TY - JOUR
T1 - Counting Static Targets Using an Unmanned Aerial Vehicle On-the-Fly and Autonomously
AU - Darji, Dhruvil
AU - Vejarano, Gustavo
N1 - export records of this page first 1000 hits only: see FAQ: BHT key: ask others view this toc in Applications I Reconstruction Scene Semantics Advances in Deep Vision 3D Objects Applications II Object Detection Attentive Vision Software Tools for Vision and Robotics Tracking Localization Image Analytics Posters: Computer Vision Posters: 3D Vision Posters: Detecting People Other Animals Posters: Motion and Tracking Posters: Mapping / SLAM Posters: Deep Learning
PY - 2018/5/8
Y1 - 2018/5/8
N2 - The counting of static targets on ground using an unmanned aerial vehicle (UAV) is proposed. To the best of our knowledge, this is the first paper to do such counting on-the-fly and autonomously. The flight path is programmed before take-off. The UAV captures images of the ground which are processed consecutively on-the-fly to count the number of targets along the flight path. Each image is processed using the proposed target-counting algorithm. First, targets' centers are detected in the current image, and second, the targets that were not covered in previous images are identified and counted. The performance of the algorithm depends on its ability to identify in the current image what targets were already counted in previous images, and this ability is affected by the limited accuracy of the UAV to stay on the flight path in the presence of wind. In the experimental evaluation, targets were distributed on ground on three different configurations: one line of targets along the flight path, parallel lines of targets at an angle with the flight path, and random. The accuracy of the target count was 96.0%, 88.9% and 91.9% respectively.
AB - The counting of static targets on ground using an unmanned aerial vehicle (UAV) is proposed. To the best of our knowledge, this is the first paper to do such counting on-the-fly and autonomously. The flight path is programmed before take-off. The UAV captures images of the ground which are processed consecutively on-the-fly to count the number of targets along the flight path. Each image is processed using the proposed target-counting algorithm. First, targets' centers are detected in the current image, and second, the targets that were not covered in previous images are identified and counted. The performance of the algorithm depends on its ability to identify in the current image what targets were already counted in previous images, and this ability is affected by the limited accuracy of the UAV to stay on the flight path in the presence of wind. In the experimental evaluation, targets were distributed on ground on three different configurations: one line of targets along the flight path, parallel lines of targets at an angle with the flight path, and random. The accuracy of the target count was 96.0%, 88.9% and 91.9% respectively.
UR - https://digitalcommons.lmu.edu/cs_fac/23/
U2 - 10.1109/CRV.2018.00037
DO - 10.1109/CRV.2018.00037
M3 - Article
SP - 206
EP - 213
JO - 2018 15th Conference on Computer and Robot Vision (CRV)
JF - 2018 15th Conference on Computer and Robot Vision (CRV)
ER -