A Drone-based Approach to Monocular-Camera Distance Estimation using Computer Vision: A Tool for Surround View System Validation
Publicerad
Författare
Typ
Examensarbete för masterexamen
Master's Thesis
Master's Thesis
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
Autonomous parking is a field within ADAS/AD that requires exceptionally high
spatial precision, given the close proximity to vehicles, people, and other obstacles.
Surround-view camera systems are often used to both map the environment
and estimate the vehicle’s position by creating a stitched birds-eye view image of
the vehicle’s surroundings. To aid the development and evaluation of these systems,
high-accuracy distance measurements between the car and its environment are
needed. This thesis presents a drone-based system that utilizes a monocular camera
to estimate ground-level distances in parking environments. Using car-mounted AR
fiducial markers as reference objects, the system achieves centimeter-level accuracy
at distances up to 10 meters relative to the car. In addition to the distance estimation
pipeline, a vision-based drone controller was implemented to track a target car
and maintain optimal positioning for video data collection during dynamic parking
scenarios. Real-world testing demonstrates that the proposed method yields consistent
results, highlighting its potential as a low-cost and flexible tool for generating
ground truth distances. To our knowledge, this is the first application of monocular
drone-based distance estimation for the development and validation of ADAS/AD
systems.
Beskrivning
Ämne/nyckelord
Monocular Camera Distance Estimation, ADAS, Autonomous Parking, Surround View 360-camera, Vision-based Drone Control, PID