The use of camera-equipped Unmanned Aerial Vehicles (UAVs, or “drones”) for a wide range of aerial video capturing applications, including media production, surveillance, search and rescue operations, etc., has exploded in recent years. Technological progress has led to commercially available UAVs with a degree of cognitive autonomy and perceptual capabilities, such as automated, on-line detection and tracking of target objects upon the captured footage. However, the limited computational hardware, the possibly high camera-to-target distance and the fact that both the UAV/camera and the target(s) are moving, makes it challenging to achieve both high accuracy and stable real-time performance. In this paper, the current state-of-the-art on real-time object detection/tracking is overviewed. Additionally, a relevant, modular implementation suitable for on-drone execution (running on top of the popular Robot Operating System) is presented and empirically evaluated on a number of relevant datasets. The results indicate that a sophisticated, neural network-based detection and tracking system can be deployed at real-time even on embedded devices.
Embedded UAV Real-Time Visual Object Detection and Tracking
2019-08-01
330147 byte
Conference paper
Electronic Resource
English
Real-time visual object tracking for unmanned aerial vehicles (UAVs)
European Patent Office | 2023
|REAL-TIME VISUAL OBJECT TRACKING FOR UNMANNED AERIAL VEHICLES (UAVS)
European Patent Office | 2022
|HIGH-PERFORMANCE VISUAL OBJECT TRACKING FOR EMBEDDED VISION SYSTEMS
European Patent Office | 2019
|High-performance visual object tracking for embedded vision systems
European Patent Office | 2021
|Real-time visual tracking algorithm for single moving object in clustered environment
British Library Online Contents | 2008
|