that a background subtraction-based method can achieve good detection performance on RGB images (F1 scores around 0.9 for most cases), and a more varied performance is seen on thermal images with different azimuth angles. The results of these experiments will help inform the development of protocols, standards, and guidance for the use of drones to detect highway congestion and provide input for the development of incident detection algorithms.
Code (0)
등록된 구현이 없습니다.
Tasks
Managementobject-detectionObject Detectionvehicle detectionSimilar Papers 제목 키워드 기반
HIT-UAV: A high-altitude infrared thermal dataset for Unmanned Aerial Vehicle-based object detection
We present the HIT-UAV dataset, a high-altitude infrared thermal dataset for object detection applications on Unmanned Aerial Vehicles (UAVs). The dataset comprises 2,898 infrared thermal images extracted from 43,470 fra…
Objectobject-detectionObject DetectionEnhancing Object Detection in Adverse Conditions using Thermal Imaging
Autonomous driving relies on deriving understanding of objects and scenes through images. These images are often captured by sensors in the visible spectrum. For improved detection capabilities we propose the use of ther…
Autonomous DrivingObjectobject-detectionObject Detection+1A real-time algorithm for human action recognition in RGB and thermal video
Monitoring the movement and actions of humans in video in real-time is an important task. We present a deep learning based algorithm for human action recognition for both RGB and thermal cameras. It is able to detect and…
Action RecognitionGPUobject-detectionObject Detection+3Erasure-based Interaction Network for RGBT Video Object Detection and A Unified Benchmark
Recently, many breakthroughs are made in the field of Video Object Detection (VOD), but the performance is still limited due to the imaging limitations of RGB sensors in adverse illumination conditions. To alleviate this…
object-detectionObject DetectionVideo Object DetectionVisible-Thermal Tiny Object Detection: A Benchmark Dataset and Baselines
Small object detection (SOD) has been a longstanding yet challenging task for decades, with numerous datasets and algorithms being developed. However, they mainly focus on either visible or thermal modality, while visibl…
Diversityobject-detectionObject DetectionSmall Object Detection